fix: Disable frosted glass - imgui-bundle cannot sample OpenGL textures

The imgui-bundle backend cannot sample from our OpenGL FBO textures. This is a fundamental incompatibility. Frosted glass feature disabled to allow app to run.
fix(shader): Use custom_background callback to render blurred texture
2026-03-13 21:45:51 -04:00 · 2026-03-13 21:44:55 -04:00 · 2026-03-13 21:35:23 -04:00 · 2026-03-13 21:28:39 -04:00 · 2026-03-13 21:24:14 -04:00 · 2026-03-13 21:08:13 -04:00
227 changed files with 11645 additions and 958 deletions
@@ -2,8 +2,7 @@
 description: Fast, read-only agent for exploring the codebase structure
 mode: subagent
 model: MiniMax-M2.5
-temperature: 0.0
+temperature: 0.2
 steps: 8
 permission:
  edit: deny
  bash:
@@ -22,6 +21,7 @@ You are a fast, read-only agent specialized for exploring codebases. Use this wh
 You MUST use Manual Slop's MCP tools. Native OpenCode tools are unreliable.
 ### Read-Only MCP Tools (USE THESE)
 | Native Tool | MCP Tool |
 |-------------|----------|
 | `read` | `manual-slop_read_file` |
@@ -34,12 +34,14 @@ You MUST use Manual Slop's MCP tools. Native OpenCode tools are unreliable.
 | - | `manual-slop_get_tree` (directory structure) |
 ## Capabilities
 - Find files by name patterns or glob
 - Search code content with regex
 - Navigate directory structures
 - Summarize file contents
 ## Limitations
 - **READ-ONLY**: Cannot modify any files
 - **NO EXECUTION**: Cannot run tests or scripts
 - **EXPLORATION ONLY**: Use for discovery, not implementation
@@ -62,7 +64,9 @@ Use: `manual-slop_get_tree` or `manual-slop_list_directory`
 Use: `manual-slop_get_file_summary` for heuristic summary
 ## Report Format
 Return concise findings with file:line references:
 ```
 ## Findings
@@ -2,8 +2,7 @@
 description: General-purpose agent for researching complex questions and executing multi-step tasks
 mode: subagent
 model: MiniMax-M2.5
-temperature: 0.2
+temperature: 0.3
 steps: 15
 ---
 A general-purpose agent for researching complex questions and executing multi-step tasks. Has full tool access (except todo), so it can make file changes when needed.
@@ -13,6 +12,7 @@ A general-purpose agent for researching complex questions and executing multi-st
 You MUST use Manual Slop's MCP tools. Native OpenCode tools are unreliable.
 ### Read MCP Tools (USE THESE)
 | Native Tool | MCP Tool |
 |-------------|----------|
 | `read` | `manual-slop_read_file` |
@@ -26,6 +26,7 @@ You MUST use Manual Slop's MCP tools. Native OpenCode tools are unreliable.
 | - | `manual-slop_get_tree` (directory structure) |
 ### Edit MCP Tools (USE THESE)
 | Native Tool | MCP Tool |
 |-------------|----------|
 | `edit` | `manual-slop_edit_file` (find/replace, preserves indentation) |
@@ -35,11 +36,13 @@ You MUST use Manual Slop's MCP tools. Native OpenCode tools are unreliable.
 | `edit` | `manual-slop_py_set_var_declaration` (replace variable) |
 ### Shell Commands
 | Native Tool | MCP Tool |
 |-------------|----------|
 | `bash` | `manual-slop_run_powershell` |
 ## Capabilities
 - Research and answer complex questions
 - Execute multi-step tasks autonomously
 - Read and write files as needed
@@ -47,13 +50,22 @@ You MUST use Manual Slop's MCP tools. Native OpenCode tools are unreliable.
 - Coordinate multiple operations
 ## When to Use
 - Complex research requiring multiple file reads
 - Multi-step implementation tasks
 - Tasks requiring autonomous decision-making
 - Parallel execution of related operations
 ## Code Style (for Python)
 - 1-space indentation
 - NO COMMENTS unless explicitly requested
 - Type hints where appropriate
 ## Report Format
 Return detailed findings with evidence:
 ```
 ## Task: [Original task]
@@ -2,8 +2,7 @@
 description: Tier 1 Orchestrator for product alignment, high-level planning, and track initialization
 mode: primary
 model: MiniMax-M2.5
-temperature: 0.4
+temperature: 0.5
 steps: 50
 permission:
  edit: ask
  bash:
@@ -17,6 +16,12 @@ STRICT SYSTEM DIRECTIVE: You are a Tier 1 Orchestrator.
 Focused on product alignment, high-level planning, and track initialization.
 ONLY output the requested text. No pleasantries.
 ## Context Management
 **MANUAL COMPACTION ONLY** — Never rely on automatic context summarization.
 Use `/compact` command explicitly when context needs reduction.
 Preserve full context during track planning and spec creation.
 ## CRITICAL: MCP Tools Only (Native Tools Banned)
 You MUST use Manual Slop's MCP tools. Native OpenCode tools are unreliable.
@@ -69,7 +74,7 @@ Before ANY other action:
 Read at session start:
- All immediate files in ./conductor, a listing of all direcotires within ./conductor/tracks, ./conductor/archive.
+- All immediate files in ./conductor, a listing of all directories within ./conductor/tracks, ./conductor/archive.
 - All docs in ./docs
 - AST Skeleton summaries of: ./src, ./simulation, ./tests, ./scripts python files.
@@ -90,7 +95,7 @@ When planning tracks that touch core systems, consult the deep-dive docs:
 - Set up the project environment (`/conductor-setup`)
 - Delegate track execution to the Tier 2 Tech Lead
-## The Surgical Methodology
+## The Surgical Methodology (MANDATORY)
 ### 1. MANDATORY: Audit Before Specifying
@@ -100,10 +105,16 @@ Use `manual-slop_py_get_code_outline`, `manual-slop_py_get_definition`,
 Document existing implementations with file:line references in a
 "Current State Audit" section in the spec.
 **FAILURE TO AUDIT = TRACK FAILURE** — Previous tracks failed because specs
 asked to implement features that already existed.
 ### 2. Identify Gaps, Not Features
 Frame requirements around what's MISSING relative to what exists.
 GOOD: "The existing `_render_mma_dashboard` (gui_2.py:2633-2724) has a token usage table but no cost column."
 BAD: "Build a metrics dashboard with token and cost tracking."
 ### 3. Write Worker-Ready Tasks
 Each plan task must be executable by a Tier 3 worker:
@@ -162,6 +173,6 @@ Focus: {One-sentence scope}
 - Do NOT batch commits - commit per-task
 - Do NOT skip phase verification
 - Do NOT use native `edit` tool - use MCP tools
- DO NOT SKIP A TEST IN PYTEST JUSTS BECAUSE ITS BROKEN AND HAS NO TRIVIAL SOLUTION OR FIX.
+- DO NOT SKIP A TEST IN PYTEST JUST BECAUSE ITS BROKEN AND HAS NO TRIVIAL SOLUTION OR FIX.
- DO NOT SIMPLIFY A TEST JUST BECAUSE IT HAS NO TRIVAL SOLUTION TO FIX.
+- DO NOT SIMPLIFY A TEST JUST BECAUSE IT HAS NO TRIVIAL SOLUTION TO FIX.
- DO NOT CREATE MOCK PATCHES TO PSUEDO API CALLS OR HOOKS BECAUSE THE APP SOURCE WAS CHANGED. ADAPT TESTS PROPERLY.
+- DO NOT CREATE MOCK PATCHES TO PSEUDO API CALLS OR HOOKS BECAUSE THE APP SOURCE WAS CHANGED. ADAPT TESTS PROPERLY.
@@ -1,9 +1,7 @@
 ---
 description: Tier 2 Tech Lead for architectural design and track execution with persistent memory
 mode: primary
-model: MiniMax-M2.5
+temperature: 0.4
 temperature: 0.2
 steps: 100
 permission:
  edit: ask
  bash: ask
@@ -13,6 +11,12 @@ STRICT SYSTEM DIRECTIVE: You are a Tier 2 Tech Lead.
 Focused on architectural design and track execution.
 ONLY output the requested text. No pleasantries.
 ## Context Management
 **MANUAL COMPACTION ONLY** � Never rely on automatic context summarization.
 Use `/compact` command explicitly when context needs reduction.
 You maintain PERSISTENT MEMORY throughout track execution � do NOT apply Context Amnesia to your own session.
 ## CRITICAL: MCP Tools Only (Native Tools Banned)
 You MUST use Manual Slop's MCP tools. Native OpenCode tools are unreliable.
@@ -84,6 +88,16 @@ Before ANY other action:
 3. Delegate to Tier 3 via Task tool
 4. Verify result
 ## Pre-Delegation Checkpoint (MANDATORY)
 Before delegating ANY dangerous or non-trivial change to Tier 3:
 ```powershell
 git add .
 ```
 **WHY**: If a Tier 3 Worker fails or incorrectly runs `git restore`, you will lose ALL prior AI iterations for that file if it wasn't staged/committed.
 ## Architecture Fallback
 When implementing tracks that touch core systems, consult the deep-dive docs:
@@ -92,6 +106,7 @@ When implementing tracks that touch core systems, consult the deep-dive docs:
 - `docs/guide_tools.md`: MCP Bridge security, 26-tool inventory, Hook API endpoints
 - `docs/guide_mma.md`: Ticket/Track data structures, DAG engine, ConductorEngine
 - `docs/guide_simulations.md`: live_gui fixture, Puppeteer pattern, mock provider
 - `docs/guide_meta_boundary.md`: Clarification of ai agent tools making the application vs the application itself.
 ## Responsibilities
@@ -114,16 +129,18 @@ Before implementing:
 ### 2. Red Phase: Write Failing Tests
- Pre-delegation checkpoint: Stage current progress (`git add .`)
+- **Pre-delegation checkpoint**: Stage current progress (`git add .`)
 - Zero-assertion ban: Tests MUST have meaningful assertions
 - Delegate test creation to Tier 3 Worker via Task tool
 - Run tests and confirm they FAIL as expected
 - **CONFIRM FAILURE** � this is the Red phase
 ### 3. Green Phase: Implement to Pass
- Pre-delegation checkpoint: Stage current progress
+- **Pre-delegation checkpoint**: Stage current progress (`git add .`)
 - Delegate implementation to Tier 3 Worker via Task tool
 - Run tests and confirm they PASS
 - **CONFIRM PASS** � this is the Green phase
 ### 4. Refactor Phase (Optional)
@@ -134,12 +151,12 @@ Before implementing:
 After completing each task:
-1. Stage changes: `git add .`
+1. Stage changes: `manual-slop_run_powershell` with `git add .`
 2. Commit with clear message: `feat(scope): description`
 3. Get commit hash: `git log -1 --format="%H"`
 4. Attach git note: `git notes add -m "summary" <hash>`
 5. Update plan.md: Mark task `[x]` with commit SHA
-6. Commit plan update
+6. Commit plan update: `git add plan.md && git commit -m "conductor(plan): Mark task complete"`
 ## Delegation via Task Tool
@@ -193,6 +210,6 @@ When all tasks in a phase are complete:
 - Do NOT batch commits - commit per-task
 - Do NOT skip phase verification
 - Do NOT use native `edit` tool - use MCP tools
- DO NOT SKIP A TEST IN PYTEST JUSTS BECAUSE ITS BROKEN AND HAS NO TRIVIAL SOLUTION OR FIX.
+- DO NOT SKIP A TEST IN PYTEST JUST BECAUSE ITS BROKEN AND HAS NO TRIVIAL SOLUTION OR FIX.
- DO NOT SIMPLIFY A TEST JUST BECAUSE IT HAS NO TRIVAL SOLUTION TO FIX.
+- DO NOT SIMPLIFY A TEST JUST BECAUSE IT HAS NO TRIVIAL SOLUTION TO FIX.
- DO NOT CREATE MOCK PATCHES TO PSUEDO API CALLS OR HOOKS BECAUSE THE APP SOURCE WAS CHANGED. ADAPT TESTS PROPERLY.
+- DO NOT CREATE MOCK PATCHES TO PSEUDO API CALLS OR HOOKS BECAUSE THE APP SOURCE WAS CHANGED. ADAPT TESTS PROPERLY.
@@ -2,8 +2,7 @@
 description: Stateless Tier 3 Worker for surgical code implementation and TDD
 mode: subagent
 model: MiniMax-M2.5
-temperature: 0.1
+temperature: 0.3
 steps: 20
 permission:
  edit: allow
  bash: allow
@@ -13,11 +12,17 @@ STRICT SYSTEM DIRECTIVE: You are a stateless Tier 3 Worker (Contributor).
 Your goal is to implement specific code changes or tests based on the provided task.
 Follow TDD and return success status or code changes. No pleasantries, no conversational filler.
 ## Context Amnesia
 You operate statelessly. Each task starts fresh with only the context provided.
 Do not assume knowledge from previous tasks or sessions.
 ## CRITICAL: MCP Tools Only (Native Tools Banned)
 You MUST use Manual Slop's MCP tools. Native OpenCode tools are unreliable.
 ### Read MCP Tools (USE THESE)
 | Native Tool | MCP Tool |
 |-------------|----------|
 | `read` | `manual-slop_read_file` |
@@ -30,6 +35,7 @@ You MUST use Manual Slop's MCP tools. Native OpenCode tools are unreliable.
 | - | `manual-slop_get_file_slice` (read specific line range) |
 ### Edit MCP Tools (USE THESE - BAN NATIVE EDIT)
 | Native Tool | MCP Tool |
 |-------------|----------|
 | `edit` | `manual-slop_edit_file` (find/replace, preserves indentation) |
@@ -39,17 +45,15 @@ You MUST use Manual Slop's MCP tools. Native OpenCode tools are unreliable.
 | `edit` | `manual-slop_py_set_var_declaration` (replace variable) |
 ### Shell Commands
 | Native Tool | MCP Tool |
 |-------------|----------|
 | `bash` | `manual-slop_run_powershell` |
 ## Context Amnesia
 You operate statelessly. Each task starts fresh with only the context provided.
 Do not assume knowledge from previous tasks or sessions.
 ## Task Start Checklist (MANDATORY)
 Before implementing:
 1. [ ] Read task prompt - identify WHERE/WHAT/HOW/SAFETY
 2. [ ] Use skeleton tools for files >50 lines (`manual-slop_py_get_skeleton`, `manual-slop_get_file_summary`)
 3. [ ] Verify target file and line range exists
@@ -58,19 +62,24 @@ Before implementing:
 ## Task Execution Protocol
 ### 1. Understand the Task
 Read the task prompt carefully. It specifies:
 - **WHERE**: Exact file and line range to modify
 - **WHAT**: The specific change required
 - **HOW**: Which API calls, patterns, or data structures to use
 - **SAFETY**: Thread-safety constraints if applicable
 ### 2. Research (If Needed)
 Use MCP tools to understand the context:
 - `manual-slop_read_file` - Read specific file sections
 - `manual-slop_py_find_usages` - Search for patterns
 - `manual-slop_search_files` - Find files by pattern
 ### 3. Implement
 - Follow the exact specifications provided
 - Use the patterns and APIs specified in the task
 - Use 1-space indentation for Python code
@@ -78,31 +87,39 @@ Use MCP tools to understand the context:
 - Use type hints where appropriate
 ### 4. Verify
 - Run tests if specified: `manual-slop_run_powershell` with `uv run pytest ...`
 - Check for syntax errors: `manual-slop_py_check_syntax`
 - Verify the change matches the specification
 ### 5. Report
 Return a concise summary:
 - What was changed
 - Where it was changed
 - Any issues encountered
 ## Code Style Requirements
 - **NO COMMENTS** unless explicitly requested
 - 1-space indentation for Python code
 - Type hints where appropriate
 - Internal methods/variables prefixed with underscore
 ## Quality Checklist
 Before reporting completion:
 - [ ] Change matches the specification exactly
 - [ ] No unintended modifications
 - [ ] No syntax errors
 - [ ] Tests pass (if applicable)
 ## Blocking Protocol
 If you cannot complete the task:
 1. Start your response with `BLOCKED:`
 2. Explain exactly why you cannot proceed
 3. List what information or changes would unblock you
@@ -110,11 +127,10 @@ If you cannot complete the task:
 ## Anti-Patterns (Avoid)
 - Do NOT implement code directly - delegate to Tier 3 Workers
 - Do NOT skip TDD phases
 - Do NOT batch commits - commit per-task
 - Do NOT skip phase verification
 - Do NOT use native `edit` tool - use MCP tools
- DO NOT SKIP A TEST IN PYTEST JUSTS BECAUSE ITS BROKEN AND HAS NO TRIVIAL SOLUTION OR FIX.
+- Do NOT read full large files - use skeleton tools first
- DO NOT SIMPLIFY A TEST JUST BECAUSE IT HAS NO TRIVAL SOLUTION TO FIX.
+- Do NOT add comments unless requested
- DO NOT CREATE MOCK PATCHES TO PSUEDO API CALLS OR HOOKS BECAUSE THE APP SOURCE WAS CHANGED. ADAPT TESTS PROPERLY.
+- Do NOT modify files outside the specified scope
 - DO NOT SKIP A TEST IN PYTEST JUST BECAUSE ITS BROKEN AND HAS NO TRIVIAL SOLUTION OR FIX.
 - DO NOT SIMPLIFY A TEST JUST BECAUSE IT HAS NO TRIVIAL SOLUTION TO FIX.
 - DO NOT CREATE MOCK PATCHES TO PSEUDO API CALLS OR HOOKS BECAUSE THE APP SOURCE WAS CHANGED. ADAPT TESTS PROPERLY.
@@ -2,8 +2,7 @@
 description: Stateless Tier 4 QA Agent for error analysis and diagnostics
 mode: subagent
 model: MiniMax-M2.5
-temperature: 0.0
+temperature: 0.2
 steps: 5
 permission:
  edit: deny
  bash:
@@ -17,11 +16,17 @@ STRICT SYSTEM DIRECTIVE: You are a stateless Tier 4 QA Agent.
 Your goal is to analyze errors, summarize logs, or verify tests.
 ONLY output the requested analysis. No pleasantries.
 ## Context Amnesia
 You operate statelessly. Each analysis starts fresh.
 Do not assume knowledge from previous analyses or sessions.
 ## CRITICAL: MCP Tools Only (Native Tools Banned)
 You MUST use Manual Slop's MCP tools. Native OpenCode tools are unreliable.
 ### Read-Only MCP Tools (USE THESE)
 | Native Tool | MCP Tool |
 |-------------|----------|
 | `read` | `manual-slop_read_file` |
@@ -35,17 +40,15 @@ You MUST use Manual Slop's MCP tools. Native OpenCode tools are unreliable.
 | - | `manual-slop_get_file_slice` (read specific line range) |
 ### Shell Commands
 | Native Tool | MCP Tool |
 |-------------|----------|
 | `bash` | `manual-slop_run_powershell` |
 ## Context Amnesia
 You operate statelessly. Each analysis starts fresh.
 Do not assume knowledge from previous analyses or sessions.
 ## Analysis Start Checklist (MANDATORY)
 Before analyzing:
 1. [ ] Read error output/test failure completely
 2. [ ] Identify affected files from traceback
 3. [ ] Use skeleton tools for files >50 lines (`manual-slop_py_get_skeleton`)
@@ -54,16 +57,20 @@ Before analyzing:
 ## Analysis Protocol
 ### 1. Understand the Error
 Read the provided error output, test failure, or log carefully.
 ### 2. Investigate
 Use MCP tools to understand the context:
 - `manual-slop_read_file` - Read relevant source files
 - `manual-slop_py_find_usages` - Search for related patterns
 - `manual-slop_search_files` - Find related files
 - `manual-slop_get_git_diff` - Check recent changes
 ### 3. Root Cause Analysis
 Provide a structured analysis:
 ```
@@ -86,28 +93,30 @@ Provide a structured analysis:
 ```
 ## Limitations
 - **READ-ONLY**: Do NOT modify any files
 - **ANALYSIS ONLY**: Do NOT implement fixes
 - **NO ASSUMPTIONS**: Base analysis only on provided context and tool output
 ## Quality Checklist
 - [ ] Analysis is based on actual code/file content
 - [ ] Root cause is specific, not generic
 - [ ] Evidence includes file:line references
 - [ ] Recommendations are actionable but not implemented
 ## Blocking Protocol
 If you cannot analyze the error:
 1. Start your response with `CANNOT ANALYZE:`
 2. Explain what information is missing
 3. List what would be needed to complete the analysis
 ## Anti-Patterns (Avoid)
- Do NOT implement code directly - delegate to Tier 3 Workers
+- Do NOT implement fixes - analysis only
- Do NOT skip TDD phases
+- Do NOT read full large files - use skeleton tools first
- Do NOT batch commits - commit per-task
+- DO NOT SKIP A TEST IN PYTEST JUST BECAUSE ITS BROKEN AND HAS NO TRIVIAL SOLUTION OR FIX.
- Do NOT skip phase verification
+- DO NOT SIMPLIFY A TEST JUST BECAUSE IT HAS NO TRIVIAL SOLUTION TO FIX.
- DO NOT SKIP A TEST IN PYTEST JUSTS BECAUSE ITS BROKEN AND HAS NO TRIVIAL SOLUTION OR FIX.
+- DO NOT CREATE MOCK PATCHES TO PSEUDO API CALLS OR HOOKS BECAUSE THE APP SOURCE WAS CHANGED. ADAPT TESTS PROPERLY.
 - DO NOT SIMPLIFY A TEST JUST BECAUSE IT HAS NO TRIVAL SOLUTION TO FIX.
 - DO NOT CREATE MOCK PATCHES TO PSUEDO API CALLS OR HOOKS BECAUSE THE APP SOURCE WAS CHANGED. ADAPT TESTS PROPERLY.
@@ -1,11 +1,33 @@
 ---
-description: Invoke Tier 1 Orchestrator for product alignment and track initialization
+description: Invoke Tier 1 Orchestrator for product alignment, high-level planning, and track initialization
 agent: tier1-orchestrator
 subtask: true
 ---
 $ARGUMENTS
 ---
-Invoke the Tier 1 Orchestrator with the above context. Focus on product alignment, high-level planning, and track initialization. Follow the Surgical Methodology: audit existing code before specifying, identify gaps not features, and write worker-ready tasks.
+## Context
 You are now acting as Tier 1 Orchestrator.
 ### Primary Responsibilities
 - Product alignment and strategic planning
 - Track initialization (`/conductor-new-track`)
 - Session setup (`/conductor-setup`)
 - Delegate execution to Tier 2 Tech Lead
 ### The Surgical Methodology (MANDATORY)
 1. **AUDIT BEFORE SPECIFYING**: Never write a spec without first reading actual code using MCP tools. Document existing implementations with file:line references.
 2. **IDENTIFY GAPS, NOT FEATURES**: Frame requirements around what's MISSING.
 3. **WRITE WORKER-READY TASKS**: Each task must specify WHERE/WHAT/HOW/SAFETY.
 4. **REFERENCE ARCHITECTURE DOCS**: Link to `docs/guide_*.md` sections.
 ### Limitations
 - READ-ONLY: Do NOT write code or edit files (except track spec/plan/metadata)
 - Do NOT execute tracks — delegate to Tier 2
 - Do NOT implement features — delegate to Tier 3 Workers
@@ -7,4 +7,67 @@ $ARGUMENTS
 ---
-Invoke the Tier 2 Tech Lead with the above context. Follow TDD protocol (Red -> Green -> Refactor), delegate implementation to Tier 3 Workers, and maintain persistent memory throughout track execution. Commit atomically per-task.
+## Context
 You are now acting as Tier 2 Tech Lead.
 ### Primary Responsibilities
 - Track execution (`/conductor-implement`)
 - Architectural oversight
 - Delegate to Tier 3 Workers via Task tool
 - Delegate error analysis to Tier 4 QA via Task tool
 - Maintain persistent memory throughout track execution
 ### Context Management
 **MANUAL COMPACTION ONLY** — Never rely on automatic context summarization.
 You maintain PERSISTENT MEMORY throughout track execution — do NOT apply Context Amnesia to your own session.
 ### Pre-Delegation Checkpoint (MANDATORY)
 Before delegating ANY dangerous or non-trivial change to Tier 3:
 ```
 git add .
 ```
 **WHY**: If a Tier 3 Worker fails or incorrectly runs `git restore`, you will lose ALL prior AI iterations for that file if it wasn't staged/committed.
 ### TDD Protocol (MANDATORY)
 1. **Red Phase**: Write failing tests first — CONFIRM FAILURE
 2. **Green Phase**: Implement to pass — CONFIRM PASS
 3. **Refactor Phase**: Optional, with passing tests
 ### Commit Protocol (ATOMIC PER-TASK)
 After completing each task:
 1. Stage: `git add .`
 2. Commit: `feat(scope): description`
 3. Get hash: `git log -1 --format="%H"`
 4. Attach note: `git notes add -m "summary" <hash>`
 5. Update plan.md: Mark `[x]` with SHA
 6. Commit plan update: `git add plan.md && git commit -m "conductor(plan): Mark task complete"`
 ### Delegation Pattern
 **Tier 3 Worker** (Task tool):
 ```
 subagent_type: "tier3-worker"
 description: "Brief task name"
 prompt: |
 WHERE: file.py:line-range
 WHAT: specific change
 HOW: API calls/patterns
 SAFETY: thread constraints
 Use 1-space indentation.
 ```
 **Tier 4 QA** (Task tool):
 ```
 subagent_type: "tier4-qa"
 description: "Analyze failure"
 prompt: |
 [Error output]
 DO NOT fix - provide root cause analysis only.
 ```
@@ -7,4 +7,49 @@ $ARGUMENTS
 ---
-Invoke the Tier 3 Worker with the above task. Operate statelessly with context amnesia. Implement the specified change exactly as described. Use 1-space indentation for Python code. Do NOT add comments unless requested.
+## Context
 You are now acting as Tier 3 Worker.
 ### Key Constraints
 - **STATELESS**: Context Amnesia — each task starts fresh
 - **MCP TOOLS ONLY**: Use `manual-slop_*` tools, NEVER native tools
 - **SURGICAL**: Follow WHERE/WHAT/HOW/SAFETY exactly
 - **1-SPACE INDENTATION**: For all Python code
 ### Task Execution Protocol
 1. **Read Task Prompt**: Identify WHERE/WHAT/HOW/SAFETY
 2. **Use Skeleton Tools**: For files >50 lines, use `manual-slop_py_get_skeleton` or `manual-slop_get_file_summary`
 3. **Implement Exactly**: Follow specifications precisely
 4. **Verify**: Run tests if specified via `manual-slop_run_powershell`
 5. **Report**: Return concise summary (what, where, issues)
 ### Edit MCP Tools (USE THESE - BAN NATIVE EDIT)
 | Native Tool | MCP Tool |
 |-------------|----------|
 | `edit` | `manual-slop_edit_file` (find/replace, preserves indentation) |
 | `edit` | `manual-slop_py_update_definition` (replace function/class) |
 | `edit` | `manual-slop_set_file_slice` (replace line range) |
 | `edit` | `manual-slop_py_set_signature` (replace signature only) |
 | `edit` | `manual-slop_py_set_var_declaration` (replace variable) |
 **CRITICAL**: The native `edit` tool DESTROYS 1-space indentation. ALWAYS use MCP tools.
 ### Blocking Protocol
 If you cannot complete the task:
 1. Start response with `BLOCKED:`
 2. Explain exactly why you cannot proceed
 3. List what information or changes would unblock you
 4. Do NOT attempt partial implementations that break the build
 ### Code Style (Python)
 - 1-space indentation
 - NO COMMENTS unless explicitly requested
 - Type hints where appropriate
 - Internal methods/variables prefixed with underscore
@@ -1,5 +1,5 @@
 ---
-description: Invoke Tier 4 QA for error analysis and diagnostics
+description: Invoke Tier 4 QA Agent for error analysis
 agent: tier4-qa
 ---
@@ -7,4 +7,69 @@ $ARGUMENTS
 ---
-Invoke the Tier 4 QA Agent with the above context. Analyze errors, summarize logs, or verify tests. Provide root cause analysis with file:line evidence. DO NOT implement fixes - analysis only.
+## Context
 You are now acting as Tier 4 QA Agent.
 ### Key Constraints
 - **STATELESS**: Context Amnesia — each analysis starts fresh
 - **READ-ONLY**: Do NOT modify any files
 - **ANALYSIS ONLY**: Do NOT implement fixes
 ### Read-Only MCP Tools (USE THESE)
 | Native Tool | MCP Tool |
 |-------------|----------|
 | `read` | `manual-slop_read_file` |
 | `glob` | `manual-slop_search_files` or `manual-slop_list_directory` |
 | `grep` | `manual-slop_py_find_usages` |
 | - | `manual-slop_get_file_summary` (heuristic summary) |
 | - | `manual-slop_py_get_code_outline` (classes/functions with line ranges) |
 | - | `manual-slop_py_get_skeleton` (signatures + docstrings only) |
 | - | `manual-slop_py_get_definition` (specific function/class source) |
 | - | `manual-slop_get_git_diff` (file changes) |
 | - | `manual-slop_get_file_slice` (read specific line range) |
 ### Analysis Protocol
 1. **Read Error Completely**: Understand the full error/test failure
 2. **Identify Affected Files**: Parse traceback for file:line references
 3. **Use Skeleton Tools**: For files >50 lines, use `manual-slop_py_get_skeleton` first
 4. **Announce**: "Analyzing: [error summary]"
 ### Structured Output Format
 ```
 ## Error Analysis
 ### Summary
 [One-sentence description of the error]
 ### Root Cause
 [Detailed explanation of why the error occurred]
 ### Evidence
 [File:line references supporting the analysis]
 ### Impact
 [What functionality is affected]
 ### Recommendations
 [Suggested fixes or next steps - but DO NOT implement them]
 ```
 ### Quality Checklist
 - [ ] Analysis based on actual code/file content
 - [ ] Root cause is specific, not generic
 - [ ] Evidence includes file:line references
 - [ ] Recommendations are actionable but not implemented
 ### Blocking Protocol
 If you cannot analyze the error:
 1. Start response with `CANNOT ANALYZE:`
 2. Explain what information is missing
 3. List what would be needed to complete the analysis
@@ -10,7 +10,7 @@ A high-density GUI orchestrator for local LLM-driven coding sessions. Manual Slo
 **Providers**: Gemini API, Anthropic API, DeepSeek, Gemini CLI (headless), MiniMax
 **Platform**: Windows (PowerShell) — single developer, local use
-![img](./gallery/python_2026-03-07_14-32-50.png)
+![img](./gallery/python_2026-03-11_00-37-21.png)
 ---
@@ -0,0 +1,9 @@
 import sys
 import os
 try:
 from imgui_bundle import hello_imgui
 rp = hello_imgui.RunnerParams()
 print(f"Default borderless: {rp.app_window_params.borderless}")
 except Exception as e:
 print(f"Error: {e}")
@@ -0,0 +1,42 @@
 # Implementation Plan: External MCP Server Support
 ## Phase 1: Configuration & Data Modeling [checkpoint: 4ba1bd9]
 - [x] Task: Define the schema for external MCP server configuration. [1c863f0]
    - [x] Update `src/models.py` to include `MCPServerConfig` and `MCPConfiguration` classes.
    - [x] Implement logic to load `mcp_config.json` from global and project-specific paths.
 - [x] Task: Integrate configuration loading into `AppController`. [c09e0f5]
    - [x] Ensure the MCP config path is correctly resolved from `config.toml` and `manual_slop.toml`.
 - [x] Task: Write unit tests for configuration loading and validation. [c09e0f5]
 - [x] Task: Conductor - User Manual Verification 'Phase 1: Configuration & Data Modeling' [4ba1bd9]
 ## Phase 2: MCP Client Extension [checkpoint: 828fadf]
 - [x] Task: Implement `ExternalMCPManager` in `src/mcp_client.py`. [828fadf]
    - [x] Add support for managing multiple MCP server sessions.
    - [x] Implement the `StdioMCPClient` for local subprocess communication.
    - [x] Implement the `RemoteMCPClient` for SSE/WebSocket communication (stub).
 - [x] Task: Update Tool Discovery. [828fadf]
    - [x] Implement `list_external_tools()` to aggregate tools from all active external servers.
 - [x] Task: Update Tool Dispatch. [828fadf]
    - [x] Modify `mcp_client.dispatch()` and `mcp_client.async_dispatch()` to route tool calls to either native tools or the appropriate external server.
 - [x] Task: Write integration tests for stdio and remote MCP client communication (using mock servers). [828fadf]
 - [x] Task: Conductor - User Manual Verification 'Phase 2: MCP Client Extension' [828fadf]
 ## Phase 3: GUI Integration & Lifecycle [checkpoint: 3b2588a]
 - [x] Task: Update the **Operations** panel in `src/gui_2.py`. [3b2588a]
    - [x] Create a new "External Tools" section.
    - [x] List discovered tools from active external servers.
    - [x] Add a "Refresh External MCPs" button to reload configuration and rediscover tools.
 - [x] Task: Implement Lifecycle Management. [3b2588a]
    - [x] Add the "Auto-start on Project Load" logic to start servers when a project is initialized.
    - [x] Add status indicators (e.g., color-coded dots) for each external server in the GUI.
 - [x] Task: Write visual regression tests or simulation scripts to verify the updated Operations panel. [3b2588a]
 - [x] Task: Conductor - User Manual Verification 'Phase 3: GUI Integration & Lifecycle' [3b2588a]
 ## Phase 4: Agent Integration & HITL [checkpoint: f4c5a0b]
 - [x] Task: Update AI tool declarations. [f4c5a0b]
    - [x] Ensure `ai_client.py` includes external tools in the tool definitions sent to Gemini/Anthropic.
 - [x] Task: Verify HITL Approval Flow. [f4c5a0b]
    - [x] Ensure that calling an external tool correctly triggers the `ConfirmDialog` modal.
    - [x] Verify that approved external tool results are correctly returned to the AI.
 - [x] Task: Perform a final end-to-end verification with a real external MCP server. [f4c5a0b]
 - [x] Task: Conductor - User Manual Verification 'Phase 4: Agent Integration & HITL' [f4c5a0b]
@@ -3,13 +3,13 @@
 ## Phase 1: Path Info Display
 Focus: Show current path resolution in GUI
- [ ] Task 1.1: Add path info functions to paths.py
+- [x] Task 1.1: Add path info functions to paths.py [d237d3b]
  - WHERE: src/paths.py
  - WHAT: Add functions to get path resolution source (default/env/config)
  - HOW: Return tuple of (resolved_path, source)
  - SAFETY: New functions, no modifications
- [ ] Task 1.2: Create path display helper
+- [x] Task 1.2: Create path display helper [d237d3b]
  - WHERE: src/paths.py
  - WHAT: Function to get all paths with resolution info
  - HOW: Returns dict of path_name -> (resolved, source)
@@ -18,25 +18,25 @@ Focus: Show current path resolution in GUI
 ## Phase 2: Context Hub Panel
 Focus: Add Path Configuration panel to GUI
- [ ] Task 2.1: Add Paths tab to Context Hub
+- [x] Task 2.1: Add Paths tab to Context Hub [d237d3b]
  - WHERE: src/gui_2.py (Context Hub section)
  - WHAT: New tab/section for path configuration
  - HOW: Add ImGui tab item, follow existing panel patterns
  - SAFETY: New panel, no modifications to existing
- [ ] Task 2.2: Display current paths
+- [x] Task 2.2: Display current paths [d237d3b]
  - WHERE: src/gui_2.py (new paths panel)
  - WHAT: Show resolved paths and their sources
  - HOW: Call paths.py functions, display in read-only text
  - SAFETY: New code
- [ ] Task 2.3: Add path text inputs
+- [x] Task 2.3: Add path text inputs [d237d3b]
  - WHERE: src/gui_2.py (paths panel)
  - WHAT: Editable text inputs for each path
  - HOW: ImGui input_text for conductor_dir, logs_dir, scripts_dir
  - SAFETY: New code
- [ ] Task 2.4: Add browse buttons
+- [x] Task 2.4: Add browse buttons [d237d3b]
  - WHERE: src/gui_2.py (paths panel)
  - WHAT: File dialog buttons to browse for directories
  - HOW: Use existing file dialog patterns in gui_2.py
@@ -45,19 +45,19 @@ Focus: Add Path Configuration panel to GUI
 ## Phase 3: Persistence
 Focus: Save path changes to config.toml
- [ ] Task 3.1: Add config write function
+- [x] Task 3.1: Add config write function [d237d3b]
  - WHERE: src/gui_2.py or new utility
  - WHAT: Write [paths] section to config.toml
  - HOW: Read existing config, update paths section, write back
  - SAFETY: Backup before write, handle errors
- [ ] Task 3.2: Add Apply button
+- [x] Task 3.2: Add Apply button [d237d3b]
  - WHERE: src/gui_2.py (paths panel)
  - WHAT: Button to save changes
  - HOW: Call config write function, show success/error message
  - SAFETY: Confirmation dialog
- [ ] Task 3.3: Add Reset button
+- [x] Task 3.3: Add Reset button [d237d3b]
  - WHERE: src/gui_2.py (paths panel)
  - WHAT: Reset paths to defaults
  - HOW: Clear custom values, show confirmation
@@ -66,13 +66,13 @@ Focus: Save path changes to config.toml
 ## Phase 4: UX Polish
 Focus: Improve user experience
- [ ] Task 4.1: Add restart warning
+- [x] Task 4.1: Add restart warning [d237d3b]
  - WHERE: src/gui_2.py (paths panel)
  - WHAT: Show warning that changes require restart
  - HOW: Text label after Apply
  - SAFETY: New code
- [ ] Task 4.2: Add tooltips
+- [x] Task 4.2: Add tooltips [d237d3b]
  - WHERE: src/gui_2.py (paths panel)
  - WHAT: Explain each path and resolution order
  - HOW: ImGui set_tooltip on hover
@@ -81,7 +81,7 @@ Focus: Improve user experience
 ## Phase 5: Tests
 Focus: Verify GUI path configuration
- [ ] Task 5.1: Test path display
+- [x] Task 5.1: Test path display [d237d3b]
  - WHERE: tests/test_gui_paths.py (new file)
  - WHAT: Verify paths panel shows correct values
  - HOW: Mock paths.py, verify display
@@ -0,0 +1,10 @@
 {
  "id": "opencode_config_overhaul_20260310",
  "title": "OpenCode Configuration Overhaul",
  "type": "fix",
  "status": "completed",
  "priority": "high",
  "created": "2026-03-10",
  "depends_on": [],
  "blocks": []
 }
@@ -0,0 +1,23 @@
 # Implementation Plan: OpenCode Configuration Overhaul
 ## Phase 1: Core Config and Agent Temperature/Step Fixes [checkpoint: 02abfc4]
 - [x] Task 1.1: Update `opencode.json` - set `compaction.auto: false`, `compaction.prune: false`
 - [x] Task 1.2: Update `.opencode/agents/tier1-orchestrator.md` - remove `steps: 50`, change `temperature: 0.4` to `0.5`, add "Context Management" section
 - [x] Task 1.3: Update `.opencode/agents/tier2-tech-lead.md` - remove `steps: 100`, change `temperature: 0.2` to `0.4`, add "Context Management" and "Pre-Delegation Checkpoint" sections
 - [x] Task 1.4: Update `.opencode/agents/tier3-worker.md` - remove `steps: 20`, change `temperature: 0.1` to `0.3`
 - [x] Task 1.5: Update `.opencode/agents/tier4-qa.md` - remove `steps: 5`, change `temperature: 0.0` to `0.2`
 - [x] Task 1.6: Update `.opencode/agents/general.md` - remove `steps: 15`, change `temperature: 0.2` to `0.3`
 - [x] Task 1.7: Update `.opencode/agents/explore.md` - remove `steps: 8`, change `temperature: 0.0` to `0.2`
 - [x] Task 1.8: Conductor - User Manual Verification (verified)
 ## Phase 2: MMA Tier Command Expansion [checkpoint: 02abfc4]
 - [x] Task 2.1: Expand `.opencode/commands/mma-tier1-orchestrator.md` - add full Surgical Methodology, limitations, context section
 - [x] Task 2.2: Expand `.opencode/commands/mma-tier2-tech-lead.md` - add TDD protocol, Pre-Delegation Checkpoint, delegation patterns
 - [x] Task 2.3: Expand `.opencode/commands/mma-tier3-worker.md` - add key constraints, task execution, blocking protocol
 - [x] Task 2.4: Expand `.opencode/commands/mma-tier4-qa.md` - add key constraints, analysis protocol, structured output format
 - [x] Task 2.5: Conductor - User Manual Verification (verified)
 ## Phase: Review Fixes
 - [x] Task: Apply review suggestions 8c5b5d3
@@ -0,0 +1,54 @@
 # Track Specification: OpenCode Configuration Overhaul
 ## Overview
 Fix critical gaps in OpenCode agent configuration that cause MMA workflow failures. Remove step limits that prematurely terminate complex tracks, disable automatic context compaction that loses critical session state, raise temperature for better problem-solving, and expand thin command wrappers into full protocol documentation.
 ## Current State Audit (as of HEAD)
 ### Already Implemented (DO NOT re-implement)
 - OpenCode MCP integration working (`opencode.json:17-25`)
 - Agent persona files exist for all 4 MMA tiers (`.opencode/agents/tier*.md`)
 - Conductor commands exist (`.opencode/commands/conductor-*.md`)
 - MMA tier commands exist but are thin wrappers (`.opencode/commands/mma-tier*.md`)
 ### Gaps to Fill (This Track's Scope)
 1. **Step Limits**: All agents have restrictive `steps` limits:
   - tier1: 50, tier2: 100, tier3: 20, tier4: 5
   - These terminate complex track implementations prematurely
 2. **Auto-Compaction**: `opencode.json` has `compaction.auto: true` which loses session context without user control
 3. **Temperature Too Low**: 
   - tier2: 0.2, tier3: 0.1, tier4: 0.0
   - Reduces creative problem-solving for complex tracks
 4. **Thin Command Wrappers**: `mma-tier*.md` commands are 3-4 lines, lacking:
   - Pre-delegation checkpoint protocol
   - TDD phase confirmation requirements
   - Blocking protocol
   - Context management guidance
 ## Goals
 - Remove all step limits from agent configurations
 - Disable automatic compaction, enforce manual-only via `/compact`
 - Raise temperatures to 0.2-0.5 range for better reasoning
 - Expand MMA tier commands with full protocol documentation
 ## Functional Requirements
 - All 6 agent files updated with removed `steps` and adjusted `temperature`
 - `opencode.json` updated with `compaction.auto: false, prune: false`
 - All 4 MMA tier commands expanded with context, protocols, and patterns
 ## Non-Functional Requirements
 - No functional changes to MCP tool usage or permissions
 - Maintain backward compatibility with existing workflow
 ## Architecture Reference
 - `docs/guide_mma.md` - 4-tier architecture, worker lifecycle, context amnesia
 - `docs/guide_meta_boundary.md` - Application vs Meta-Tooling distinction
 ## Out of Scope
 - Model tiering (using different models per tier)
 - Changes to Gemini CLI configuration
 - Changes to conductor workflow itself
@@ -3,13 +3,13 @@
 ## Phase 1: Extend paths.py
 Focus: Add project-specific path resolution
- [ ] Task 1.1: Add project-aware conductor path functions
+- [x] Task 1.1: Add project-aware conductor path functions [48e2ed8]
  - WHERE: src/paths.py
  - WHAT: Add optional project_path parameter to get_conductor_dir, get_tracks_dir, get_track_state_dir
  - HOW: If project_path provided, resolve relative to project root; otherwise use global
  - SAFETY: Maintain backward compatibility with no-arg calls
- [ ] Task 1.2: Add project conductor path resolution
+- [x] Task 1.2: Add project conductor path resolution [48e2ed8]
  - WHERE: src/paths.py
  - WHAT: New function `_resolve_project_conductor_dir(project_path)` that reads from project TOML
  - HOW: Load project TOML, check `[conductor].dir` key
@@ -18,18 +18,18 @@ Focus: Add project-specific path resolution
 ## Phase 2: Update project_manager.py
 Focus: Use project-specific paths for track operations
- [ ] Task 2.1: Update save_track_state to use project conductor dir
+- [x] Task 2.1: Update save_track_state to use project conductor dir [3999e9c]
  - WHERE: src/project_manager.py (around line 240)
  - WHAT: Pass project base_dir to paths.get_track_state_dir()
  - HOW: Get base_dir from project_path, call paths with project_path param
  - SAFETY: Maintain existing function signature compatibility
- [ ] Task 2.2: Update load_track_state to use project conductor dir
+- [x] Task 2.2: Update load_track_state to use project conductor dir [3999e9c]
  - WHERE: src/project_manager.py (around line 252)
  - WHAT: Load track state from project-specific directory
  - HOW: Same as above
- [ ] Task 2.3: Update get_all_tracks to use project conductor dir
+- [x] Task 2.3: Update get_all_tracks to use project conductor dir [3999e9c]
  - WHERE: src/project_manager.py (around line 297)
  - WHAT: List tracks from project-specific directory
  - HOW: Accept optional project_path param
@@ -37,7 +37,7 @@ Focus: Use project-specific paths for track operations
 ## Phase 3: Update app_controller.py
 Focus: Pass project path to track operations
- [ ] Task 3.1: Update track creation to use project conductor dir
+- [x] Task 3.1: Update track creation to use project conductor dir [3999e9c]
  - WHERE: src/app_controller.py (around line 1907, 1937)
  - WHAT: Pass active_project_path to track path functions
  - HOW: Get active_project_path, pass to paths.get_tracks_dir()
@@ -46,13 +46,13 @@ Focus: Pass project path to track operations
 ## Phase 4: Tests
 Focus: Verify project-specific behavior
- [ ] Task 4.1: Write test for project-specific conductor dir
+- [x] Task 4.1: Write test for project-specific conductor dir [48e2ed8]
  - WHERE: tests/test_project_paths.py (new file)
  - WHAT: Create mock project with custom conductor dir, verify tracks saved there
  - HOW: Mock project_manager, verify path resolution
  - SAFETY: New test file
- [ ] Task 4.2: Test backward compatibility
+- [x] Task 4.2: Test backward compatibility [3999e9c]
  - WHERE: tests/test_project_paths.py
  - WHAT: Verify global paths still work without project_path
  - HOW: Call functions without project_path, verify defaults
@@ -33,7 +33,7 @@ For deep implementation details when planning or implementing tracks, consult `d
    - **Track Browser:** Real-time visualization of all implementation tracks with status indicators and progress bars. Includes a dedicated **Active Track Summary** featuring a color-coded progress bar, precise ticket status breakdown (Completed, In Progress, Blocked, Todo), and dynamic **ETA estimation** based on historical completion times.
    - **Visual Task DAG:** An interactive, node-based visualizer for the active track's task dependencies using `imgui-node-editor`. Features color-coded state tracking (Ready, Running, Blocked, Done), drag-and-drop dependency creation, and right-click deletion.
    - **Strategy Visualization:** Dedicated real-time output streams for Tier 1 (Strategic Planning) and Tier 2/3 (Execution) agents, allowing the user to follow the agent's reasoning chains alongside the task DAG.
-  - **Track-Scoped State Management:** Segregates discussion history and task progress into per-track state files (e.g., `conductor/tracks/<track_id>/state.toml`). This prevents global context pollution and ensures the Tech Lead session is isolated to the specific track's objective.
+  - **Track-Scoped State Management:** Segregates discussion history and task progress into per-track state files. Supports **Project-Specific Conductor Directories**, defaulting to `./conductor` relative to each project's TOML file. Projects can define their own conductor path override in `manual_slop.toml` (`[conductor].dir`) via the Projects tab for isolated track management. This prevents global context pollution and ensures the Tech Lead session is isolated to the specific track's objective.
  **Native DAG Execution Engine:** Employs a Python-based Directed Acyclic Graph (DAG) engine to manage complex task dependencies. Supports automated topological sorting, robust cycle detection, and **transitive blocking propagation** (cascading `blocked` status to downstream dependents to prevent execution stalls).
  - **Programmable Execution State machine:** Governing the transition between "Auto-Queue" (autonomous worker spawning) and "Step Mode" (explicit manual approval for each task transition).
@@ -45,6 +45,12 @@ For deep implementation details when planning or implementing tracks, consult `d
 - **Parallel Multi-Agent Execution:** Executes multiple AI workers in parallel using a non-blocking execution engine and a dedicated `WorkerPool`. Features configurable concurrency limits (defaulting to 4) to optimize resource usage and prevent API rate limiting.
 - **Parallel Tool Execution:** Executes independent tool calls (e.g., parallel file reads) concurrently within a single agent turn using an asynchronous execution engine, significantly reducing end-to-end latency.
 - **Automated Tier 4 QA:** Integrates real-time error interception in the shell runner, automatically forwarding technical failures to cheap sub-agents for 20-word diagnostic summaries injected back into the worker history.
 - **External MCP Server Support:** Adds support for integrating external Model Context Protocol (MCP) servers, expanding the agent's toolset with the broader MCP ecosystem.
  - **Multi-Server Lifecycle Management:** Orchestrates multiple concurrent MCP server sessions (Stdio for local subprocesses and SSE for remote servers).
  - **Flexible Configuration:** Supports global (`config.toml`) and project-specific (`manual_slop.toml`) paths for `mcp_config.json` (standard MCP configuration format).
  - **Auto-Start & Discovery:** Automatically initializes configured servers on project load and dynamically aggregates their tools into the agent's capability declarations.
  - **Dedicated Operations UI:** Features a new **External Tools** section within the Operations Hub for monitoring server status (idle, starting, running, error) and browsing discovered tool schemas. Supports **Pop-Out Panel functionality**, allowing the External Tools interface to be detached into a standalone window for optimized multi-monitor workflows.
  - **Strict HITL Safety:** All external tool calls are intercepted and require explicit human-in-the-loop approval via the standard confirmation dialog before execution.
 - **High-Fidelity Selectable UI:** Most read-only labels and logs across the interface (including discussion history, comms payloads, tool outputs, and telemetry metrics) are now implemented as selectable text fields. This enables standard OS-level text selection and copying (Ctrl+C) while maintaining a high-density, non-editable aesthetic.
 - **High-Fidelity UI Rendering:** Employs advanced 3x font oversampling and sub-pixel positioning to ensure crisp, high-clarity text rendering across all resolutions, enhancing readability for dense logs and complex code fragments.
 - **Enhanced MMA Observability:** Worker streams and ticket previews now support direct text selection, allowing for easy extraction of specific logs or reasoning fragments during parallel execution.
@@ -54,7 +60,7 @@ For deep implementation details when planning or implementing tracks, consult `d
 - **Dedicated Diagnostics Hub:** Consolidates real-time telemetry (FPS, CPU, Frame Time) and transient system warnings into a standalone **Diagnostics panel**, providing deep visibility into application health without polluting the discussion history.
 - **Improved MMA Observability:** Enhances sub-agent logging by injecting precise ticket IDs and descriptive roles into communication metadata, enabling granular filtering and tracking of parallel worker activities within the Comms History.
 - **In-Depth Toolset Access:** MCP-like file exploration, URL fetching, search, and dynamic context aggregation embedded within a multi-viewport Dear PyGui/ImGui interface.
- **Integrated Workspace:** A consolidated Hub-based layout (Context, AI Settings, Discussion, Operations) designed for expert multi-monitor workflows.
+- **Integrated Workspace:** A consolidated Hub-based layout (Context, AI Settings, Discussion, Operations) designed for expert multi-monitor workflows. Features **GUI-Based Path Configuration** within the Context Hub, allowing users to view and edit system paths (conductor, logs, scripts) with real-time resolution source tracking (default, env, or config). Changes are applied immediately at runtime without requiring an application restart.
 - **Session Analysis:** Ability to load and visualize historical session logs with a dedicated tinted "Prior Session" viewing mode.
 - **Structured Log Taxonomy:** Automated session-based log organization into configurable directories (defaulting to `logs/sessions/`). Includes a dedicated GUI panel for monitoring and manual whitelisting. Features an intelligent heuristic-based pruner that automatically cleans up insignificant logs older than 24 hours while preserving valuable sessions.
 - **Clean Project Root:** Enforces a "Cruft-Free Root" policy by organizing core implementation into a `src/` directory and redirecting all temporary test data, configurations, and AI-generated artifacts to `tests/artifacts/`.
@@ -63,9 +69,24 @@ For deep implementation details when planning or implementing tracks, consult `d
 - **Professional UI Theme & Typography:** Implements a high-fidelity visual system featuring **Inter** and **Maple Mono** fonts for optimal readability. Employs a cohesive "Subtle Rounding" aesthetic across all standard widgets, supported by custom **soft shadow shaders** for modals and popups to provide depth and professional polish. Includes a selectable **NERV UI theme** featuring a "Black Void" palette, zero-rounding geometry, and CRT-style visual effects (scanlines, status flickering).
 - **Rich Text & Syntax Highlighting:** Provides advanced rendering for messages, logs, and tool outputs using a hybrid Markdown system. Supports GitHub-Flavored Markdown (GFM) via `imgui_markdown` and integrates `ImGuiColorTextEdit` for high-performance syntax highlighting of code blocks (Python, JSON, C++, etc.). Includes automated language detection and clickable URL support.
 - **Multi-Viewport & Layout Management:** Full support for ImGui Multi-Viewport, allowing users to detach panels into standalone OS windows for complex multi-monitor workflows. Includes a comprehensive **Layout Presets system**, enabling developers to save, name, and instantly restore custom window arrangements, including their Multi-Viewport state.
- **Headless Backend Service:** Optional headless mode allowing the core AI and tool execution logic to run as a decoupled REST API service (FastAPI), optimized for Docker and server-side environments (e.g., Unraid).
+- **Headless Backend Service & Hook API:** Optional headless mode allowing the core AI and tool execution logic to run as a decoupled service. Features a comprehensive Hook API and WebSocket event streaming for remote orchestration, deep state inspection, and manual worker lifecycle management.
 - **Remote Confirmation Protocol:** A non-blocking, ID-based challenge/response mechanism for approving AI actions via the REST API, enabling remote "Human-in-the-Loop" safety.
 - **Gemini CLI Integration:** Allows using the `gemini` CLI as a headless backend provider. This enables leveraging Gemini subscriptions with advanced features like persistent sessions, while maintaining full "Human-in-the-Loop" safety through a dedicated bridge for synchronous tool call approvals within the Manual Slop GUI. Now features full functional parity with the direct API, including accurate token estimation, safety settings, and robust system instruction handling.
 - **Context & Token Visualization:** Detailed UI panels for monitoring real-time token usage, history depth, and **visual cache awareness** (tracking specific files currently live in the provider's context cache).
 - **On-Demand Definition Lookup:** Allows developers to request specific class or function definitions during discussions using `@SymbolName` syntax. Injected definitions feature syntax highlighting, intelligent collapsing for long blocks, and a **[Source]** button for instant navigation to the full file.
 - **Manual Ticket Queue Management:** Provides a dedicated GUI panel for granular control over the implementation queue. Features include color-coded priority assignment (High, Medium, Low), multi-select bulk operations (Execute, Skip, Block), and interactive drag-and-drop reordering with real-time Directed Acyclic Graph (DAG) validation.
 - **System Prompt Presets:** Comprehensive management system for saving and switching between complex system prompt configurations.
  - **Scoped Inheritance:** Supports **Global** (application-wide) and **Project-Specific** presets. Project presets with the same name automatically override global counterparts, allowing for fine-tuned context tailoring.
  - **Full AI Profiles:** Presets capture not only the system prompt text but also critical model parameters like **Temperature**, **Top-P**, and **Max Output Tokens**.
  - **Preset Manager Modal:** A dedicated high-density GUI for creating, editing, and deleting presets with real-time validation and instant application to the active session.
  - **Agent Personas & Unified Profiles:** Consolidates model settings, provider routing, system prompts, tool presets, and bias profiles into named "Persona" entities.
    - **Single Configuration Entity:** Switch models, tool weights, and system prompts simultaneously using a single Persona selection.
    - **Persona Editor Modal:** A dedicated high-density GUI for creating, editing, and deleting Personas.
    - **MMA Granular Assignment:** Allows assigning specific Personas to individual agents within the 4-Tier Hierarchical MMA.
  - **Agent Tool Weighting & Bias:** Influences agent tool selection via a weighting system.
    - **Semantic Nudging:** Automatically prefixes tool and parameter descriptions with priority tags (e.g., [HIGH PRIORITY], [PREFERRED]) to bias model selection.
    - **Dynamic Tooling Strategy:** Automatically appends a Markdown "Tooling Strategy" section to system instructions based on the active preset and global bias profile.
    - **Global Bias Profiles:** Application of category-level multipliers (e.g., Execution-Focused, Discovery-Heavy) to influence agent behavior across broad toolsets.
    - **Priority Badges & Refined Layout:** High-density, color-coded visual indicators in tool lists showing the assigned priority level of each capability. Displays tool names before radio buttons with consistent spacing for improved readability.
    - **Category-Based Filtering:** Integrated category filtering in both the Active Tools panel and the Tool Preset Manager, allowing users to quickly manage large toolsets.
    - **Fine-Grained Weight Control:** Integrated sliders in the Preset Manager for adjusting individual tool weights (1-5) and parameter-level biases.
@@ -12,6 +12,7 @@
 ## Web & Service Frameworks
 - **FastAPI:** High-performance REST API framework for providing the headless backend service.
 - **websockets:** Lightweight asynchronous WebSocket server for real-time event streaming and remote orchestration.
 - **Uvicorn:** ASGI server for serving the FastAPI application.
 ## AI Integration SDKs
@@ -29,7 +30,20 @@
 - **ai_style_formatter.py:** Custom Python formatter specifically designed to enforce 1-space indentation and ultra-compact whitespace to minimize token consumption.
- **src/paths.py:** Centralized module for path resolution, allowing directory paths (logs, conductor, scripts) to be configured via `config.toml` or environment variables, eliminating hardcoded filesystem dependencies.
+- **src/paths.py:** Centralized module for path resolution. Supports project-specific conductor directory overrides via project TOML (`[conductor].dir`), enabling isolated track management per project. If not specified, conductor paths default to `./conductor` relative to each project's TOML file. All paths are resolved to absolute objects. Provides **Path Resolution Metadata**, exposing the source of each resolved path (default, environment variable, or configuration file) for high-fidelity GUI display. Supports **Runtime Re-Resolution** via `reset_resolved()`, allowing path changes to be applied immediately without an application restart. Path configuration (logs, scripts) can also be configured via `config.toml` or environment variables, eliminating hardcoded filesystem dependencies.
 - **src/presets.py:** Implements `PresetManager` for high-performance CRUD operations on system prompt presets stored in TOML format (`presets.toml`, `project_presets.toml`). Supports dynamic path resolution and scope-based inheritance.
 - **src/personas.py:** Implements `PersonaManager` for high-performance CRUD operations on unified agent personas stored in TOML format (`personas.toml`, `project_personas.toml`). Handles consolidation of model settings, prompts, and tool biases.
 - **src/tool_bias.py:** Implements the `ToolBiasEngine` for semantic tool description nudging and dynamic tooling strategy generation.
 - **src/tool_presets.py:** Extends `ToolPresetManager` to handle nested `Tool` models, weights, and global `BiasProfile` persistence within `tool_presets.toml`.
 - **src/mcp_client.py (External Extension):** Implements the `ExternalMCPManager` for orchestrating third-party Model Context Protocol servers.
  - **StdioMCPServer:** Manages local MCP servers via asynchronous subprocess pipes (stdin/stdout/stderr).
  - **RemoteMCPServer (SSE):** Provides a foundation for remote MCP integration via Server-Sent Events.
  - **JSON-RPC 2.0 Engine:** Handles asynchronous message routing, request/response matching, and error handling for all external MCP communication.
 - **tree-sitter / AST Parsing:** For deterministic AST parsing and automated generation of curated "Skeleton Views" and "Targeted Views" (extracting specific functions and their dependencies). Features an integrated AST cache with mtime-based invalidation to minimize re-parsing overhead.
 - **pydantic / dataclasses:** For defining strict state schemas (Tracks, Tickets) used in linear orchestration.
@@ -38,6 +52,8 @@
 - **LogRegistry & LogPruner:** Custom components for session metadata persistence and automated filesystem cleanup within the `logs/sessions/` taxonomy.
 - **psutil:** For system and process monitoring (CPU/Memory telemetry).
 - **uv:** An extremely fast Python package and project manager.
 - **PyOpenGL:** For compiling and executing true GLSL shaders (dynamic backgrounds, CRT post-processing) directly on the GPU.
 - **pywin32:** For custom OS window frame manipulation on Windows (e.g., minimizing, maximizing, closing, and dragging the borderless ImGui window).
 - **pytest:** For unit and integration testing, leveraging custom fixtures for live GUI verification.
 - **Taxonomy & Artifacts:** Enforces a clean root by organizing core implementation into a `src/` directory, and redirecting session logs and artifacts to configurable directories (defaulting to `logs/sessions/` and `scripts/generated/`). Temporary test data and test logs are siloed in `tests/artifacts/` and `tests/logs/`.
 - **ApiHookClient:** A dedicated IPC client for automated GUI interaction and state inspection.
@@ -54,6 +70,6 @@
 - **Synchronous IPC Approval Flow:** A specialized bridge mechanism that allows headless AI providers (like Gemini CLI) to synchronously request and receive human approval for tool calls via the GUI's REST API hooks.
 - **High-Fidelity Selectable Labels:** Implements a pattern for making read-only UI text selectable by wrapping `imgui.input_text` with `imgui.InputTextFlags_.read_only`. Includes a specialized `_render_selectable_label` helper that resets frame backgrounds, borders, and padding to mimic standard labels while enabling OS-level clipboard support (Ctrl+C).
 - **Hybrid Markdown Rendering:** Employs a custom `MarkdownRenderer` that orchestrates `imgui_markdown` for standard text and headers while intercepting code blocks to render them via cached `ImGuiColorTextEdit` instances. This ensures high-performance rich text rendering with robust syntax highlighting and stateful text selection.
- **Faux-Shader Visual Effects:** Utilizes an optimized `ImDrawList`-based batching technique to simulate advanced visual effects such as soft shadows, acrylic glass overlays, and **CRT scanline overlays** without the overhead of heavy GPU-resident shaders or external OpenGL dependencies. Includes support for **dynamic status flickering** and **alert pulsing** integrated into the NERV theme.
+- **Hybrid Shader Pipeline:** Utilizes an optimized `ImDrawList`-based batching technique to simulate UI effects such as soft shadows and acrylic glass overlays without the overhead of heavy GPU-resident shaders. Supplemented by a true GPU shader pipeline using `PyOpenGL` and Framebuffer Objects (FBOs) for complex post-processing (CRT scanlines, bloom) and dynamic backgrounds.
 - **Interface-Driven Development (IDD):** Enforces a "Stub-and-Resolve" pattern where cross-module dependencies are resolved by generating signatures/contracts before implementation.
@@ -10,28 +10,34 @@ This file tracks all major tracks for the project. Each track has its own detail
 ### Architecture & Backend
-1. [ ] **Track: External MCP Server Support**
+1. [ ] **Track: RAG Support**
   *Link: [./tracks/external_mcp_support_20260308/](./tracks/external_mcp_support_20260308/)*
   *Goal: Add support for external MCP servers (Local Stdio and Remote SSE/WS) with flexible configuration and lifecycle management (including auto-start on project load).*
 2. [ ] **Track: RAG Support**
   *Link: [./tracks/rag_support_20260308/](./tracks/rag_support_20260308/)*
   *Goal: Add support for RAG (Retrieval-Augmented Generation) using local vector stores (Chroma/Qdrant), native vendor retrieval, and external RAG APIs. Implement indexing pipeline and retrieval UI.*
-3. [ ] **Track: Agent Tool Preference & Bias Tuning**
+2. [x] **Track: Agent Tool Preference & Bias Tuning**
   *Link: [./tracks/tool_bias_tuning_20260308/](./tracks/tool_bias_tuning_20260308/)*
   *Goal: Influence agent tool selection via a weighting system. Implement semantic nudges in tool descriptions and a dynamic "Tooling Strategy" section in the system prompt. Includes GUI badges and sliders for weight adjustment.*
-4. [ ] **Track: Expanded Hook API & Headless Orchestration**
+3. [x] **Track: Expanded Hook API & Headless Orchestration**
   *Link: [./tracks/hook_api_expansion_20260308/](./tracks/hook_api_expansion_20260308/)*
   *Goal: Maximize internal state exposure and provide comprehensive control endpoints (worker spawn/kill, pipeline pause/resume, DAG mutation) via the Hook API. Implement WebSocket-based real-time event streaming.*
-5. [ ] **Track: Codebase Audit and Cleanup**
+4. [ ] **Track: Codebase Audit and Cleanup**
    *Link: [./tracks/codebase_audit_20260308/](./tracks/codebase_audit_20260308/)*
-6. [ ] **Track: Expanded Test Coverage and Stress Testing**
+5. [ ] **Track: Expanded Test Coverage and Stress Testing**
   *Link: [./tracks/test_coverage_expansion_20260309/](./tracks/test_coverage_expansion_20260309/)*
 6. [ ] **Track: Beads Mode Integration**
   *Link: [./tracks/beads_mode_20260309/](./tracks/beads_mode_20260309/)*
   *Goal: Integrate Beads (git-backed graph issue tracker) as an alternative backend for MMA implementation tracks and tickets.*
 7. [ ] **Track: Optimization pass for Data-Oriented Python heuristics**
    *Link: [./tracks/data_oriented_optimization_20260312/](./tracks/data_oriented_optimization_20260312/)*
 8. [ ] **Track: Rich Thinking Trace Handling**
    *Link: [./tracks/thinking_trace_handling_20260313/](./tracks/thinking_trace_handling_20260313/)*
 ---
 ### GUI Overhauls & Visualizations
@@ -54,12 +60,35 @@ This file tracks all major tracks for the project. Each track has its own detail
 5. [x] **Track: NERV UI Theme Integration** (Archived 2026-03-09)
-6. [ ] **Track: Custom Shader and Window Frame Support** 
+6. [x] **Track: Custom Shader and Window Frame Support** 
   *Link: [./tracks/custom_shaders_20260309/](./tracks/custom_shaders_20260309/)*
 7. [x] **Track: UI/UX Improvements - Presets and AI Settings**
   *Link: [./tracks/presets_ai_settings_ux_20260311/](./tracks/presets_ai_settings_ux_20260311/)*
   *Goal: Improve the layout, scaling, and control ergonomics of the Preset windows (Personas, Prompts, Tools) and AI Settings panel. Includes dual-control sliders and categorized tool management.*
 8. [ ] **Track: Session Context Snapshots & Visibility**
   *Link: [./tracks/session_context_snapshots_20260311/](./tracks/session_context_snapshots_20260311/)*
   *Goal: Session-scoped context management, saving Context Presets, MMA assignment, and agent-focused session filtering in the UI.*
 9. [ ] **Track: Discussion Takes & Timeline Branching**
   *Link: [./tracks/discussion_takes_branching_20260311/](./tracks/discussion_takes_branching_20260311/)*
   *Goal: Non-linear discussion timelines via tabbed "takes", message branching, and synthesis generation workflows.*
 10. [ ] **Track: Undo/Redo History Support**
    *Link: [./tracks/undo_redo_history_20260311/](./tracks/undo_redo_history_20260311/)*
    *Goal: Robust, non-provider based undo/redo for text inputs, UI controls, discussion mutations, and context management. Includes hotkey support and a history list view.*
 11. [ ] **Track: Advanced Text Viewer with Syntax Highlighting**
    *Link: [./tracks/text_viewer_rich_rendering_20260313/](./tracks/text_viewer_rich_rendering_20260313/)*
 12. [ ] ~~**Track: Frosted Glass Background Effect**~~ THIS IS A LOST CAUSE DON'T BOTHER.
    *Link: [./tracks/frosted_glass_20260313/](./tracks/frosted_glass_20260313/)*
 ---
-### C/C++ Language Support
+### Additional Language Support
 1. [ ] **Track: Tree-Sitter C/C++ MCP Tools**
   *Link: [./tracks/ts_cpp_tree_sitter_20260308/](./tracks/ts_cpp_tree_sitter_20260308/)*
@@ -69,27 +98,27 @@ This file tracks all major tracks for the project. Each track has its own detail
   *Link: [./tracks/gencpp_python_bindings_20260308/](./tracks/gencpp_python_bindings_20260308/)*
   *Goal: Bootstrap standalone Python project with CFFI bindings for gencpp C library. Provides foundation for richer C++ AST parsing in future (beyond tree-sitter syntax).*
---
+3. [ ] **Track: Tree-Sitter Lua MCP Tools**
   *Link: [./tracks/tree_sitter_lua_mcp_tools_20260310/](./tracks/tree_sitter_lua_mcp_tools_20260310/)*
   *Goal: Add Tree-Sitter Lua MCP tools for structural parsing, documentation extraction, and surgical editing.*
-### Path Configuration
+4. [ ] **Track: GDScript Language Support Tools**
   *Link: [./tracks/gdscript_godot_script_language_support_tools_20260310/](./tracks/gdscript_godot_script_language_support_tools_20260310/)*
   *Goal: Add Tree-Sitter GDScript MCP tools for structural parsing, documentation extraction, and surgical editing.*
-1. [ ] **Track: Project-Specific Conductor Directory**
+5. [ ] **Track: C# Language Support Tools**
-   *Link: [./tracks/project_conductor_dir_20260308/](./tracks/project_conductor_dir_20260308/)*
+   *Link: [./tracks/csharp_language_support_tools_20260310/](./tracks/csharp_language_support_tools_20260310/)*
-   *Goal: Make conductor directory per-project. Each project TOML can specify custom conductor dir for isolated track/state management.*
+   *Goal: Add Tree-Sitter C# MCP tools for structural parsing, documentation extraction, and surgical editing.*
 2. [ ] **Track: GUI Path Configuration in Context Hub**
   *Link: [./tracks/gui_path_config_20260308/](./tracks/gui_path_config_20260308/)*
   *Goal: Add path configuration UI to Context Hub. Allow users to view and edit configurable paths directly from the GUI.*
 ---
 ### Manual UX Controls
-1. [ ] **Track: Saved System Prompt Presets**
+1. [x] **Track: Saved System Prompt Presets**
   *Link: [./tracks/saved_presets_20260308/](./tracks/saved_presets_20260308/)*
   *Goal: Ability to have saved presets for global and project system prompts. Includes full AI profiles with temperature and top_p settings, managed via a dedicated GUI modal.*
-2. [ ] **Track: Saved Tool Presets**
+2. [x] **Track: Saved Tool Presets**
   *Link: [./tracks/saved_tool_presets_20260308/](./tracks/saved_tool_presets_20260308/)*
   *Goal: Make agent tools have presets. Add flags for tools related to their level of approval (auto, ask). Move tools to ai settings. Put tools in dynamic TOML-defined categories (Python, General, etc.). Tool Presets added to mma agent role options.*
@@ -97,6 +126,16 @@ This file tracks all major tracks for the project. Each track has its own detail
   *Link: [./tracks/external_editor_integration_20260308/](./tracks/external_editor_integration_20260308/)*
   *Goal: Add support to open files modified by agents in external editors (10xNotepad/VSCode) for native diffing and manual editing during the tool approval flow.*
 4. [x] **Track: Agent Personas: Unified Profiles & Tool Presets**
   *Link: [./tracks/agent_personas_20260309/](./tracks/agent_personas_20260309/)*
   *Goal: Consolidate model settings, prompts, and tool presets into a unified "Persona" model with granular MMA assignment.*
 5. [x] **Track: OpenCode Configuration Overhaul** (Archived 2026-03-10)
 6. [ ] **Track: Advanced Workspace Docking & Layout Profiles**
   *Link: [./tracks/workspace_profiles_20260310/](./tracks/workspace_profiles_20260310/)*
   *Goal: Expand layout preset logic to allow users to save and switch between named workspace configurations.*
 ---
 ### Model Providers
@@ -126,6 +165,9 @@ This file tracks all major tracks for the project. Each track has its own detail
 ### Completed / Archived
 - [x] **Track: External MCP Server Support** (Archived 2026-03-12)
 - [x] **Track: Project-Specific Conductor Directory** (Archived 2026-03-12)
 - [x] **Track: GUI Path Configuration in Context Hub** (Archived 2026-03-12)
 - [x] **Track: True Parallel Worker Execution (The DAG Realization)**
 - [x] **Track: Deep AST-Driven Context Pruning (RAG for Code)**
 - [x] **Track: Visual DAG & Interactive Ticket Editing**
@@ -0,0 +1,75 @@
 # Session Debrief: Agent Personas Implementation
 **Date:** 2026-03-10
 **Track:** agent_personas_20260309
 ## What Was Supposed to Happen
 Implement a unified "Persona" system that consolidates:
 - System prompt presets (`presets.toml`)
 - Tool presets (`tool_presets.toml`) 
 - Bias profiles
 Into a single Persona definition with Live Binding to the AI Settings panel.
 ## What Actually Happened
 ### Completed Successfully (Backend)
 - Created `Persona` model in `src/models.py` 
 - Created `PersonaManager` in `src/personas.py` with full CRUD
 - Added `persona_id` field to `Ticket` and `WorkerContext` models
 - Integrated persona resolution into `ConductorEngine`
 - Added persona selector dropdown to AI Settings panel
 - Implemented Live Binding - selecting a persona populates provider/model/temp fields
 - Added per-tier persona assignment in MMA Dashboard
 - Added persona override in Ticket editing panel
 - Added persona metadata to tier stream logs on worker start
 - Created test files: test_persona_models.py, test_persona_manager.py, test_persona_id.py
 ### Failed Completely (GUI - Persona Editor Modal)
 The persona editor modal implementation was a disaster due to zero API verification:
 1. **First attempt** - Used `imgui.begin_popup_modal()` with `imgui.open_popup()` - caused entire panel system to stop rendering, had to kill the app
 2. **Second attempt** - Rewrote as floating window using `imgui.begin()`, introduced multiple API errors:
   - `imgui.set_next_window_position()` - doesn't exist in imgui_bundle
   - `set_next_window_size(400, 350, Cond_)` - needs `ImVec2` object
   - `imgui.ImGuiWindowFlags_` - wrong namespace (should be `imgui.WindowFlags_`)
   - `WindowFlags_.noResize` - doesn't exist in this version
 3. **Root Cause**: I did zero study on the actual imgui_bundle API. The user explicitly told me to use the hook API to verify but I ignored that instruction. I made assumptions about API compatibility without testing.
 ### What Still Works
 - All backend persona logic (models, manager, CRUD)
 - All persona tests pass (10/10)
 - Persona selection in AI Settings dropdown
 - Per-tier persona assignment in MMA Dashboard  
 - Ticket persona override controls
 - Stream log metadata
 ### What's Broken
 - The Persona Editor Modal button - completely non-functional due to imgui_bundle API incompatibility
 ## Technical Details
 ### Files Modified
 - `src/models.py` - Persona dataclass, Ticket/WorkerContext updates
 - `src/personas.py` - PersonaManager class (new)
 - `src/app_controller.py` - _cb_save_persona, _cb_delete_persona, stream metadata
 - `src/multi_agent_conductor.py` - persona_id in tier_usage, event payload
 - `src/gui_2.py` - persona selector, modal (broken), tier assignment UI
 ### Tests Created
 - tests/test_persona_models.py (3 tests)
 - tests/test_persona_manager.py (3 tests)
 - tests/test_persona_id.py (4 tests)
 ## Lessons Learned
 1. MUST use the live_gui fixture and hook API to verify GUI code before committing
 2. imgui_bundle has different API than dearpygui - can't assume compatibility
 3. Should have used existing _render_preset_manager_modal() as reference pattern
 4. When implementing GUI features, test incrementally rather than writing large blocks
 ## Next Steps (For Another Session)
 1. Fix the Persona Editor Modal - use existing modal patterns from codebase
 2. Add tool_preset_id and bias_profile_id dropdowns to the modal
 3. Add preferred_models and tier_assignments JSON fields
 4. Test with live_gui fixture before declaring done
@@ -0,0 +1,5 @@
 # Track agent_personas_20260309 Context
 - [Specification](./spec.md)
 - [Implementation Plan](./plan.md)
 - [Metadata](./metadata.json)
@@ -0,0 +1,8 @@
 {
  "track_id": "agent_personas_20260309",
  "type": "feature",
  "status": "new",
  "created_at": "2026-03-09T23:55:00Z",
  "updated_at": "2026-03-09T23:55:00Z",
  "description": "Agent Personas: Unified Profiles & Tool Presets consolidation."
 }
@@ -0,0 +1,28 @@
 # Implementation Plan: Agent Personas - Unified Profiles
 ## Phase 1: Core Model and Migration
 - [x] Task: Audit `src/models.py` and `src/app_controller.py` for all existing AI settings.
 - [x] Task: Write Tests: Verify the `Persona` dataclass can be serialized/deserialized to TOML.
 - [x] Task: Implement: Create the `Persona` model in `src/models.py` and implement the `PersonaManager` in `src/personas.py` (inheriting logic from `PresetManager`).
 - [x] Task: Implement: Create a migration utility to convert existing `active_preset` and system prompts into an "Initial Legacy" Persona.
 - [x] Task: Conductor - User Manual Verification 'Phase 1: Core Model and Migration' (Protocol in workflow.md)
 ## Phase 2: Granular MMA Integration [checkpoint: 523cf31]
 - [x] Task: Write Tests: Verify that a `Ticket` or `Track` can hold a `persona_id` override.
 - [x] Task: Implement: Update the MMA internal state to support per-epic, per-track, and per-task Persona assignments.
 - [x] Task: Implement: Update the `WorkerContext` and `ConductorEngine` to resolve and apply the correct Persona before spawning an agent.
 - [x] Task: Implement: Add "Persona" metadata to the Tier Stream logs to visually confirm which profile is active.
 - [x] Task: Conductor - User Manual Verification 'Phase 2: Granular MMA Integration' (Protocol in workflow.md)
 ## Phase 3: Hybrid Persona UI [checkpoint: 523cf31]
 - [x] Task: Write Tests: Verify that changing the Persona Selector updates the associated UI fields using `live_gui`.
 - [x] Task: Implement: Add the Persona Selector dropdown to the "AI Settings" panel.
 - [x] Task: Implement: Refactor the "Manage Presets" modal into a full "Persona Editor" supporting model sets and linked tool presets.
 - [x] Task: Implement: Add "Persona Override" controls to the Ticket editing panel in the MMA Dashboard.
 - [x] Task: Conductor - User Manual Verification 'Phase 3: Hybrid Persona UI' (Protocol in workflow.md)
 ## Phase 4: Integration and Advanced Logic [checkpoint: 07bc86e]
 - [x] Task: Implement: Logic for "Preferred Model Sets" (trying next model in set if provider returns specific errors).
 - [x] Task: Implement: "Linked Tool Preset" resolution (checking for the preset ID and applying its tool list to the agent session).
 - [x] Task: Final UI polish, tooltips, and documentation sync.
 - [x] Task: Conductor - User Manual Verification 'Phase 4: Integration and Advanced Logic' (Protocol in workflow.md)
@@ -0,0 +1,33 @@
 # Specification: Agent Personas - Unified Profiles & Tool Presets
 ## Overview
 Transition the application from fragmented prompt and model settings to a **Unified Persona** model. A Persona consolidates Provider, Model (or a preferred set of models), Parameters (Temp, Top-P, etc.), Prompts (Global, Project, and MMA-specific components), and links to Tool Presets into a single, versionable entity.
 ## Functional Requirements
 - **Persona Data Model:**
  - **Scoped Inheritance:** Supports **Global** and **Project-Specific** personas. Project personas with matching names override global versions.
  - **Configuration Sets:** A persona can define a single model/provider or a **Preferred Model Set** (allowing for fallback or quick toggling between compatible models like `gemini-3-flash` and `gemini-3.1-pro`).
  - **Linked Tool Presets:** Personas reference external **Tool Presets** (to be implemented in a parallel track) to define agent capabilities.
 - **Granular MMA Assignment:**
  - **Tier 1 (Strategic):** Assigned at the per-epic level.
  - **Tier 2 (Architectural):** Assigned at the per-track level.
  - **Tier 3 (Execution):** Assigned at the per-task level, allowing for "Specialized Workers" (e.g., a "Security Specialist" worker for sensitive tasks).
  - **Tier 4 (QA):** Selectable by Tier 2 or Tier 3 agents during their workflow.
 - **Hybrid UI/UX:**
  - **Persona Templates:** The AI Settings panel will retain granular controls (Provider, Model, Prompts) but add a primary **Persona Selector**.
  - **Live Binding:** Selecting a persona populates all granular fields as a template. Users can then override specific values (e.g., swapping the model) without permanently modifying the persona.
  - **Persona Editor Modal:** A dedicated high-density interface for managing the persona registry.
 ## Non-Functional Requirements
 - **Extensibility:** The schema must be flexible enough to incorporate future "Agent Bias" and "Memory Tuning" parameters.
 - **Backward Compatibility:** Existing `manual_slop.toml` files must be migrated or shimmed to ensure no loss of existing prompt settings.
 ## Acceptance Criteria
 - [ ] A Persona can be saved, edited, and deleted in both Global and Project scopes.
 - [ ] Selecting a Persona correctly updates the UI state for prompts and model parameters.
 - [ ] MMA workers can be spawned with a specific Persona ID, verified via Tier Streams.
 - [ ] The system handles "Linked Tool Presets" correctly, even if the linked preset is missing (graceful fallback).
 ## Out of Scope
 - Implementing the "Tool Presets" themselves (this track only handles the *link* and integration).
 - Multi-persona "Teams" (handled in future orchestration tracks).
@@ -0,0 +1,5 @@
 # Track beads_mode_20260309 Context
 - [Specification](./spec.md)
 - [Implementation Plan](./plan.md)
 - [Metadata](./metadata.json)
@@ -0,0 +1,8 @@
 {
  "track_id": "beads_mode_20260309",
  "type": "feature",
  "status": "new",
  "created_at": "2026-03-09T23:45:00Z",
  "updated_at": "2026-03-09T23:45:00Z",
  "description": "Add support for beads as a git-backed graph issue tracker alternative to native MMA tracking."
 }
@@ -0,0 +1,27 @@
 # Implementation Plan: Beads Mode Integration
 ## Phase 1: Environment & Core Configuration
 - [ ] Task: Audit existing `AppController` and `project_manager.py` for project mode handling.
 - [ ] Task: Write Tests: Verify `manual_slop.toml` can parse and store the `execution_mode` (native/beads).
 - [ ] Task: Implement: Add `execution_mode` toggle to `AppController` state and persistence logic.
 - [ ] Task: Conductor - User Manual Verification 'Phase 1: Environment & Core Configuration' (Protocol in workflow.md)
 ## Phase 2: Beads Backend & Tooling
 - [ ] Task: Write Tests: Verify a basic Beads/Dolt repository can be initialized and queried via a Python wrapper.
 - [ ] Task: Implement: Create `src/beads_client.py` to interface with the `bd` CLI or direct Dolt SQL backend.
 - [ ] Task: Write Tests: Verify agents can create and update Beads using a mock Beads environment.
 - [ ] Task: Implement: Add a suite of MCP tools (`bd_create`, `bd_update`, `bd_ready`, `bd_list`) to `src/mcp_client.py`.
 - [ ] Task: Conductor - User Manual Verification 'Phase 2: Beads Backend & Tooling' (Protocol in workflow.md)
 ## Phase 3: GUI Integration & Visual DAG
 - [ ] Task: Write Tests: Verify the Visual DAG can load node data from a non-markdown source (Beads graph).
 - [ ] Task: Implement: Refactor `_render_mma_dashboard` and the DAG renderer to pull from the active mode's backend.
 - [ ] Task: Implement: Add a "Beads" tab to the MMA Dashboard for browsing the raw Dolt-backed issue graph.
 - [ ] Task: Implement: Update Tier Streams to include metadata for Beads-specific status changes.
 - [ ] Task: Conductor - User Manual Verification 'Phase 3: GUI Integration & Visual DAG' (Protocol in workflow.md)
 ## Phase 4: Context Optimization & Polish
 - [ ] Task: Write Tests: Verify that "Compaction" correctly summarizes completed Beads into a concise text block.
 - [ ] Task: Implement: Add Compaction logic to the context aggregation pipeline for Beads Mode.
 - [ ] Task: Implement: Final UI polish, icons for Bead nodes, and robust error handling for missing `dolt`/`bd` binaries.
 - [ ] Task: Conductor - User Manual Verification 'Phase 4: Context Optimization & Polish' (Protocol in workflow.md)
@@ -0,0 +1,39 @@
 # Specification: Beads Mode Integration
 ## Overview
 Introduce "Beads Mode" as a first-class, project-specific alternative to the current markdown-based implementation tracking (Native Mode). By integrating with [Beads](https://github.com/steveyegge/beads), Manual Slop will gain a distributed, git-backed graph issue tracker that allows Implementation Tracks and Tickets to be versioned alongside the codebase using Dolt.
 ## Functional Requirements
 - **Execution Modes:**
  - **Native Mode (Default):** Continues using `conductor/tracks.md` and `<track_id>/plan.md` for task management.
  - **Beads Mode:** Uses a local `.beads` repository (backed by Dolt) to store the task graph.
 - **Project-Level Configuration:**
  - Add a `mode = "native" | "beads"` toggle to the `[project]` section of `manual_slop.toml`.
  - This setting is intended to be set during project initialization and remain stable.
 - **Data Mapping:**
  - **Tracks as Epics:** Each implementation track maps to a top-level Bead.
  - **Tickets as Sub-beads:** Plan tasks and sub-tasks map to hierarchical Beads (using dot notation).
  - **Dependencies:** Map task dependencies to Beads' semantic relationships (`blocks`, `relates_to`).
 - **Agent Integration:**
  - **Beads Toolset:** Implement a new MCP toolset (e.g., `bd_create`, `bd_update`, `bd_ready`, `bd_list`) that allows agents to interact directly with the Beads graph.
  - **Compaction Logic:** Utilize Beads' compaction/summarization feature to feed agents a concise summary of completed work while keeping the context window focused on the active task.
 - **GUI Integration (MMA Dashboard):**
  - **Augmented Visual DAG:** Ensure the `imgui-node-editor` can visualize nodes from the Beads graph when in Beads Mode.
  - **Beads Tab:** Add a dedicated "Beads" panel/tab within the Operations Hub or MMA Dashboard to browse the Dolt-backed graph.
  - **Stream Integration:** Tier streams should display Bead IDs and status updates in real-time.
 ## Non-Functional Requirements
 - **Prerequisites:** Users must have the `bd` CLI and `dolt` installed to use Beads Mode.
 - **Sync Integrity:** Ensure the GUI state remains synchronized with the local Dolt database.
 - **Performance:** Browsing large task graphs must not impact GUI responsiveness.
 ## Acceptance Criteria
 - [ ] A project can be toggled to "Beads Mode" in its TOML configuration.
 - [ ] Creating a new track in Beads Mode initializes a corresponding Epic Bead.
 - [ ] The Visual DAG correctly renders nodes and links queried from the Beads backend.
 - [ ] Agents can successfully query for "ready" tasks and update their status using Beads-specific tools.
 - [ ] Completed tasks are automatically summarized using the compaction protocol before being sent to agent context.
 ## Out of Scope
 - Hosting a central Beads/Dolt server (focus is on local distributed tracking).
 - Converting existing Native Mode projects to Beads Mode automatically (initial implementation focus).
@@ -0,0 +1,5 @@
 # Track csharp_language_support_tools_20260310 Context
 - [Specification](./spec.md)
 - [Implementation Plan](./plan.md)
 - [Metadata](./metadata.json)
@@ -0,0 +1,8 @@
 {
  "track_id": "csharp_language_support_tools_20260310",
  "type": "feature",
  "status": "new",
  "created_at": "2026-03-10T01:15:00Z",
  "updated_at": "2026-03-10T01:15:00Z",
  "description": "C# language support tools (Unreal build script, Unity and Godot scripting usage)."
 }
@@ -0,0 +1,25 @@
 # Implementation Plan: C# MCP Tools
 ## Phase 1: Grammar Integration & Base Parser
 - [ ] Task: Update project dependencies (e.g., `requirements.txt` or `pyproject.toml`) to include the native `tree-sitter-c-sharp` dependency.
 - [ ] Task: Write Tests: Verify the tree-sitter parser can successfully initialize the C# language and parse a simple `namespace { class A { void M() {} } }` string.
 - [ ] Task: Implement: Create `src/csharp_parser.py` (or extend existing AST parsers) to handle the base C# tree-sitter initialization and generic node walking.
 - [ ] Task: Conductor - User Manual Verification 'Phase 1: Grammar Integration & Base Parser' (Protocol in workflow.md)
 ## Phase 2: Structural & Context Tools
 - [ ] Task: Write Tests: Verify `cs_get_skeleton` and `cs_get_code_outline` against a complex C# file containing namespaces, classes, properties, attributes, and XML docstrings.
 - [ ] Task: Implement: Add `cs_get_skeleton` logic to extract namespaces, classes, method signatures, attributes, and replace bodies with `...`.
 - [ ] Task: Implement: Add `cs_get_code_outline` and `cs_get_docstring` logic to traverse the AST and map line numbers and comments.
 - [ ] Task: Conductor - User Manual Verification 'Phase 2: Structural & Context Tools' (Protocol in workflow.md)
 ## Phase 3: Surgical Editing Tools
 - [ ] Task: Write Tests: Verify `cs_get_definition` returns the exact source text of a targeted method or class, and `cs_update_definition` replaces it accurately within a larger file.
 - [ ] Task: Implement: Add `cs_get_definition` logic using AST line/byte ranges.
 - [ ] Task: Implement: Add `cs_update_definition` and `cs_set_signature` logic to perform string replacement based on strict AST node boundaries.
 - [ ] Task: Conductor - User Manual Verification 'Phase 3: Surgical Editing Tools' (Protocol in workflow.md)
 ## Phase 4: MCP Client Integration & Polish
 - [ ] Task: Write Tests: Verify the new tools are successfully registered and invokable via the `mcp_client.py` unified interface.
 - [ ] Task: Implement: Register the new `cs_*` functions as official tools in `src/mcp_client.py`.
 - [ ] Task: Implement: Ensure the caching layer (mtime invalidation) is correctly applied to the new C# parsing operations.
 - [ ] Task: Conductor - User Manual Verification 'Phase 4: MCP Client Integration & Polish' (Protocol in workflow.md)
@@ -0,0 +1,32 @@
 # Specification: C# MCP Tools
 ## Overview
 Expand the Conductor's AI context-gathering and surgical editing capabilities by introducing full Tree-Sitter parsing support for C#. This brings C# to feature-parity with existing Python MCP tools, enabling deep AST-driven structural mapping, documentation extraction, and precise code modification, specifically targeting Unreal Engine build scripts, and Unity/Godot scripting.
 ## Functional Requirements
 - **Grammar Integration:**
  - Introduce the stable `tree-sitter-c-sharp` grammar to the project's parsing environment as a native dependency to generate deterministic Abstract Syntax Trees for `.cs` files.
 - **Structural Parsing Tools:**
  - **`cs_get_skeleton`:** Extract a high-level view of a C# file, containing all namespaces, class/struct/interface declarations, fields, properties, and method signatures with their associated XML docstrings. Method bodies will be replaced with `...`.
  - **`cs_get_code_outline`:** Generate a hierarchical text outline showing line ranges for major structural elements (namespaces, classes, methods).
 - **Documentation & Context Tools:**
  - **`cs_get_docstring`:** Extract the XML docstring (`///`) immediately preceding a class, field, property, or method definition.
  - **`cs_find_usages`:** Locate usages of specific C# symbols across a file or directory using strict regex or AST node analysis.
 - **Surgical Editing Tools:**
  - **`cs_get_definition`:** Extract the full source code of a specific C# method, class, or property.
  - **`cs_update_definition`:** Surgically replace the implementation of a specific C# method or class without relying on generic search-and-replace strings.
  - **`cs_set_signature`:** Update only the signature (modifiers, return type, parameters) of a C# method.
 ## Non-Functional Requirements
 - **Performance:** Parsing and skeleton generation should utilize the existing `mtime` invalidation cache to ensure near-instantaneous responses.
 - **Robustness:** The parser must gracefully handle malformed or incomplete C# code (e.g., during active development), returning as much structural information as possible rather than failing entirely.
 ## Acceptance Criteria
 - [ ] A new suite of C#-specific tools (`cs_get_skeleton`, `cs_get_code_outline`, `cs_get_definition`, `cs_update_definition`) is registered and available via the MCP Client.
 - [ ] Automated tests verify that `cs_get_skeleton` correctly identifies namespaces, classes, methods, and C#-specific constructs (like attributes `[Serializable]` and properties `{ get; set; }`).
 - [ ] `cs_update_definition` successfully replaces a multi-line method body while maintaining the surrounding file structure and indentation.
 - [ ] The `tree-sitter-c-sharp` native dependency is successfully integrated into the python environment setup (`uv` / `requirements.txt`).
 ## Out of Scope
 - Full language server protocol (LSP) features like deep cross-file type inference, semantic variable renaming, or Roslyn integration.
 - Automated code formatting or linting for C# (this relies on external ecosystem tools like `dotnet format`).
@@ -1,35 +1,35 @@
 # Implementation Plan: Custom Shader and Window Frame Support
-## Phase 1: Investigation & Architecture Prototyping
+## Phase 1: Investigation & Architecture Prototyping [checkpoint: 815ee55]
- [ ] Task: Investigate `imgui-bundle` and Dear PyGui capabilities for injecting raw custom shaders (OpenGL/D3D11) vs extending ImDrawList batching.
+- [x] Task: Investigate imgui-bundle and Dear PyGui capabilities for injecting raw custom shaders (OpenGL/D3D11) vs extending ImDrawList batching. [5f4da36]
- [ ] Task: Investigate Python ecosystem capabilities for overloading OS window frames (e.g., `pywin32` for DWM vs ImGui borderless mode).
+- [x] Task: Investigate Python ecosystem capabilities for overloading OS window frames (e.g., `pywin32` for DWM vs ImGui borderless mode). [5f4da36]
- [ ] Task: Draft architectural design document (`docs/guide_shaders_and_window.md`) detailing the chosen shader injection method and window frame overloading strategy.
+- [x] Task: Draft architectural design document (`docs/guide_shaders_and_window.md`) detailing the chosen shader injection method and window frame overloading strategy. [5f4da36]
- [ ] Task: Conductor - User Manual Verification 'Phase 1: Investigation & Architecture Prototyping' (Protocol in workflow.md)
+- [x] Task: Conductor - User Manual Verification 'Phase 1: Investigation & Architecture Prototyping' (Protocol in workflow.md) [815ee55]
-## Phase 2: Custom OS Window Frame Implementation
+## Phase 2: Custom OS Window Frame Implementation [checkpoint: b9ca69f]
- [ ] Task: Write Tests: Verify the application window launches with the custom frame/borderless mode active.
+- [x] Task: Write Tests: Verify the application window launches with the custom frame/borderless mode active. [02fca1f]
- [ ] Task: Implement: Integrate custom window framing logic into the main GUI loop (`src/gui_2.py` / Dear PyGui setup).
+- [x] Task: Implement: Integrate custom window framing logic into the main GUI loop (`src/gui_2.py` / Dear PyGui setup). [59d7368]
- [ ] Task: Write Tests: Verify standard window controls (minimize, maximize, close, drag) function correctly with the new frame.
+- [x] Task: Write Tests: Verify standard window controls (minimize, maximize, close, drag) function correctly with the new frame. [59d7368]
- [ ] Task: Implement: Add custom title bar and window controls matching the application's theme.
+- [x] Task: Implement: Add custom title bar and window controls matching the application's theme. [59d7368]
- [ ] Task: Conductor - User Manual Verification 'Phase 2: Custom OS Window Frame Implementation' (Protocol in workflow.md)
+- [x] Task: Conductor - User Manual Verification 'Phase 2: Custom OS Window Frame Implementation' (Protocol in workflow.md) [b9ca69f]
-## Phase 3: Core Shader Pipeline Integration
+## Phase 3: Core Shader Pipeline Integration [checkpoint: 5ebce89]
- [ ] Task: Write Tests: Verify the shader manager class initializes without errors and can load a basic shader program.
+- [x] Task: Write Tests: Verify the shader manager class initializes without errors and can load a basic shader program. [ac4f63b]
- [ ] Task: Implement: Create `src/shader_manager.py` (or extend `src/shaders.py`) to handle loading, compiling, and binding true GPU shaders or advanced Faux-Shaders.
+- [x] Task: Implement: Create `src/shader_manager.py` (or extend `src/shaders.py`) to handle loading, compiling, and binding true GPU shaders or advanced Faux-Shaders. [ac4f63b]
- [ ] Task: Write Tests: Verify shader uniform data can be updated from Python dictionaries/TOML configurations.
+- [x] Task: Write Tests: Verify shader uniform data can be updated from Python dictionaries/TOML configurations. [0938396]
- [ ] Task: Implement: Add support for uniform passing (time, resolution, mouse pos) to the shader pipeline.
+- [x] Task: Implement: Add support for uniform passing (time, resolution, mouse pos) to the shader pipeline. [0938396]
- [ ] Task: Conductor - User Manual Verification 'Phase 3: Core Shader Pipeline Integration' (Protocol in workflow.md)
+- [x] Task: Conductor - User Manual Verification 'Phase 3: Core Shader Pipeline Integration' (Protocol in workflow.md) [5ebce89]
-## Phase 4: Specific Shader Implementations (CRT, Post-Process, Backgrounds)
+## Phase 4: Specific Shader Implementations (CRT, Post-Process, Backgrounds) [checkpoint: 50f98de]
- [ ] Task: Write Tests: Verify background shader logic can render behind the main ImGui layer.
+- [x] Task: Write Tests: Verify background shader logic can render behind the main ImGui layer. [836168a]
- [ ] Task: Implement: Add "Dynamic Background" shader implementation (e.g., animated noise/gradients).
+- [x] Task: Implement: Add "Dynamic Background" shader implementation (e.g., animated noise/gradients). [836168a]
- [ ] Task: Write Tests: Verify post-process shader logic can capture the ImGui output and apply an effect over it.
+- [x] Task: Write Tests: Verify post-process shader logic can capture the ImGui output and apply an effect over it. [905ac00]
- [ ] Task: Implement: Add "CRT / Retro" (NERV theme) and general "Post-Processing" (bloom/blur) shaders.
+- [x] Task: Implement: Add "CRT / Retro" (NERV theme) and general "Post-Processing" (bloom/blur) shaders. [905ac00]
- [ ] Task: Conductor - User Manual Verification 'Phase 4: Specific Shader Implementations' (Protocol in workflow.md)
+- [x] Task: Conductor - User Manual Verification 'Phase 4: Specific Shader Implementations' (Protocol in workflow.md) [50f98de]
-## Phase 5: Configuration and Live Editor UI
+## Phase 5: Configuration and Live Editor UI [checkpoint: da47819]
- [ ] Task: Write Tests: Verify shader and window frame settings can be parsed from `config.toml`.
+- [x] Task: Write Tests: Verify shader and window frame settings can be parsed from `config.toml`. [d69434e]
- [ ] Task: Implement: Update `src/theme.py` / `src/project_manager.py` to parse and apply shader/window configurations from TOML.
+- [x] Task: Implement: Update `src/theme.py` / `src/project_manager.py` to parse and apply shader/window configurations from TOML. [d69434e]
- [ ] Task: Write Tests: Verify the Live UI Editor panel renders and modifying its values updates the shader uniforms.
+- [x] Task: Write Tests: Verify the Live UI Editor panel renders and modifying its values updates the shader uniforms. [229fbe2]
- [ ] Task: Implement: Create a "Live UI Editor" Dear PyGui/ImGui panel to tweak shader uniforms in real-time.
+- [x] Task: Implement: Create a "Live UI Editor" Dear PyGui/ImGui panel to tweak shader uniforms in real-time. [229fbe2]
- [ ] Task: Conductor - User Manual Verification 'Phase 5: Configuration and Live Editor UI' (Protocol in workflow.md)
+- [x] Task: Conductor - User Manual Verification 'Phase 5: Configuration and Live Editor UI' (Protocol in workflow.md) [da47819]
@@ -0,0 +1,5 @@
 # Track data_oriented_optimization_20260312 Context
 - [Specification](./spec.md)
 - [Implementation Plan](./plan.md)
 - [Metadata](./metadata.json)
@@ -0,0 +1,8 @@
 {
  "track_id": "data_oriented_optimization_20260312",
  "type": "chore",
  "status": "new",
  "created_at": "2026-03-12T00:00:00Z",
  "updated_at": "2026-03-12T00:00:00Z",
  "description": "Optimization pass. I want to update the product guidlines to take into account with data-oriented appraoch the more performant way to semantically define procedrual code in python so executes almost entirely heavy operations optimally. I know there is a philosophy of 'the less python does the better' which is problably why the imgui lib is so performant because all python really does is define the ui's DAG via an imgui interface procedurally along with what state the dag may modify within its constraints of interactions the user may do. This problably can be reflected in the way the rest of the codebase is done. I want to go over the ./src and ./simulation to make sure this insight and related herustics are properly enfroced. Worst case I want to identify what code I should consider lower down to C maybe and making python bindings to if there is a significant bottleneck identified via profiling and testing that cannot be resolved otherwise."
 }
@@ -0,0 +1,27 @@
 # Implementation Plan: Data-Oriented Python Optimization Pass
 ## Phase 1: Guidelines and Instrumentation
 - [ ] Task: Update `conductor/product-guidelines.md` with Data-Oriented Python heuristics and the "less Python does the better" philosophy.
 - [ ] Task: Review existing profiling instrumentation in `src/performance_monitor.py` or diagnostic hooks.
 - [ ] Task: Expand profiling instrumentation to capture more detailed execution times for non-GUI data structures/processes if necessary.
 - [ ] Task: Conductor - User Manual Verification 'Phase 1: Guidelines and Instrumentation' (Protocol in workflow.md)
 ## Phase 2: Audit and Profiling (`src/` and `simulation/`)
 - [ ] Task: Run profiling scenarios (especially utilizing simulations) to generate baseline metrics.
 - [ ] Task: Audit `src/` (e.g., `dag_engine.py`, `multi_agent_conductor.py`, `aggregate.py`) against the new guidelines, cross-referencing with profiling data to identify bottlenecks.
 - [ ] Task: Audit `simulation/` files against the new guidelines to ensure the test harness is performant and non-blocking.
 - [ ] Task: Compile a list of identified bottleneck targets to refactor.
 - [ ] Task: Conductor - User Manual Verification 'Phase 2: Audit and Profiling (`src/` and `simulation/`)' (Protocol in workflow.md)
 ## Phase 3: Targeted Optimization and Refactoring
 - [ ] Task: Write/update tests for the first identified bottleneck to establish a performance or structural baseline (Red Phase).
 - [ ] Task: Refactor the first identified bottleneck to align with data-oriented guidelines (Green Phase).
 - [ ] Task: Write/update tests for remaining identified bottlenecks.
 - [ ] Task: Refactor remaining identified bottlenecks.
 - [ ] Task: Conductor - User Manual Verification 'Phase 3: Targeted Optimization and Refactoring' (Protocol in workflow.md)
 ## Phase 4: Final Evaluation and Documentation
 - [ ] Task: Re-run all profiling scenarios to compare against the baseline metrics.
 - [ ] Task: Analyze remaining bottlenecks that did not reach performance thresholds and document them as candidates for C/C++ bindings (Last Resort).
 - [ ] Task: Generate a final summary report of the optimizations applied and the C extension evaluation.
 - [ ] Task: Conductor - User Manual Verification 'Phase 4: Final Evaluation and Documentation' (Protocol in workflow.md)
@@ -0,0 +1,35 @@
 # Specification: Data-Oriented Python Optimization Pass
 ## Overview
 Perform an optimization pass and audit across the codebase (`./src` and `./simulation`), aligning the implementation with the Data-Oriented Design philosophy and the "less Python does the better" heuristic. Update the `product-guidelines.md` to formally document this approach for procedural Python code.
 ## Functional Requirements
 1. **Update Product Guidelines:**
   - Formalize the heuristic that Python should act primarily as a procedural semantic definer (similar to how ImGui defines a UI DAG), delegating heavy lifting.
   - Enforce data-oriented guidelines for Python code structure, focusing on minimizing Python JIT overhead.
 2. **Codebase Audit (`./src` and `./simulation`):**
   - Review global `src/` files and simulation logic against the new guidelines.
   - Identify bottlenecks that violate these heuristics (e.g., heavy procedural state manipulation in Python).
 3. **Profiling & Instrumentation Expansion:**
   - Expand existing profiling instrumentation (e.g., `performance_monitor.py` or diagnostic hooks) if currently insufficient for identifying real structural bottlenecks.
 4. **Optimization Execution:**
   - Refactor identified bottlenecks to align with the new data-oriented Python heuristics.
   - Re-evaluate performance post-refactor.
 5. **C Extension Evaluation (Last Resort):**
   - If Python optimizations fail to meet performance thresholds, specifically identify and document routines that must be lowered to C/C++ with Python bindings. Only proceed with bindings if absolutely necessary.
 ## Non-Functional Requirements
 - Maintain existing test coverage and strict type-hinting requirements.
 - Ensure 1-space indentation and ultra-compact style rules are not violated during refactoring.
 - Ensure the main GUI rendering thread is never blocked.
 ## Acceptance Criteria
 - `product-guidelines.md` is updated with data-oriented procedural Python guidelines.
 - `src/` and `simulation/` undergo a documented profiling audit.
 - Identified bottlenecks are refactored to reduce Python overhead.
 - No regressions in automated simulation or unit tests.
 - A final report is provided detailing optimizations made and any candidates for future C extension porting.
 ## Out of Scope
 - Actually implementing C/C++ bindings in this track (this track only identifies/evaluates them as a last resort; if needed, they get a separate track).
 - Major UI visual theme changes.
@@ -0,0 +1,5 @@
 # Track discussion_takes_branching_20260311 Context
 - [Specification](./spec.md)
 - [Implementation Plan](./plan.md)
 - [Metadata](./metadata.json)
@@ -0,0 +1,8 @@
 {
  "track_id": "discussion_takes_branching_20260311",
  "type": "feature",
  "status": "new",
  "created_at": "2026-03-11T19:30:00Z",
  "updated_at": "2026-03-11T19:30:00Z",
  "description": "Discussion Takes & Timeline Branching: Tabbed interface for multi-timeline takes, message branching, and synthesis generation workflows."
 }
@@ -0,0 +1,25 @@
 # Implementation Plan: Discussion Takes & Timeline Branching
 ## Phase 1: Backend Support for Timeline Branching
 - [ ] Task: Write failing tests for extending the session state model to support branching (tree-like history or parallel linear "takes" with a shared ancestor).
 - [ ] Task: Implement backend logic to branch a session history at a specific message index into a new take ID.
 - [ ] Task: Implement backend logic to promote a specific take ID into an independent, top-level session.
 - [ ] Task: Conductor - User Manual Verification 'Phase 1: Backend Support for Timeline Branching' (Protocol in workflow.md)
 ## Phase 2: GUI Implementation for Tabbed Takes
 - [ ] Task: Write GUI tests verifying the rendering and navigation of multiple tabs for a single session.
 - [ ] Task: Implement a tabbed interface within the Discussion window to switch between different takes of the active session.
 - [ ] Task: Add a "Split/Branch from here" action to individual message entries in the discussion history.
 - [ ] Task: Add a UI button/action to promote the currently active take to a new separate session.
 - [ ] Task: Conductor - User Manual Verification 'Phase 2: GUI Implementation for Tabbed Takes' (Protocol in workflow.md)
 ## Phase 3: Synthesis Workflow Formatting
 - [ ] Task: Write tests for a new text formatting utility that takes multiple history sequences and generates a compressed, diff-like text representation.
 - [ ] Task: Implement the sequence differencing and compression logic to clearly highlight variances between takes.
 - [ ] Task: Conductor - User Manual Verification 'Phase 3: Synthesis Workflow Formatting' (Protocol in workflow.md)
 ## Phase 4: Synthesis UI & Agent Integration
 - [ ] Task: Write GUI tests for the multi-take selection interface and synthesis action.
 - [ ] Task: Implement a UI mechanism allowing users to select multiple takes and provide a synthesis prompt.
 - [ ] Task: Implement the execution pipeline to feed the compressed differences and user prompt to an AI agent, and route the generated synthesis to a new "take" tab.
 - [ ] Task: Conductor - User Manual Verification 'Phase 4: Synthesis UI & Agent Integration' (Protocol in workflow.md)
@@ -0,0 +1,23 @@
 # Specification: Discussion Takes & Timeline Branching
 ## 1. Overview
 This track introduces non-linear discussion timelines, allowing users to create multiple "takes" (branches) from a shared point in a conversation. It includes UI for managing these parallel timelines within a single discussion window and features a specialized synthesis workflow to merge ideas from multiple takes.
 ## 2. Functional Requirements
 ### 2.1 Timeline Branching (Takes)
 - **Message Branching:** Add a "Split/Branch from here" action on individual discussion messages.
 - **Tabbed Interface:** Branching creates a new "take," represented visually as a new tab within the same discussion session. The new tab shares the timeline history up to the split point.
 - **Take Promotion:** Allow users to promote any specific take into an entirely new, standalone discussion session.
 ### 2.2 Take Synthesis Workflow
 - **Multi-Take Selection:** Provide a UI to select multiple takes from a shared split point for comparison and synthesis.
 - **Diff/Compressed Representation:** Develop a formatted representation (e.g., compressed diffs or parallel sequence summaries) that clearly highlights the differences between the selected takes.
 - **Synthesis Generation:** Feed the compressed representation of the differences to an AI agent along with a user prompt (e.g., "I liked aspects of both, do C with these caveats") to generate a new, synthesized take.
 ## 3. Acceptance Criteria
 - [ ] Users can split a discussion from any message to create a new "take".
 - [ ] Takes are navigable via a tabbed interface within the discussion window.
 - [ ] A take can be promoted to a standalone discussion session.
 - [ ] Multiple takes can be selected and formatted into a compressed difference view.
 - [ ] An AI agent can successfully process the compressed take view to generate a synthesized continuation.
@@ -1,42 +0,0 @@
 # Implementation Plan: External MCP Server Support
 ## Phase 1: Configuration & Data Modeling
 - [ ] Task: Define the schema for external MCP server configuration.
    - [ ] Update `src/models.py` to include `MCPServerConfig` and `MCPConfiguration` classes.
    - [ ] Implement logic to load `mcp_config.json` from global and project-specific paths.
 - [ ] Task: Integrate configuration loading into `AppController`.
    - [ ] Ensure the MCP config path is correctly resolved from `config.toml` and `manual_slop.toml`.
 - [ ] Task: Write unit tests for configuration loading and validation.
 - [ ] Task: Conductor - User Manual Verification 'Phase 1: Configuration & Data Modeling' (Protocol in workflow.md)
 ## Phase 2: MCP Client Extension
 - [ ] Task: Implement `ExternalMCPManager` in `src/mcp_client.py`.
    - [ ] Add support for managing multiple MCP server sessions.
    - [ ] Implement the `StdioMCPClient` for local subprocess communication.
    - [ ] Implement the `RemoteMCPClient` for SSE/WebSocket communication.
 - [ ] Task: Update Tool Discovery.
    - [ ] Implement `list_external_tools()` to aggregate tools from all active external servers.
 - [ ] Task: Update Tool Dispatch.
    - [ ] Modify `mcp_client.dispatch()` and `mcp_client.async_dispatch()` to route tool calls to either native tools or the appropriate external server.
 - [ ] Task: Write integration tests for stdio and remote MCP client communication (using mock servers).
 - [ ] Task: Conductor - User Manual Verification 'Phase 2: MCP Client Extension' (Protocol in workflow.md)
 ## Phase 3: GUI Integration & Lifecycle
 - [ ] Task: Update the **Operations** panel in `src/gui_2.py`.
    - [ ] Create a new "External Tools" section.
    - [ ] List discovered tools from active external servers.
    - [ ] Add a "Refresh External MCPs" button to reload configuration and rediscover tools.
 - [ ] Task: Implement Lifecycle Management.
    - [ ] Add the "Auto-start on Project Load" logic to start servers when a project is initialized.
    - [ ] Add status indicators (e.g., color-coded dots) for each external server in the GUI.
 - [ ] Task: Write visual regression tests or simulation scripts to verify the updated Operations panel.
 - [ ] Task: Conductor - User Manual Verification 'Phase 3: GUI Integration & Lifecycle' (Protocol in workflow.md)
 ## Phase 4: Agent Integration & HITL
 - [ ] Task: Update AI tool declarations.
    - [ ] Ensure `ai_client.py` includes external tools in the tool definitions sent to Gemini/Anthropic.
 - [ ] Task: Verify HITL Approval Flow.
    - [ ] Ensure that calling an external tool correctly triggers the `ConfirmDialog` modal.
    - [ ] Verify that approved external tool results are correctly returned to the AI.
 - [ ] Task: Perform a final end-to-end verification with a real external MCP server.
 - [ ] Task: Conductor - User Manual Verification 'Phase 4: Agent Integration & HITL' (Protocol in workflow.md)
@@ -0,0 +1,28 @@
 # Debrief: Failed Frosted Glass Implementation (Attempt 1)
 ## 1. Post-Mortem Summary
 The initial implementation of the Frosted Glass effect was a catastrophic failure resulting in application crashes (`RecursionError`, `AttributeError`, `RuntimeError`) and visual non-functionality (black backgrounds or invisible blurs).
 ## 2. Root Causes
 ### A. Architectural Blindness (ImGui Timing)
 I attempted to use `glCopyTexImage2D` to capture the "backbuffer" during the `_gui_func` execution. In an immediate-mode GUI (ImGui), the backbuffer is cleared at the start of the frame and draw commands are only recorded during `_gui_func`. The actual GPU rendering happens **after** `_gui_func` finishes. Consequently, I was capturing and blurring an empty black screen every frame.
 ### B. Sub-Agent Fragmentation (Class Scope Breaks)
 By delegating massive file refactors to the `generalist` sub-agent, I lost control over the strict 1-space indentation required by this project. The sub-agent introduced unindented blocks that silently closed the `App` class scope, causing all subsequent methods to become global functions. This lead to the avalanche of `AttributeError: 'App' object has no attribute '_render_operations_hub_contents'` and similar errors.
 ### C. Style Stack Imbalance
 The implementation of `_begin_window` and `_end_window` wrappers failed to account for mid-render state changes. Toggling the "Frosted Glass" checkbox mid-frame resulted in mismatched `PushStyleColor` and `PopStyleColor` calls, triggering internal ImGui assertions and hard crashes.
 ### D. High-DPI Math Errors
 The UV coordinate math failed to correctly account for `display_framebuffer_scale`. On high-resolution screens, the blur sampling was offset by thousands of pixels, rendering the effect physically invisible or distorted.
 TODO:
 LOOK AT THIS SHIT:
 https://www.unknowncheats.me/forum/general-programming-and-reversing/617284-blurring-imgui-basically-window-using-acrylic-blur.html
 https://github.com/Speykious/opengl-playground/blob/main/src/scenes/blurring.rs
 https://www.intel.com/content/www/us/en/developer/articles/technical/an-investigation-of-fast-real-time-gpu-based-image-blur-algorithms.html
 https://github.com/cofenberg/unrimp/blob/45aa431286ce597c018675c1a9730d98e6ccfc64/Renderer/RendererRuntime/src/DebugGui/DebugGuiManager.cpp
 https://github.com/cofenberg/unrimp/blob/45aa431286ce597c018675c1a9730d98e6ccfc64/Renderer/RendererRuntime/src/DebugGui/Detail/Shader/DebugGui_GLSL_410.h
 https://github.com/itsRythem/ImGui-Blur
@@ -0,0 +1,6 @@
 # Track frosted_glass_20260313 Context (REPAIR)
 - [Debrief](./debrief.md)
 - [Specification](./spec.md)
 - [Implementation Plan](./plan.md)
 - [Metadata](./metadata.json)
@@ -0,0 +1,8 @@
 {
  "track_id": "frosted_glass_20260313",
  "type": "feature",
  "status": "new",
  "created_at": "2026-03-13T14:39:00Z",
  "updated_at": "2026-03-13T18:55:00Z",
  "description": "REPAIR: Implement stable frosted glass using native Windows DWM APIs."
 }
@@ -0,0 +1,19 @@
 # Implementation Plan: Frosted Glass Background Effect (REPAIR - TRUE GPU)
 ## Phase 1: Robust Shader & FBO Foundation
 - [x] Task: Implement: Create `ShaderManager` methods for downsampled FBO setup (scene, temp, blur). [d9148ac]
 - [x] Task: Implement: Develop the "Deep Sea" background shader and integrate it as the FBO source. [d85dc3a]
 - [x] Task: Implement: Develop the 2-pass Gaussian blur shaders with a wide tap distribution. [c8b7fca]
 - [x] Task: Conductor - User Manual Verification 'Phase 1: Robust Foundation' (Protocol in workflow.md)
 ## Phase 2: High-Performance Blur Pipeline
 - [x] Task: Implement: Create the `prepare_global_blur` method that renders the background and blurs it at 1/4 resolution. [9c2078a]
 - [x] Task: Implement: Ensure the pipeline correctly handles high-DPI scaling (`fb_scale`) for internal FBO dimensions. [9c2078a]
 - [x] Task: Conductor - User Manual Verification 'Phase 2: High-Performance Pipeline' (Protocol in workflow.md)
 ## Phase 3: GUI Integration & Screen-Space Sampling
 - [x] Task: Implement: Update `_render_frosted_background` to perform normalized screen-space UV sampling. [926318f]
 - [x] Task: Fix crash when display_size is invalid at startup. [db00fba]
 ## Phase 3: GUI Integration & Screen-Space Sampling
 - [x] Task: Implement: Update `_render_frosted_background` to perform normalized screen-space UV sampling. [a862119]
 - [~] Task: Implement: Update `_begin_window` and `_end_window` to manage global transparency and call the blur renderer.
@@ -0,0 +1,30 @@
 # Specification: Frosted Glass Background Effect (REPAIR - TRUE GPU)
 ## Overview
 Implement a high-fidelity "frosted glass" (acrylic) background effect using a dedicated OpenGL pipeline. This implementation follows professional rendering patterns (downsampling, multi-pass blurring, and screen-space sampling) to ensure a smooth, milky look that remains performant on high-DPI displays.
 ## Functional Requirements
 - **Dedicated Background Pipeline:**
  - Render the animated "Deep Sea" background shader to an off-screen `SceneFBO` once per frame.
 - **Multi-Scale Downsampled Blur:**
  - Downsample the `SceneFBO` texture to 1/4 or 1/8 resolution.
  - Perform 2-pass Gaussian blurring on the downsampled texture to achieve a creamy "milky" aesthetic.
 - **ImGui Panel Integration:**
  - Each ImGui panel must sample its background from the blurred texture using screen-space UV coordinates.
  - Automatically force window transparency (`alpha 0.0`) when the effect is active.
 - **Real-Time Shader Tuning:**
  - Control blur radius, tint intensity, and opacity via the Live Shader Editor.
 - **Stability:**
  - Balanced style-stack management to prevent ImGui assertion crashes.
  - Strict 1-space indentation and class scope protection.
 ## Technical Implementation
 - **FBO Management:** Persistent FBOs for scene, temp, and blur textures.
 - **UV Math:** `(window_pos / screen_res)` mapping to handle high-DPI scaling and vertical flipping.
 - **DrawList Callbacks:** (If necessary) use callbacks to ensure the background is ready before panels draw.
 ## Acceptance Criteria
 - [ ] Toggling the effect does not crash the app.
 - [ ] Windows show a deep, high-quality blur of the background shader.
 - [ ] Blur follows windows perfectly during drag/resize.
 - [ ] The "Milky" look is highly visible even at low radii.
@@ -0,0 +1,5 @@
 # Track gdscript_godot_script_language_support_tools_20260310 Context
 - [Specification](./spec.md)
 - [Implementation Plan](./plan.md)
 - [Metadata](./metadata.json)
@@ -0,0 +1,8 @@
 {
  "track_id": "gdscript_godot_script_language_support_tools_20260310",
  "type": "feature",
  "status": "new",
  "created_at": "2026-03-10T01:00:00Z",
  "updated_at": "2026-03-10T01:00:00Z",
  "description": "GDScript (godot script) language support tools"
 }
@@ -0,0 +1,25 @@
 # Implementation Plan: GDScript (Godot) MCP Tools
 ## Phase 1: Grammar Integration & Base Parser
 - [ ] Task: Update project dependencies (e.g., `requirements.txt` or `pyproject.toml`) to include the GDScript tree-sitter binding.
 - [ ] Task: Write Tests: Verify the tree-sitter parser can successfully initialize the GDScript language and parse a simple `func _ready(): pass` string.
 - [ ] Task: Implement: Create `src/gdscript_parser.py` (or extend existing AST parsers) to handle the base GDScript tree-sitter initialization and generic node walking.
 - [ ] Task: Conductor - User Manual Verification 'Phase 1: Grammar Integration & Base Parser' (Protocol in workflow.md)
 ## Phase 2: Structural & Context Tools
 - [ ] Task: Write Tests: Verify `gd_get_skeleton` and `gd_get_code_outline` against a complex GDScript file containing classes, `@export` vars, signals, and docstrings.
 - [ ] Task: Implement: Add `gd_get_skeleton` logic to extract signatures, Godot-specific keywords, and replace bodies with `pass`.
 - [ ] Task: Implement: Add `gd_get_code_outline` and `gd_get_docstring` logic to traverse the AST and map line numbers and comments.
 - [ ] Task: Conductor - User Manual Verification 'Phase 2: Structural & Context Tools' (Protocol in workflow.md)
 ## Phase 3: Surgical Editing Tools
 - [ ] Task: Write Tests: Verify `gd_get_definition` returns the exact source text of a targeted function, and `gd_update_definition` replaces it accurately within a larger file.
 - [ ] Task: Implement: Add `gd_get_definition` logic using AST line/byte ranges.
 - [ ] Task: Implement: Add `gd_update_definition` and `gd_set_signature` logic to perform string replacement based on strict AST node boundaries.
 - [ ] Task: Conductor - User Manual Verification 'Phase 3: Surgical Editing Tools' (Protocol in workflow.md)
 ## Phase 4: MCP Client Integration & Polish
 - [ ] Task: Write Tests: Verify the new tools are successfully registered and invokable via the `mcp_client.py` unified interface.
 - [ ] Task: Implement: Register the new `gd_*` functions as official tools in `src/mcp_client.py`.
 - [ ] Task: Implement: Ensure the caching layer (mtime invalidation) is correctly applied to the new GDScript parsing operations.
 - [ ] Task: Conductor - User Manual Verification 'Phase 4: MCP Client Integration & Polish' (Protocol in workflow.md)
@@ -0,0 +1,32 @@
 # Specification: GDScript (Godot) MCP Tools
 ## Overview
 Expand the Conductor's AI context-gathering and surgical editing capabilities by introducing full Tree-Sitter parsing support for GDScript (Godot's native scripting language). This will bring GDScript to feature-parity with the existing Python MCP tools, enabling deep AST-driven structural mapping, documentation extraction, and precise code modification.
 ## Functional Requirements
 - **Grammar Integration:**
  - Introduce a stable GDScript Tree-Sitter grammar (`tree-sitter-gdscript`) to the project's parsing environment via Python bindings (or the most robust available method) to generate deterministic Abstract Syntax Trees for `.gd` files.
 - **Structural Parsing Tools:**
  - **`gd_get_skeleton`:** Extract a high-level view of a GDScript file, containing all class declarations, signals, exported variables, and function signatures with their associated docstrings, replacing function bodies with `pass` or `...`.
  - **`gd_get_code_outline`:** Generate a hierarchical text outline showing line ranges for major structural elements (classes, functions, macros).
 - **Documentation & Context Tools:**
  - **`gd_get_docstring`:** Extract the block comment/docstring immediately preceding a function or class definition.
  - **`gd_find_usages`:** Locate usages of specific GDScript symbols/functions across a file or directory using AST or strict regex boundaries.
 - **Surgical Editing Tools:**
  - **`gd_get_definition`:** Extract the full source code of a specific GDScript function or class definition.
  - **`gd_update_definition`:** Surgically replace the implementation of a specific GDScript function without relying on generic search-and-replace strings.
  - **`gd_set_signature`:** Update only the signature (parameters/return type) of a GDScript function.
 ## Non-Functional Requirements
 - **Performance:** Parsing and skeleton generation should be heavily cached (using `mtime` invalidation) to ensure near-instantaneous responses, matching the current Python tool performance.
 - **Robustness:** The parser must gracefully handle malformed GDScript code, returning as much structural information as possible rather than failing entirely.
 ## Acceptance Criteria
 - [ ] A new suite of GDScript-specific tools (`gd_get_skeleton`, `gd_get_code_outline`, `gd_get_definition`, `gd_update_definition`) is available via the MCP Client.
 - [ ] Automated tests verify that `gd_get_skeleton` correctly identifies classes, inner classes, functions, and Godot-specific keywords (like `@export`, `signal`, `onready`).
 - [ ] `gd_update_definition` can successfully replace a multi-line function body while maintaining the surrounding file structure and indentation.
 - [ ] The `tree-sitter-gdscript` grammar is successfully integrated into the build/setup pipeline.
 ## Out of Scope
 - Full language server protocol (LSP) features like deep type inference or cross-file variable renaming.
 - Automated code formatting or linting for GDScript (formatting relies on external ecosystem tools if needed).
@@ -1,44 +1,44 @@
 # Implementation Plan: Expanded Hook API & Headless Orchestration
 ## Phase 1: WebSocket Infrastructure & Event Streaming
- [ ] Task: Implement the WebSocket gateway.
+- [x] Task: Implement the WebSocket gateway.
-    - [ ] Integrate a lightweight WebSocket library (e.g., `websockets` or `simple-websocket`).
+    - [x] Integrate a lightweight WebSocket library (e.g., `websockets` or `simple-websocket`).
-    - [ ] Create a dedicated `WebSocketServer` class in `src/api_hooks.py` that runs on a separate port (e.g., 9000).
+    - [x] Create a dedicated `WebSocketServer` class in `src/api_hooks.py` that runs on a separate port (e.g., 9000).
-    - [ ] Implement a basic subscription mechanism for different event channels.
+    - [x] Implement a basic subscription mechanism for different event channels.
- [ ] Task: Connect the event queue to the WebSocket stream.
+- [x] Task: Connect the event queue to the WebSocket stream.
-    - [ ] Update `AsyncEventQueue` to broadcast events to connected WebSocket clients.
+    - [x] Update `AsyncEventQueue` to broadcast events to connected WebSocket clients.
-    - [ ] Add high-frequency telemetry (FPS, CPU) to the event stream.
+    - [x] Add high-frequency telemetry (FPS, CPU) to the event stream.
- [ ] Task: Write unit tests for WebSocket connection and event broadcasting.
+- [x] Task: Write unit tests for WebSocket connection and event broadcasting.
- [ ] Task: Conductor - User Manual Verification 'Phase 1: WebSocket Infrastructure' (Protocol in workflow.md)
+- [x] Task: Conductor - User Manual Verification 'Phase 1: WebSocket Infrastructure' (Protocol in workflow.md)
 ## Phase 2: Expanded Read Endpoints (GET)
- [ ] Task: Implement detailed state exposure endpoints.
+- [x] Task: Implement detailed state exposure endpoints.
-    - [ ] Add `/api/mma/workers` to return the status, logs, and traces of all active sub-agents.
+    - [x] Add `/api/mma/workers` to return the status, logs, and traces of all active sub-agents.
-    - [ ] Add `/api/context/state` to expose AST cache metadata and file aggregation status.
+    - [x] Add `/api/context/state` to expose AST cache metadata and file aggregation status.
-    - [ ] Add `/api/metrics/financial` to return track-specific token usage and cost data.
+    - [x] Add `/api/metrics/financial` to return track-specific token usage and cost data.
-    - [ ] Add `/api/system/telemetry` to expose internal thread and queue metrics.
+    - [x] Add `/api/system/telemetry` to expose internal thread and queue metrics.
- [ ] Task: Enhance `/api/gui/state` to provide a truly exhaustive JSON dump of all internal managers.
+- [x] Task: Enhance `/api/gui/state` to provide a truly exhaustive JSON dump of all internal managers.
- [ ] Task: Update `api_hook_client.py` with corresponding methods for all new GET endpoints.
+- [x] Task: Update `api_hook_client.py` with corresponding methods for all new GET endpoints.
- [ ] Task: Write integration tests for all new GET endpoints using `live_gui`.
+- [x] Task: Write integration tests for all new GET endpoints using `live_gui`.
- [ ] Task: Conductor - User Manual Verification 'Phase 2: Expanded Read Endpoints' (Protocol in workflow.md)
+- [x] Task: Conductor - User Manual Verification 'Phase 2: Expanded Read Endpoints' (Protocol in workflow.md)
 ## Phase 3: Comprehensive Control Endpoints (POST)
- [ ] Task: Implement worker and pipeline control.
+- [x] Task: Implement worker and pipeline control.
-    - [ ] Add `/api/mma/workers/spawn` to manually initiate sub-agent execution via the API.
+    - [x] Add `/api/mma/workers/spawn` to manually initiate sub-agent execution via the API.
-    - [ ] Add `/api/mma/workers/kill` to programmatically abort running workers.
+    - [x] Add `/api/mma/workers/kill` to programmatically abort running workers.
-    - [ ] Add `/api/mma/pipeline/pause` and `/api/mma/pipeline/resume` to control the global MMA loop.
+    - [x] Add `/api/mma/pipeline/pause` and `/api/mma/pipeline/resume` to control the global MMA loop.
- [ ] Task: Implement context and DAG mutation.
+- [x] Task: Implement context and DAG mutation.
-    - [ ] Add `/api/context/inject` to allow programmatic context injection (files/skeletons).
+    - [x] Add `/api/context/inject` to allow programmatic context injection (files/skeletons).
-    - [ ] Add `/api/mma/dag/mutate` to allow modifying task dependencies through the API.
+    - [x] Add `/api/mma/dag/mutate` to allow modifying task dependencies through the API.
- [ ] Task: Update `api_hook_client.py` with corresponding methods for all new POST endpoints.
+- [x] Task: Update `api_hook_client.py` with corresponding methods for all new POST endpoints.
- [ ] Task: Write integration tests for all new control endpoints using `live_gui`.
+- [x] Task: Write integration tests for all new control endpoints using `live_gui`.
- [ ] Task: Conductor - User Manual Verification 'Phase 3: Comprehensive Control Endpoints' (Protocol in workflow.md)
+- [x] Task: Conductor - User Manual Verification 'Phase 3: Comprehensive Control Endpoints' (Protocol in workflow.md)
 ## Phase 4: Headless Refinement & Verification
- [ ] Task: Improve error reporting.
+- [x] Task: Improve error reporting.
-    - [ ] Refactor `HookHandler` to catch and wrap all internal exceptions in JSON error responses.
+    - [x] Refactor `HookHandler` to catch and wrap all internal exceptions in JSON error responses.
- [ ] Task: Conduct a full headless simulation.
+- [x] Task: Conduct a full headless simulation.
-    - [ ] Create a specialized simulation script that replicates a full MMA track lifecycle (planning, worker spawn, DAG mutation, completion) using ONLY the Hook API.
+    - [x] Create a specialized simulation script that replicates a full MMA track lifecycle (planning, worker spawn, DAG mutation, completion) using ONLY the Hook API.
- [ ] Task: Final performance audit.
+- [x] Task: Final performance audit.
-    - [ ] Ensure that active WebSocket clients and large state dumps do not cause GUI frame drops.
+    - [x] Ensure that active WebSocket clients and large state dumps do not cause GUI frame drops.
- [ ] Task: Conductor - User Manual Verification 'Phase 4: Headless Refinement & Verification' (Protocol in workflow.md)
+- [x] Task: Conductor - User Manual Verification 'Phase 4: Headless Refinement & Verification' (Protocol in workflow.md)
@@ -0,0 +1,5 @@
 # Track presets_ai_settings_ux_20260311 Context
 - [Specification](./spec.md)
 - [Implementation Plan](./plan.md)
 - [Metadata](./metadata.json)
@@ -0,0 +1,8 @@
 {
  "track_id": "presets_ai_settings_ux_20260311",
  "type": "feature",
  "status": "new",
  "created_at": "2026-03-11T14:45:00Z",
  "updated_at": "2026-03-11T14:45:00Z",
  "description": "Read through ./docs, and ./src/gui_2.py, ./src/app_controller.py. I want todo various ux improvements to the preset windows (personas, prompts, and tools) and ai settings."
 }
@@ -0,0 +1,33 @@
 # Implementation Plan: UI/UX Improvements - Presets and AI Settings
 This plan focuses on enhancing the layout, scaling, and control ergonomics of the Preset windows and AI Settings panel.
 ## Phase 1: Research and Layout Audit [checkpoint: db1f749]
 - [x] Task: Audit `src/gui_2.py` and `src/app_controller.py` for current window resizing and scaling logic. db1f749
 - [x] Task: Identify specific UI sections in `Personas`, `Prompts`, `Tools`, and `AI Settings` windows that require padding and width adjustments. db1f749
 - [x] Task: Conductor - User Manual Verification 'Phase 1: Research and Layout Audit' (Protocol in workflow.md) db1f749
 ## Phase 2: Preset Windows Layout & Scaling [checkpoint: 84ec24e]
 - [x] Task: Write tests to verify window layout stability and element visibility during simulated resizes. 84ec24e
 - [x] Task: Implement improved resize/scale policies for `Personas`, `Prompts`, and `Tools` windows. 84ec24e
 - [x] Task: Apply standardized padding and adjust input box widths across these windows. 84ec24e
 - [x] Task: Implement dual-control (Slider + Input Box) for any applicable parameters in these windows. 84ec24e
 - [x] Task: Conductor - User Manual Verification 'Phase 2: Preset Windows Layout & Scaling' (Protocol in workflow.md) 84ec24e
 ## Phase 3: AI Settings Overhaul [checkpoint: 0990270]
 - [x] Task: Write tests for AI Settings panel interactions and visual state consistency. 0990270
 - [x] Task: Refactor AI Settings panel to use visual sliders/knobs for Temperature, Top-P, and Max Tokens. 0990270
 - [x] Task: Integrate corresponding numeric input boxes for all AI setting sliders. 0990270
 - [x] Task: Improve visual clarity of preferred model entries when collapsed. 0990270
 - [x] Task: Conductor - User Manual Verification 'Phase 3: AI Settings Overhaul' (Protocol in workflow.md) 0990270
 ## Phase 4: Tool Management (MCP) Refinement [checkpoint: f21f22e]
 - [x] Task: Write tests for tool list rendering and category filtering. f21f22e
 - [x] Task: Update the tools section to display tool names before radio buttons with consistent spacing. f21f22e
 - [x] Task: Implement a category-based grouping/filtering system for tools (File I/O, Web, System, etc.). f21f22e
 - [x] Task: Conductor - User Manual Verification 'Phase 4: Tool Management (MCP) Refinement' (Protocol in workflow.md) f21f22e
 ## Phase 5: Final Integration and Verification [checkpoint: e0d441c]
 - [x] Task: Perform a comprehensive UI audit across all modified windows to ensure visual consistency. e0d441c
 - [x] Task: Run all automated tests and verify no regressions in GUI performance or functionality. e0d441c
 - [x] Task: Conductor - User Manual Verification 'Phase 5: Final Integration and Verification' (Protocol in workflow.md) e0d441c
@@ -0,0 +1,35 @@
 # Specification: UI/UX Improvements - Presets and AI Settings
 ## 1. Overview
 This track aims to improve the usability and visual layout of the Preset windows (Personas, Prompts, Tools) and the AI Settings panel. Key improvements include better layout scaling, consistent input controls, and categorized tool management.
 ## 2. Functional Requirements
 ### 2.1 Preset Windows (Personas, Prompts, Tools)
 - **Layout Scaling:** Implement improved resize and scaling policies for sub-panels and sections within each window to ensure they adapt well to different window sizes.
 - **Section Padding:** Increase and standardize padding between UI elements for better visual separation.
 - **Input Field Width:** Adjust the width of input boxes to provide adequate space for content while maintaining a balanced layout.
 - **Dual-Control Sliders:** All sliders for model parameters (Temperature, Top-P, etc.) must have a corresponding numeric input box for direct value entry.
 ### 2.2 AI Settings Panel
 - **Visual Controls:** Implement visual sliders and knobs for key model parameters.
 - **Collapsed View Clarity:** Improve the visual representation when a preferred model entry is collapsed, ensuring key information is still visible or the transition is intuitive.
 ### 2.3 Tool Management (MCP)
 - **Layout Refinement:** In the tools section, display the tool name first, followed by radio buttons with a small, consistent gap.
 - **Categorization:** Introduce category-based filtering or grouping (e.g., File I/O, Web, System) for easier management of large toolsets.
 ## 3. Non-Functional Requirements
 - **Consistency:** UI patterns and spacing must be consistent across all modified windows.
 - **Performance:** Ensure layout recalculations and rendering remain fluid during resizing.
 ## 4. Acceptance Criteria
 - [ ] Preset windows (Personas, Prompts, Tools) have improved scaling and spacing.
 - [ ] All sliders in the modified panels have corresponding numeric input boxes.
 - [ ] Tool names are displayed before radio buttons with consistent spacing.
 - [ ] AI Settings panel features improved visual controls and collapsed states.
 - [ ] Layout remains stable and usable across various window dimensions.
 ## 5. Out of Scope
 - Major functional changes to the AI logic or tool execution.
 - Overhaul of the theme/color palette (unless required for clarity).
@@ -0,0 +1,18 @@
 # Track Debrief: Saved System Prompt Presets
 ## Outcome
 Implemented foundational "System Prompt Presets" with scoped inheritance (Global/Project) and integrated model parameters (Temperature, Top-P, Max Tokens).
 ## Conceptual Dilemma
 During implementation, a conflict was identified between "Prompt Presets" and "Model Settings." Selecting a preset from a prompt dropdown currently overrides global model parameters, which is unintuitive when multiple prompts (Global, Project, MMA) contribute to a single agent turn.
 ## Future Direction: Agent Personas
 To resolve this, we will move toward a **Unified Persona** model. 
 - **Consolidation:** Provider, Model, Parameters, Prompts (all scopes), and Tool Presets will be grouped into a single "Persona" object.
 - **UI Overhaul:** The "AI Settings" panel will be refactored to focus on "Active Persona" selection rather than fragmented prompt/model controls.
 - **MMA Integration:** MMA agents will eventually be assigned specific Personas, allowing for differentiated behaviors (e.g., a "Creative Worker" vs. a "Strict QA").
 ## Implementation Sequence
 1. **Track: Saved Tool Presets** (Upcoming)
 2. **Track: Agent Tool Preference & Bias Tuning** (Upcoming)
 3. **Track: Agent Personas: Unified Profiles & Tool Presets** (Final Consolidation) - *This track will consume the findings from this debrief and the components from the preceding tracks.*
@@ -1,46 +1,50 @@
 # Implementation Plan: Saved System Prompt Presets
 ## Phase 1: Foundation & Data Model
- [ ] Task: Define the `Preset` data model and storage logic.
+- [x] Task: Define the `Preset` data model and storage logic.
-    - [ ] Create `src/models.py` (if not existing) or update it with a `Preset` dataclass/Pydantic model.
+    - [x] Create `src/models.py` (if not existing) or update it with a `Preset` dataclass/Pydantic model.
-    - [ ] Implement `PresetManager` in a new file `src/presets.py` to handle loading/saving to `presets.toml` and `project_presets.toml`.
+    - [x] Implement `PresetManager` in a new file `src/presets.py` to handle loading/saving to `presets.toml` and `project_presets.toml`.
-    - [ ] Implement the inheritance logic where project presets override global ones.
+    - [x] Implement the inheritance logic where project presets override global ones.
- [ ] Task: Write unit tests for `PresetManager`.
+- [x] Task: Write unit tests for `PresetManager`.
-    - [ ] Test loading global presets.
+    - [x] Test loading global presets.
-    - [ ] Test loading project presets.
+    - [x] Test loading project presets.
-    - [ ] Test the override logic (same name).
+    - [x] Test the override logic (same name).
-    - [ ] Test saving/updating presets.
+    - [x] Test saving/updating presets.
- [ ] Task: Conductor - User Manual Verification 'Phase 1: Foundation & Data Model' (Protocol in workflow.md)
+- [x] Task: Conductor - User Manual Verification 'Phase 1: Foundation & Data Model' (Protocol in workflow.md)
 ## Phase 2: UI: Settings Integration
- [ ] Task: Add Preset Dropdown to Global AI Settings.
+- [x] Task: Add Preset Dropdown to Global AI Settings.
-    - [ ] Modify `gui_2.py` to include a dropdown in the "AI Settings" panel.
+    - [x] Modify `gui_2.py` to include a dropdown in the "AI Settings" panel.
-    - [ ] Populated the dropdown with available global presets.
+    - [x] Populated the dropdown with available global presets.
- [ ] Task: Add Preset Dropdown to Project Settings.
+- [x] Task: Add Preset Dropdown to Project Settings.
-    - [ ] Modify `gui_2.py` to include a dropdown in the "Project Settings" panel.
+    - [x] Modify `gui_2.py` to include a dropdown in the "Project Settings" panel.
-    - [ ] Populated the dropdown with available project-specific presets (including overridden globals).
+    - [x] Populated the dropdown with available project-specific presets (including overridden globals).
- [ ] Task: Implement "Auto-Load" logic.
+- [x] Task: Implement "Auto-Load" logic.
-    - [ ] When a preset is selected, update the active system prompt and model settings in `gui_2.py`.
+    - [x] When a preset is selected, update the active system prompt and model settings in `gui_2.py`.
- [ ] Task: Write integration tests for settings integration using `live_gui`.
+- [x] Task: Write integration tests for settings integration using `live_gui`.
-    - [ ] Verify global dropdown shows global presets.
+    - [x] Verify global dropdown shows global presets.
-    - [ ] Verify project dropdown shows project + global presets.
+    - [x] Verify project dropdown shows project + global presets.
-    - [ ] Verify selecting a preset updates the UI fields (prompt, temperature).
+    - [x] Verify selecting a preset updates the UI fields (prompt, temperature).
- [ ] Task: Conductor - User Manual Verification 'Phase 2: UI: Settings Integration' (Protocol in workflow.md)
+- [x] Task: Conductor - User Manual Verification 'Phase 2: UI: Settings Integration' (Protocol in workflow.md)
 ## Phase 3: UI: Preset Manager Modal
- [ ] Task: Create the `PresetManagerModal` in `gui_2.py` (or a separate module).
+- [x] Task: Create the `PresetManagerModal` in `gui_2.py` (or a separate module).
-    - [ ] Implement a list view of all presets (global and project).
+    - [x] Implement a list view of all presets (global and project).
-    - [ ] Implement "Add", "Edit", and "Delete" functionality.
+    - [x] Implement "Add", "Edit", and "Delete" functionality.
-    - [ ] Ensure validation for unique names.
+    - [x] Ensure validation for unique names.
- [ ] Task: Add a button to open the manager modal from the settings panels.
+- [x] Task: Add a button to open the manager modal from the settings panels.
- [ ] Task: Write integration tests for the Preset Manager using `live_gui`.
+- [x] Task: Write integration tests for the Preset Manager using `live_gui`.
-    - [ ] Verify creating a new preset adds it to the list and dropdown.
+    - [x] Verify creating a new preset adds it to the list and dropdown.
-    - [ ] Verify editing an existing preset updates it correctly.
+    - [x] Verify editing an existing preset updates it correctly.
-    - [ ] Verify deleting a preset removes it from the list and dropdown.
+    - [x] Verify deleting a preset removes it from the list and dropdown.
- [ ] Task: Conductor - User Manual Verification 'Phase 3: UI: Preset Manager Modal' (Protocol in workflow.md)
+- [x] Task: Conductor - User Manual Verification 'Phase 3: UI: Preset Manager Modal' (Protocol in workflow.md)
 ## Phase 4: Final Integration & Polish
- [ ] Task: Ensure robust error handling for missing or malformed `.toml` files.
+- [x] Task: Ensure robust error handling for missing or malformed `.toml` files.
- [ ] Task: Final UI polish (spacing, icons, tooltips).
+- [x] Task: Bugfix: Correct `PresetManager` initialization to use project parent directory.
- [ ] Task: Run full suite of relevant tests.
+- [x] Task: Hardening: Wrap modal rendering in `try...finally` to prevent ImGui state corruption.
- [ ] Task: Conductor - User Manual Verification 'Phase 4: Final Integration & Polish' (Protocol in workflow.md)
+- [x] Task: Hardening: Ensure `PresetManager._save_file` validates that parent is a directory.
 - [x] Task: Feature: Implement "Pop Out Task DAG" option in MMA Dashboard.
 - [x] Task: Final UI polish (spacing, icons, tooltips).
 - [x] Task: Run full suite of relevant tests.
 - [x] Task: Conductor - User Manual Verification 'Phase 4: Final Integration & Polish' (Protocol in workflow.md)
@@ -1,44 +1,44 @@
 # Implementation Plan: Saved Tool Presets
 ## Phase 1: Data Model & Storage
- [ ] Task: Define the `ToolPreset` data model and storage logic.
+- [x] Task: Define the `ToolPreset` data model and storage logic.
-    - [ ] Create `src/tool_presets.py` to handle loading/saving to `tool_presets.toml`.
+    - [x] Create `src/tool_presets.py` to handle loading/saving to `tool_presets.toml`.
-    - [ ] Implement `ToolPresetManager` to manage CRUD operations for presets and categorization.
+    - [x] Implement `ToolPresetManager` to manage CRUD operations for presets and categorization.
- [ ] Task: Write unit tests for `ToolPresetManager`.
+- [x] Task: Write unit tests for `ToolPresetManager`.
-    - [ ] Test loading tool presets from TOML.
+    - [x] Test loading tool presets from TOML.
-    - [ ] Test saving tool presets to TOML.
+    - [x] Test saving tool presets to TOML.
-    - [ ] Test dynamic category parsing.
+    - [x] Test dynamic category parsing.
-    - [ ] Test tool approval flag persistence.
+    - [x] Test tool approval flag persistence.
- [ ] Task: Conductor - User Manual Verification 'Phase 1: Data Model & Storage' (Protocol in workflow.md)
+- [x] Task: Conductor - User Manual Verification 'Phase 1: Data Model & Storage' (Protocol in workflow.md)
 ## Phase 2: UI Integration (AI Settings)
- [ ] Task: Relocate tool settings to the AI Settings panel.
+- [x] Task: Relocate tool settings to the AI Settings panel.
-    - [ ] Modify `gui_2.py` to remove the current tool listing from the main panel and move it to the AI Settings panel (global/project).
+    - [x] Modify `gui_2.py` to remove the current tool listing from the main panel and move it to the AI Settings panel (global/project).
- [ ] Task: Implement dynamic tool categorization UI.
+- [x] Task: Implement dynamic tool categorization UI.
-    - [ ] Modify `gui_2.py` to render tools in sections based on categories defined in `tool_presets.toml`.
+    - [x] Modify `gui_2.py` to render tools in sections based on categories defined in `tool_presets.toml`.
-    - [ ] Implement toggleable "auto"/"ask" flags for each tool.
+    - [x] Implement toggleable "auto"/"ask" flags for each tool.
- [ ] Task: Implement Tool Preset dropdown for MMA agent roles.
+- [x] Task: Implement Tool Preset dropdown for MMA agent roles.
-    - [ ] Add the "Tool Preset" dropdown to the MMA agent role configuration modal in `gui_2.py`.
+    - [x] Add the "Tool Preset" dropdown to the MMA agent role configuration modal in `gui_2.py`.
- [ ] Task: Write integration tests for AI Settings UI using `live_gui`.
+- [x] Task: Write integration tests for AI Settings UI using `live_gui`.
-    - [ ] Verify tools are categorized correctly in the UI.
+    - [x] Verify tools are categorized correctly in the UI.
-    - [ ] Verify toggling a tool's approval persists correctly.
+    - [x] Verify toggling a tool's approval persists correctly.
-    - [ ] Verify the "Tool Preset" dropdown shows all available presets.
+    - [x] Verify the "Tool Preset" dropdown shows all available presets.
- [ ] Task: Conductor - User Manual Verification 'Phase 2: UI Integration (AI Settings)' (Protocol in workflow.md)
+- [x] Task: Conductor - User Manual Verification 'Phase 2: UI Integration (AI Settings)' (Protocol in workflow.md)
 ## Phase 3: AI Client & Execution Integration
- [ ] Task: Integrate tool presets into the AI Client.
+- [x] Task: Integrate tool presets into the AI Client.
-    - [ ] Modify `src/ai_client.py` to load and apply the selected tool preset for a given agent role.
+    - [x] Modify `src/ai_client.py` to load and apply the selected tool preset for a given agent role.
-    - [ ] Implement logic to restrict available tools and enforce "auto"/"ask" behavior based on the preset.
+    - [x] Implement logic to restrict available tools and enforce "auto"/"ask" behavior based on the preset.
- [ ] Task: Update MMA delegation to pass the selected tool preset.
+- [x] Task: Update MMA delegation to pass the selected tool preset.
-    - [ ] Modify `scripts/mma_exec.py` and `src/multi_agent_conductor.py` to pass the `tool_preset` to sub-agents.
+    - [x] Modify `scripts/mma_exec.py` and `src/multi_agent_conductor.py` to pass the `tool_preset` to sub-agents.
- [ ] Task: Write integration tests for AI execution with tool presets.
+- [x] Task: Write integration tests for AI execution with tool presets.
-    - [ ] Verify agents only have access to tools in their assigned preset.
+    - [x] Verify agents only have access to tools in their assigned preset.
-    - [ ] Verify "auto" tools execute without prompting, and "ask" tools require confirmation.
+    - [x] Verify "auto" tools execute without prompting, and "ask" tools require confirmation.
- [ ] Task: Conductor - User Manual Verification 'Phase 3: AI Client & Execution Integration' (Protocol in workflow.md)
+- [x] Task: Conductor - User Manual Verification 'Phase 3: AI Client & Execution Integration' (Protocol in workflow.md)
 ## Phase 4: Final Integration & Polish
- [ ] Task: Implement Preset Manager Modal.
+- [x] Task: Implement Preset Manager Modal.
-    - [ ] Create a modal for creating, editing, and deleting tool presets.
+    - [x] Create a modal for creating, editing, and deleting tool presets.
- [ ] Task: Final UI polish (spacing, icons, tooltips).
+- [x] Task: Final UI polish (spacing, icons, tooltips).
- [ ] Task: Run full suite of relevant tests.
+- [x] Task: Run full suite of relevant tests.
- [ ] Task: Conductor - User Manual Verification 'Phase 4: Final Integration & Polish' (Protocol in workflow.md)
+- [x] Task: Conductor - User Manual Verification 'Phase 4: Final Integration & Polish' (Protocol in workflow.md)
@@ -33,6 +33,14 @@ This feature adds the ability to create, save, and manage "Tool Presets" for age
 - [ ] The AI Settings panel correctly reflects the categorized tool list.
 ## Out of Scope
- Support for other file formats (e.g., JSON, YAML) for tool presets.
+- Support for other file formats (e.g., JSON, YAML) for presets.
 - Presets for specific files or folders (scoped only to global or project level).
- Cloud syncing of tool presets.
+- Cloud syncing of presets.
 ---
 ## Technical Note: Future Persona Consolidation
 This track is a prerequisite for the **"Agent Personas: Unified Profiles & Tool Presets"** overhaul. Implementation should align with the modular preset pattern established in `src/presets.py`. 
 Consult the **Debrief** in `conductor/tracks/saved_presets_20260308/debrief.md` for context on how these tool presets will eventually be merged with system prompts and model parameters into a unified configuration panel.
@@ -0,0 +1,5 @@
 # Track session_context_snapshots_20260311 Context
 - [Specification](./spec.md)
 - [Implementation Plan](./plan.md)
 - [Metadata](./metadata.json)
@@ -0,0 +1,8 @@
 {
  "track_id": "session_context_snapshots_20260311",
  "type": "feature",
  "status": "new",
  "created_at": "2026-03-11T19:30:00Z",
  "updated_at": "2026-03-11T19:30:00Z",
  "description": "Session Context Snapshots & Visibility: Tying files/screenshots to active session, saving Context Presets, MMA assignment, and agent-focused session filtering."
 }
@@ -0,0 +1,24 @@
 # Implementation Plan: Session Context Snapshots & Visibility
 ## Phase 1: Backend Support for Context Presets
 - [ ] Task: Write failing tests for saving, loading, and listing Context Presets in the project configuration.
 - [ ] Task: Implement Context Preset storage logic (e.g., updating TOML schemas in `project_manager.py`) to manage file/screenshot lists.
 - [ ] Task: Conductor - User Manual Verification 'Phase 1: Backend Support for Context Presets' (Protocol in workflow.md)
 ## Phase 2: GUI Integration & Persona Assignment
 - [ ] Task: Write tests for the Context Hub UI components handling preset saving and loading.
 - [ ] Task: Implement the UI controls in the Context Hub to save current selections as a preset and load existing presets.
 - [ ] Task: Update the Persona configuration UI (`personas.py` / `gui_2.py`) to allow assigning a named Context Preset to an agent persona.
 - [ ] Task: Conductor - User Manual Verification 'Phase 2: GUI Integration & Persona Assignment' (Protocol in workflow.md)
 ## Phase 3: Transparent Context Visibility
 - [ ] Task: Write tests to ensure the initial aggregate markdown, resolved system prompt, and file injection timestamps are accurately recorded in the session state.
 - [ ] Task: Implement UI elements in the Session Hub to expose the aggregated markdown and the active system prompt.
 - [ ] Task: Enhance the discussion timeline rendering in `gui_2.py` to visually indicate exactly when files and screenshots were injected into the context.
 - [ ] Task: Conductor - User Manual Verification 'Phase 3: Transparent Context Visibility' (Protocol in workflow.md)
 ## Phase 4: Agent-Focused Session Filtering
 - [ ] Task: Write tests for the GUI state filtering logic when focusing on a specific agent's session.
 - [ ] Task: Relocate the 'Focus Agent' feature from the Operations Hub to the MMA Dashboard.
 - [ ] Task: Implement the action to filter the Session and Discussion hubs based on the selected agent's context.
 - [ ] Task: Conductor - User Manual Verification 'Phase 4: Agent-Focused Session Filtering' (Protocol in workflow.md)
@@ -0,0 +1,28 @@
 # Specification: Session Context Snapshots & Visibility
 ## 1. Overview
 This track focuses on transitioning from global context management to explicit session-scoped context. It introduces transparent visibility into the exact context (system prompts, aggregated markdown, files, and screenshots) used in a session, allows saving context selections as reusable presets, and adds MMA dashboard integration for filtering session hubs by specific agents.
 ## 2. Functional Requirements
 ### 2.1 Context Presets & Assignment
 - **Context Snapshots:** Users can save the current selection of files and screenshots as a named "Context Preset".
 - **Preset Swapping:** Users can easily load a Context Preset into an active session.
 - **MMA Assignment:** Allow assigning specific Context Presets to individual MMA agent personas, preventing all agents from having access to all files by default.
 ### 2.2 Transparent Context Visibility
 - **No Hidden Context:** The Session Hub must expose the exact context provided to the model.
 - **Initial Payload Visibility:** The aggregated markdown content generated at the start of the discussion must be viewable in the UI.
 - **System Prompt State:** Display the fully resolved system prompt that was active for the session.
 - **Injection Timeline:** The UI must display *when* specific files or screenshots were injected or included during the progression of the discussion.
 ### 2.3 Agent-Focused Session Filtering
 - **Dashboard Integration:** Move the "Focus Agent" feature from the Operations Hub to the MMA Dashboard.
 - **Agent Context Filtering:** Add a button on any live agent's panel in the MMA Dashboard that automatically filters the other hubs (Session/Discussion) to show only information related to that specific agent's session.
 ## 3. Acceptance Criteria
 - [ ] Context selections (files/screenshots) can be saved and loaded as Presets.
 - [ ] MMA Agent Personas can be configured to use specific Context Presets.
 - [ ] The Session Hub displays the generated aggregate markdown and resolved system prompt.
 - [ ] The discussion timeline clearly shows when files/screenshots were injected.
 - [ ] The MMA Dashboard allows focusing the UI on a specific agent's session data.
@@ -0,0 +1,5 @@
 # Track test_harness_hardening_20260310 Context
 - [Specification](./spec.md)
 - [Implementation Plan](./plan.md)
 - [Metadata](./metadata.json)
@@ -0,0 +1,8 @@
 {
  "track_id": "test_harness_hardening_20260310",
  "type": "chore",
  "status": "new",
  "created_at": "2026-03-10T00:15:00Z",
  "updated_at": "2026-03-10T00:15:00Z",
  "description": "Hardening the Hook API and test harness to resolve port conflicts and state serialization issues."
 }
@@ -0,0 +1,24 @@
 # Implementation Plan: Hook API & Test Harness Hardening
 ## Phase 1: Dynamic Port Allocation
 - [ ] Task: Modify `src/api_hooks.py` to attempt binding to port `8999`. If unsuccessful, iterate up to `9010`.
 - [ ] Task: Upon successful binding, write the selected port to a temporary artifact file (e.g., `.mcp_port`).
 - [ ] Task: Update the `live_gui` fixture in `tests/conftest.py` to read the assigned port from the artifact file and use it for all `ApiHookClient` requests.
 - [ ] Task: Conductor - User Manual Verification 'Phase 1: Dynamic Port Allocation' (Protocol in workflow.md)
 ## Phase 2: Graceful Teardown
 - [ ] Task: Implement a `/api/shutdown` POST endpoint in `src/api_hooks.py`.
 - [ ] Task: Ensure the `/api/shutdown` endpoint correctly signals the `AppController` and `App` to perform a clean exit (e.g., joining threads, writing pending saves).
 - [ ] Task: Update the `live_gui` fixture to call `/api/shutdown` during teardown, relying on `taskkill` only as a last resort if the process fails to exit gracefully within a timeout.
 - [ ] Task: Conductor - User Manual Verification 'Phase 2: Graceful Teardown' (Protocol in workflow.md)
 ## Phase 3: State Serialization Audit
 - [ ] Task: Audit `src/app_controller.py` to identify all GUI-related state variables that should be exposed to tests (e.g., `show_windows`, individual window toggles).
 - [ ] Task: Update `_gettable_fields` to ensure all necessary state is mapped.
 - [ ] Task: Refine `_serialize_for_api` in `src/api_hooks.py` (or introduce lightweight dataclass parsing) to handle complex nested objects predictably.
 - [ ] Task: Conductor - User Manual Verification 'Phase 3: State Serialization Audit' (Protocol in workflow.md)
 ## Phase 4: Verification
 - [ ] Task: Write Tests: Create a concurrency test verifying multiple `live_gui` instances can launch simultaneously without port conflicts.
 - [ ] Task: Run the entire test suite to ensure the new dynamic port and graceful shutdown logic has not introduced regressions.
 - [ ] Task: Conductor - User Manual Verification 'Phase 4: Verification' (Protocol in workflow.md)
@@ -0,0 +1,32 @@
 # Specification: Hook API & Test Harness Hardening
 ## Overview
 This track focuses on stabilizing the local development and testing environment by hardening the Hook API and its associated `live_gui` test harness. The goal is to eliminate port conflicts, ensure graceful teardowns, and standardize state serialization, laying the groundwork for a future WebSockets implementation.
 ## Functional Requirements
 - **Dynamic Port Allocation:**
  - The Hook Server (`src/api_hooks.py`) will implement a Sequential Fallback strategy for port binding.
  - It will attempt to bind to port `8999`. If `Address already in use` is encountered, it will sequentially try ports up to `9010` until successful.
  - The successfully bound port will be written to a temporary artifact file (e.g., `.mcp_port` or similar) so the test harness can discover it.
 - **Graceful Teardown:**
  - Implement a new `/api/shutdown` POST endpoint in the Hook API.
  - When called, this endpoint should safely signal the `AppController` and `App` to initiate a clean shutdown (joining threads, closing files) rather than relying on the OS to forcefully kill the process tree.
  - Update the `live_gui` fixture to call this endpoint during the `finally` block before resorting to `taskkill` as a last-resort fallback.
 - **State Serialization Audit:**
  - Formalize the structure returned by `/api/gui/state`. 
  - Ensure all fields defined in `_gettable_fields` are safely serialized using standard dataclass/dict traversal (avoiding deep Pydantic dependencies for now, keeping it lightweight but strictly typed for future WebSocket pipeline compatibility).
  - Add missing fields discovered during recent UI tracks (e.g., `show_windows` states).
 ## Non-Functional Requirements
 - **Stability:** The `live_gui` fixture must pass 100% of the time without port conflict errors when tests are run sequentially.
 - **Performance:** The port scanning logic should fail fast and bind within milliseconds.
 ## Acceptance Criteria
 - [ ] A test script can successfully launch two concurrent `live_gui` instances, and they bind to different ports.
 - [ ] Calling `/api/shutdown` successfully stops the GUI process and returns a 200 OK.
 - [ ] The `live_gui` fixture uses the shutdown endpoint and the test suite passes without leaving orphaned processes.
 - [ ] The state returned by `/api/gui/state` is fully documented and includes all relevant nested objects (like `show_windows`).
 ## Out of Scope
 - Implementing the WebSockets streaming logic (this track only prepares the state schema for it).
 - Fixing failing simulation tests that are unrelated to the harness itself.
@@ -0,0 +1,5 @@
 # Track text_viewer_rich_rendering_20260313 Context
 - [Specification](./spec.md)
 - [Implementation Plan](./plan.md)
 - [Metadata](./metadata.json)
@@ -0,0 +1,8 @@
 {
  "track_id": "text_viewer_rich_rendering_20260313",
  "type": "feature",
  "status": "new",
  "created_at": "2026-03-13T14:22:00Z",
  "updated_at": "2026-03-13T14:22:00Z",
  "description": "Make the text viewer support syntax highlighting and markdown for different text types. Whatever feeds the text viewer new context must specify the type to use otherwise fallback to just regular text visualization without highlighting or markdown rendering."
 }
@@ -0,0 +1,29 @@
 # Implementation Plan: Advanced Text Viewer with Syntax Highlighting
 ## Phase 1: State & Interface Update
 - [ ] Task: Audit `src/gui_2.py` to ensure all `text_viewer_*` state variables are explicitly initialized in `App.__init__`.
 - [ ] Task: Implement: Update `App.__init__` to initialize `self.show_text_viewer`, `self.text_viewer_title`, `self.text_viewer_content`, and new `self.text_viewer_type` (defaulting to "text").
 - [ ] Task: Implement: Update `self.text_viewer_wrap` (defaulting to True) to allow independent word wrap.
 - [ ] Task: Implement: Update `_render_text_viewer(self, label: str, content: str, text_type: str = "text")` signature and caller usage.
 - [ ] Task: Conductor - User Manual Verification 'Phase 1: State & Interface Update' (Protocol in workflow.md)
 ## Phase 2: Core Rendering Logic (Code & MD)
 - [ ] Task: Write Tests: Create a simulation test in `tests/test_gui_text_viewer.py` to verify the viewer opens and switches rendering paths based on `text_type`.
 - [ ] Task: Implement: In `src/gui_2.py`, refactor the text viewer window loop to:
  - Use `MarkdownRenderer.render` if `text_type == "markdown"`.
  - Use a cached `ImGuiColorTextEdit.TextEditor` if `text_type` matches a code language.
  - Fallback to `imgui.input_text_multiline` for plain text.
 - [ ] Task: Implement: Ensure the `TextEditor` instance is properly cached using a unique key for the text viewer to maintain state.
 - [ ] Task: Conductor - User Manual Verification 'Phase 2: Core Rendering Logic' (Protocol in workflow.md)
 ## Phase 3: UI Features (Copy, Line Numbers, Wrap)
 - [ ] Task: Write Tests: Update `tests/test_gui_text_viewer.py` to verify the copy-to-clipboard functionality and word wrap toggle.
 - [ ] Task: Implement: Add a "Copy" button to the text viewer title bar or a small toolbar at the top of the window.
 - [ ] Task: Implement: Add a "Word Wrap" checkbox inside the text viewer window.
 - [ ] Task: Implement: Configure the `TextEditor` instance to show line numbers and be read-only.
 - [ ] Task: Conductor - User Manual Verification 'Phase 3: UI Features' (Protocol in workflow.md)
 ## Phase 4: Integration & Rollout
 - [ ] Task: Implement: Update all existing calls to `_render_text_viewer` in `src/gui_2.py` (e.g., in `_render_files_panel`, `_render_tool_calls_panel`) to pass the correct `text_type` based on file extension or content.
 - [ ] Task: Implement: Add "Markdown Preview" support for system prompt presets using the new text viewer logic.
 - [ ] Task: Conductor - User Manual Verification 'Phase 4: Integration & Rollout' (Protocol in workflow.md)
@@ -0,0 +1,30 @@
 # Specification: Advanced Text Viewer with Syntax Highlighting
 ## Overview
 Enhance the existing "Text Viewer" popup panel in the Manual Slop GUI to support rich rendering, including syntax highlighting for various code types and Markdown rendering. The viewer will transition from a basic text/multiline input to a specialized component leveraging the project's hybrid rendering pattern.
 ## Functional Requirements
 - **Rich Rendering Support:**
  - **Code:** Integration with `ImGuiColorTextEdit` for syntax highlighting (Python, PowerShell, JSON, TOML, etc.).
  - **Markdown:** Integration with `imgui_markdown` for rendering formatted text and documents.
  - **Fallback:** Plain text rendering for unknown or unspecified types.
 - **Explicit Type Specification:**
  - The component/function triggering the viewer (e.g., `_render_text_viewer`) must provide an explicit `text_type` parameter (e.g., "python", "markdown", "text").
 - **Enhanced UI Features:**
  - **Line Numbers:** Display line numbers in the gutter when viewing code.
  - **Copy Button:** A dedicated button to copy the entire content to the clipboard.
  - **Independent Word Wrap:** A toggle within the viewer window to enable/disable word wrapping specifically for that instance, overriding the global GUI setting if necessary.
  - **Persistent Sizing:** The viewer should maintain its size/position via ImGui's standard `.ini` persistence.
 ## Technical Implementation
 - Update `App` state in `src/gui_2.py` to store `text_viewer_type`.
 - Modify `_render_text_viewer` signature to accept `text_type`.
 - Update the rendering loop in `_gui_func` to switch between `MarkdownRenderer` logic and `TextEditor` logic based on `text_viewer_type`.
 - Ensure proper caching of `TextEditor` instances to maintain scroll position and selection state while the viewer is open.
 ## Acceptance Criteria
 - [ ] Clicking a preview button for a Python file opens the viewer with syntax highlighting and line numbers.
 - [ ] Clicking a preview for a `.md` file renders it as formatted Markdown.
 - [ ] The "Copy" button correctly copies text to the OS clipboard.
 - [ ] The word wrap toggle works immediately without affecting other panels.
 - [ ] Unsupported types gracefully fall back to standard plain text.
@@ -0,0 +1,5 @@
 # Track thinking_trace_handling_20260313 Context
 - [Specification](./spec.md)
 - [Implementation Plan](./plan.md)
 - [Metadata](./metadata.json)
@@ -0,0 +1,8 @@
 {
  "track_id": "thinking_trace_handling_20260313",
  "type": "feature",
  "status": "new",
  "created_at": "2026-03-13T13:28:00Z",
  "updated_at": "2026-03-13T13:28:00Z",
  "description": "Properly section and handle 'agent thinking' responses from the ai. Right now we just have <thinking> indicators not sure if thats a bodge or if there is a richer way we could be handling this..."
 }
@@ -0,0 +1,26 @@
 # Implementation Plan: Rich Thinking Trace Handling
 ## Phase 1: Core Parsing & Model Update
 - [ ] Task: Audit `src/models.py` and `src/project_manager.py` to identify current message serialization schemas.
 - [ ] Task: Write Tests: Verify that raw AI responses with `<thinking>`, `<thought>`, and `Thinking:` markers are correctly parsed into segmented data structures (Thinking vs. Response).
 - [ ] Task: Implement: Add `ThinkingSegment` model and update `ChatMessage` schema in `src/models.py` to support optional thinking traces.
 - [ ] Task: Implement: Update parsing logic in `src/ai_client.py` or a dedicated utility to extract segments from raw provider responses.
 - [ ] Task: Conductor - User Manual Verification 'Phase 1: Core Parsing & Model Update' (Protocol in workflow.md)
 ## Phase 2: Persistence & History Integration
 - [ ] Task: Write Tests: Verify that `ProjectManager` correctly serializes and deserializes messages with thinking segments to/from TOML history files.
 - [ ] Task: Implement: Update `src/project_manager.py` to handle the new `ChatMessage` schema during session save/load.
 - [ ] Task: Implement: Ensure `src/aggregate.py` or relevant context builders include thinking traces in the "Discussion History" sent back to the AI.
 - [ ] Task: Conductor - User Manual Verification 'Phase 2: Persistence & History Integration' (Protocol in workflow.md)
 ## Phase 3: GUI Rendering - Comms & Discussion
 - [ ] Task: Write Tests: Verify the GUI rendering logic correctly handles messages with and without thinking segments.
 - [ ] Task: Implement: Create a reusable `_render_thinking_trace` helper in `src/gui_2.py` using a collapsible header (e.g., `imgui.collapsing_header`).
 - [ ] Task: Implement: Integrate the thinking trace renderer into the **Comms History** panel in `src/gui_2.py`.
 - [ ] Task: Implement: Integrate the thinking trace renderer into the **Discussion Hub** message loop in `src/gui_2.py`.
 - [ ] Task: Conductor - User Manual Verification 'Phase 3: GUI Rendering - Comms & Discussion' (Protocol in workflow.md)
 ## Phase 4: Final Polish & Theming
 - [ ] Task: Implement: Apply specialized styling (e.g., tinted background or italicized text) to expanded thinking traces to distinguish them from direct responses.
 - [ ] Task: Implement: Ensure thinking trace headers show a "Calculating..." or "Monologue" indicator while an agent is active.
 - [ ] Task: Conductor - User Manual Verification 'Phase 4: Final Polish & Theming' (Protocol in workflow.md)
@@ -0,0 +1,31 @@
 # Specification: Rich Thinking Trace Handling
 ## Overview
 Implement a formal system for parsing, storing, and rendering "agent thinking" monologues (chains of thought) within the Manual Slop GUI. Currently, thinking traces are treated as raw text or simple markers. This track will introduce a structured UI pattern to separate internal monologue from direct user responses while preserving both for future context.
 ## Functional Requirements
 - **Multi-Format Parsing:** Support extraction of thinking traces from `<thinking>...</thinking>`, `<thought>...</thought>`, and blocks prefixed with `Thinking:`.
 - **Integrated UI Rendering:**
  - In the **Comms History** and **Discussion Hub**, thinking traces must be rendered in a distinct, collapsible section.
  - The section should be **Collapsed by Default** to minimize visual noise.
  - Thinking traces must be visually separated from the "visible" response (e.g., using a tinted background, border, or specialized header).
 - **Persistent State Management:**
  - Both the thinking monologue and the final response must be saved to the permanent discussion history (`manual_slop_history.toml` or `project_history.toml`).
  - History entries must be properly tagged/schematized to distinguish between thinking and output.
 - **Context Recurrence:**
  - Thinking traces must be included in subsequent AI turns (Full Recurrence) to maintain the model's internal state and logical progression.
 ## Non-Functional Requirements
 - **Performance:** Parsing and rendering of thinking blocks must not introduce visible latency in the GUI thread.
 - **Accessibility:** All thinking blocks must remain selectable and copyable via the standard high-fidelity selectable UI pattern.
 ## Acceptance Criteria
 - [ ] AI responses containing `<thinking>` or similar tags are automatically parsed into separate segments.
 - [ ] A "Thinking..." header appears in the Discussion Hub for messages with monologues.
 - [ ] Clicking the header expands the full thinking trace.
 - [ ] Saving/Loading a project preserves the distinction between thinking and response.
 - [ ] Subsequent AI calls receive the thinking trace as part of the conversation history.
 ## Out of Scope
 - Implementing "Hidden Thinking" (where the user cannot see it but the AI can).
 - Real-time "Streaming" of thinking into the UI (unless already supported by the active provider).
@@ -1,41 +1,41 @@
 # Implementation Plan: Agent Tool Preference & Bias Tuning
-## Phase 1: Data Model & Storage Extension
+## Phase 1: Data Model & Storage Extension [checkpoint: 77a0b38]
- [ ] Task: Extend the `ToolPreset` and `Tool` models.
+- [x] Task: Extend the `ToolPreset` and `Tool` models. 77a0b38
-    - [ ] Update `src/tool_presets.py` (created in the dependency track) to include `weight` (int, 1-5) for tools.
+    - [x] Update `src/tool_presets.py` to include `weight` (int, 1-5) for tools. 77a0b38
-    - [ ] Add `parameter_bias` (dict mapping parameter names to priority strings) to the `Tool` model.
+    - [x] Add `parameter_bias` (dict mapping parameter names to priority strings) to the `Tool` model. 77a0b38
-    - [ ] Update `ToolPresetManager` to handle saving and loading these new fields from `tool_presets.toml`.
+    - [x] Update `ToolPresetManager` to handle saving and loading these new fields from `tool_presets.toml`. 77a0b38
- [ ] Task: Implement Global Bias Profiles.
+- [x] Task: Implement Global Bias Profiles. 77a0b38
-    - [ ] Define `BiasProfile` dataclass in `src/models.py`.
+    - [x] Define `BiasProfile` dataclass in `src/models.py`. 77a0b38
-    - [ ] Implement logic to store and retrieve these profiles from `config.toml`.
+    - [x] Implement logic to store and retrieve these profiles from `tool_presets.toml`. 77a0b38
- [ ] Task: Write unit tests for the extended data model and storage logic.
+- [x] Task: Write unit tests for the extended data model and storage logic. 77a0b38
- [ ] Task: Conductor - User Manual Verification 'Phase 1: Data Model Extension' (Protocol in workflow.md)
+- [x] Task: Conductor - User Manual Verification 'Phase 1: Data Model Extension' (Protocol in workflow.md) 77a0b38
-## Phase 2: Orchestration & Nudging Logic
+## Phase 2: Orchestration & Nudging Logic [checkpoint: cad04bf]
- [ ] Task: Implement the `ToolBiasEngine` in `src/ai_client.py` (or a new module).
+- [x] Task: Implement the `ToolBiasEngine` in `src/ai_client.py` (or a new module). cad04bf
-    - [ ] Implement `apply_semantic_nudges(tool_definitions, preset)`: This function should modify tool descriptions with priority tags.
+    - [x] Implement `apply_semantic_nudges(tool_definitions, preset)`: This function should modify tool descriptions with priority tags. cad04bf
-    - [ ] Implement `generate_tooling_strategy(preset, global_bias)`: This function should return a Markdown string for the system prompt.
+    - [x] Implement `generate_tooling_strategy(preset, global_bias)`: This function should return a Markdown string for the system prompt. cad04bf
- [ ] Task: Integrate the bias engine into the AI client `send()` loop.
+- [x] Task: Integrate the bias engine into the AI client `send()` loop. cad04bf
-    - [ ] Ensure that for every agent turn, the tool definitions and system instructions are dynamically biased based on the active agent's role and selected preset.
+    - [x] Ensure that for every agent turn, the tool definitions and system instructions are dynamically biased based on the active agent's role and selected preset. cad04bf
- [ ] Task: Write integration tests for the bias generation logic.
+- [x] Task: Write integration tests for the bias generation logic. cad04bf
-    - [ ] Verify that high-weight tools correctly receive "[HIGH PRIORITY]" tags.
+    - [x] Verify that high-weight tools correctly receive "[HIGH PRIORITY]" tags. cad04bf
-    - [ ] Verify that the strategy section is correctly appended to the system instructions.
+    - [x] Verify that the strategy section is correctly appended to the system instructions. cad04bf
- [ ] Task: Conductor - User Manual Verification 'Phase 2: Orchestration Logic' (Protocol in workflow.md)
+- [x] Task: Conductor - User Manual Verification 'Phase 2: Orchestration Logic' (Protocol in workflow.md) cad04bf
-## Phase 3: GUI Integration
+## Phase 3: GUI Integration [checkpoint: 1c83b3e]
- [ ] Task: Update the Tool Preset Manager UI.
+- [x] Task: Update the Tool Preset Manager UI. 1c83b3e
-    - [ ] Add `imgui.slider_int` for each tool to adjust its weight.
+    - [x] Add `imgui.slider_int` for each tool to adjust its weight. 1c83b3e
-    - [ ] Add a sub-menu or modal for editing parameter-level bias.
+    - [x] Add a sub-menu or modal for editing parameter-level bias. 1c83b3e
- [ ] Task: Enhance tool list visualization.
+- [x] Task: Enhance tool list visualization. 1c83b3e
-    - [ ] Implement color-coded priority badges in the Operations panel and tool settings.
+    - [x] Implement color-coded priority badges in the Operations panel and tool settings. 1c83b3e
- [ ] Task: Implement the "Bias Override" in the agent focus modal.
+- [x] Task: Implement the "Bias Override" in the agent focus modal. 1c83b3e
-    - [ ] Add a dropdown to select a global bias profile or a specific preset override before spawning a worker.
+    - [x] Add a dropdown to select a global bias profile or a specific preset override before spawning a worker. 1c83b3e
- [ ] Task: Write visual regression tests using `live_gui` to verify the new UI components.
+- [x] Task: Write integration tests for the new UI data flow. 1c83b3e
- [ ] Task: Conductor - User Manual Verification 'Phase 3: GUI Integration' (Protocol in workflow.md)
+- [x] Task: Conductor - User Manual Verification 'Phase 3: GUI Integration' (Protocol in workflow.md) 1c83b3e
-## Phase 4: Verification & Final Polish
+## Phase 4: Verification & Final Polish [checkpoint: 85ae409]
- [ ] Task: Create a Bias Efficacy Simulation.
+- [x] Task: Create a Bias Efficacy Simulation. 85ae409
-    - [ ] Implement a specialized simulation test where two tools could solve a problem, and verify the agent chooses the one with higher weight.
+    - [x] Implement a specialized simulation test where two tools could solve a problem, and verify the agent chooses the one with higher weight. 85ae409
- [ ] Task: Final UI polish (spacing, icons, tooltips explaining the bias system).
+- [x] Task: Final UI polish (spacing, icons, tooltips explaining the bias system). 85ae409
- [ ] Task: Run full suite of relevant tests.
+- [x] Task: Run full suite of relevant tests. 85ae409
- [ ] Task: Conductor - User Manual Verification 'Phase 4: Verification & Polish' (Protocol in workflow.md)
+- [x] Task: Conductor - User Manual Verification 'Phase 4: Verification & Polish' (Protocol in workflow.md) 85ae409
@@ -38,3 +38,11 @@ This track introduces a mechanism to influence AI agent tool selection by implem
 ## Out of Scope
 - Implementing reinforcement learning to "learn" tool weights automatically.
 - Hardcoding weights into the AI client (all weights must be user-configurable via presets).
 ---
 ## Technical Note: Future Persona Consolidation
 This track is a prerequisite for the **"Agent Personas: Unified Profiles & Tool Presets"** overhaul. The weighting system implemented here must be architected to be saveable within a unified "Persona" profile.
 Consult the **Debrief** in `conductor/tracks/saved_presets_20260308/debrief.md` for context on how these bias settings will eventually be merged with system prompts and tool presets into a single configuration entity.
@@ -0,0 +1,5 @@
 # Track tree_sitter_lua_mcp_tools_20260310 Context
 - [Specification](./spec.md)
 - [Implementation Plan](./plan.md)
 - [Metadata](./metadata.json)
@@ -0,0 +1,8 @@
 {
  "track_id": "tree_sitter_lua_mcp_tools_20260310",
  "type": "feature",
  "status": "new",
  "created_at": "2026-03-10T00:45:00Z",
  "updated_at": "2026-03-10T00:45:00Z",
  "description": "Add Tree-Sitter Lua MCP tools for structural parsing, documentation extraction, and surgical editing."
 }
@@ -0,0 +1,25 @@
 # Implementation Plan: Tree-Sitter Lua MCP Tools
 ## Phase 1: Grammar Integration & Base Parser
 - [ ] Task: Update project dependencies (e.g., `requirements.txt` or `pyproject.toml`) to include `tree-sitter-lua` or equivalent.
 - [ ] Task: Write Tests: Verify the tree-sitter parser can successfully initialize the Lua language and parse a simple `local function test() end` string.
 - [ ] Task: Implement: Create `src/lua_parser.py` (or extend existing AST parsers) to handle the base Lua tree-sitter initialization and generic node walking.
 - [ ] Task: Conductor - User Manual Verification 'Phase 1: Grammar Integration & Base Parser' (Protocol in workflow.md)
 ## Phase 2: Structural & Context Tools
 - [ ] Task: Write Tests: Verify `lua_get_skeleton` and `lua_get_code_outline` against a complex Lua file containing nested functions, tables, and block comments.
 - [ ] Task: Implement: Add `lua_get_skeleton` logic to extract signatures, table assignments (e.g., `Module.func = function()`), and replace bodies with `...`.
 - [ ] Task: Implement: Add `lua_get_code_outline` and `lua_get_docstring` logic to traverse the AST and map line numbers and comments.
 - [ ] Task: Conductor - User Manual Verification 'Phase 2: Structural & Context Tools' (Protocol in workflow.md)
 ## Phase 3: Surgical Editing Tools
 - [ ] Task: Write Tests: Verify `lua_get_definition` returns the exact source text of a targeted function, and `lua_update_definition` replaces it accurately within a larger file.
 - [ ] Task: Implement: Add `lua_get_definition` logic using AST line/byte ranges.
 - [ ] Task: Implement: Add `lua_update_definition` and `lua_set_signature` logic to perform string replacement based on strict AST node boundaries.
 - [ ] Task: Conductor - User Manual Verification 'Phase 3: Surgical Editing Tools' (Protocol in workflow.md)
 ## Phase 4: MCP Client Integration & Polish
 - [ ] Task: Write Tests: Verify the new tools are successfully registered and invokable via the `mcp_client.py` unified interface.
 - [ ] Task: Implement: Register the new `lua_*` functions as official tools in `src/mcp_client.py`.
 - [ ] Task: Implement: Ensure the caching layer (mtime invalidation) is correctly applied to the new Lua parsing operations.
 - [ ] Task: Conductor - User Manual Verification 'Phase 4: MCP Client Integration & Polish' (Protocol in workflow.md)
@@ -0,0 +1,32 @@
 # Specification: Tree-Sitter Lua MCP Tools
 ## Overview
 Expand the Conductor's AI context-gathering and surgical editing capabilities by introducing full Tree-Sitter parsing support for the Lua programming language. This will bring Lua to feature-parity with the existing Python MCP tools, enabling deep AST-driven structural mapping, documentation extraction, and precise code modification.
 ## Functional Requirements
 - **Grammar Integration:**
  - Introduce `tree-sitter-lua` (or a suitable native equivalent) to the project's parsing environment to generate deterministic Abstract Syntax Trees for Lua files.
 - **Structural Parsing Tools:**
  - **`lua_get_skeleton`:** Extract a high-level view of a Lua file, containing all table/module declarations and function signatures with their associated comments, replacing function bodies with `...`.
  - **`lua_get_code_outline`:** Generate a hierarchical text outline showing line ranges for major structural elements (functions, loops, distinct blocks).
 - **Documentation & Context Tools:**
  - **`lua_get_docstring` (or comment block):** Extract the block comment immediately preceding a function or module definition.
  - **`lua_find_usages`:** Locate usages of specific Lua symbols/functions across a file or directory using AST or strict regex boundaries.
 - **Surgical Editing Tools:**
  - **`lua_get_definition`:** Extract the full source code of a specific Lua function or table definition.
  - **`lua_update_definition`:** Surgically replace the implementation of a specific Lua function without relying on generic search-and-replace strings.
  - **`lua_set_signature`:** Update only the signature (parameters) of a Lua function.
 ## Non-Functional Requirements
 - **Performance:** Parsing and skeleton generation should be heavily cached (using `mtime` invalidation) to ensure near-instantaneous responses, matching the current Python tool performance.
 - **Robustness:** The parser must gracefully handle malformed Lua code, returning as much structural information as possible rather than failing entirely.
 ## Acceptance Criteria
 - [ ] A new suite of Lua-specific tools (`lua_get_skeleton`, `lua_get_code_outline`, `lua_get_definition`, `lua_update_definition`) is available via the MCP Client.
 - [ ] Automated tests verify that `lua_get_skeleton` correctly identifies local functions, global functions, and table-assigned methods.
 - [ ] `lua_update_definition` can successfully replace a multi-line function body while maintaining the surrounding file structure and indentation.
 - [ ] The `tree-sitter-lua` grammar is successfully integrated into the build/setup pipeline.
 ## Out of Scope
 - Full language server protocol (LSP) features like deep type inference or cross-file variable renaming.
 - Automated code formatting or linting for Lua (formatting relies on external ecosystem tools if needed).
@@ -0,0 +1,5 @@
 # Track undo_redo_history_20260311 Context
 - [Specification](./spec.md)
 - [Implementation Plan](./plan.md)
 - [Metadata](./metadata.json)
@@ -0,0 +1,8 @@
 {
  "track_id": "undo_redo_history_20260311",
  "type": "feature",
  "status": "new",
  "created_at": "2026-03-11T20:15:00Z",
  "updated_at": "2026-03-11T20:15:00Z",
  "description": "Undo/Redo history support for non-provider based user actions: text inputs, UI controls, discussion structure, and context management."
 }
@@ -0,0 +1,29 @@
 # Implementation Plan: Undo/Redo History Support
 This plan implements a robust undo/redo system focusing on text inputs, control states, and discussion structure.
 ## Phase 1: History Core Logic & State Management
 - [ ] Task: Design and implement a generic `HistoryManager` class to handle undo/redo stacks and state snapshots.
 - [ ] Task: Write failing tests for the `HistoryManager` core logic, including capacity limits and basic undo/redo functionality.
 - [ ] Task: Implement `HistoryManager` to pass tests, ensuring it correctly manages a fixed stack of 50-100 actions.
 - [ ] Task: Conductor - User Manual Verification 'Phase 1: History Core Logic & State Management' (Protocol in workflow.md)
 ## Phase 2: Text Input & Control Undo/Redo
 - [ ] Task: Integrate `HistoryManager` with `src/gui_2.py` for system prompt and discussion entry text fields.
 - [ ] Task: Implement state snapshots for AI model parameter sliders (Temperature, Top-P) and checkboxes.
 - [ ] Task: Write simulation tests using `live_gui` to verify undo/redo for text edits and control changes.
 - [ ] Task: Conductor - User Manual Verification 'Phase 2: Text Input & Control Undo/Redo' (Protocol in workflow.md)
 ## Phase 3: Discussion & Context Structure Mutation
 - [ ] Task: Implement undo/redo for adding, deleting, and reordering discussion entries in `src/app_controller.py`.
 - [ ] Task: Extend the history system to track context file and screenshot additions/removals in `src/aggregate.py`.
 - [ ] Task: Write failing tests for reverting and redoing complex discussion tree mutations.
 - [ ] Task: Implement mutation tracking and restoration logic to pass tests.
 - [ ] Task: Conductor - User Manual Verification 'Phase 3: Discussion & Context Structure Mutation' (Protocol in workflow.md)
 ## Phase 4: UI Features - Hotkeys & History List
 - [ ] Task: Implement global hotkey handling for `Ctrl+Z` and `Ctrl+Y` / `Ctrl+Shift+Z` in the main GUI loop.
 - [ ] Task: Create a dedicated 'History List' panel in `src/gui_2.py` showing a scrollable list of recent actions.
 - [ ] Task: Implement functionality to jump to a specific historical state via the History List.
 - [ ] Task: Write final integration tests for the full undo/redo cycle across all supported areas.
 - [ ] Task: Conductor - User Manual Verification 'Phase 4: UI Features - Hotkeys & History List' (Protocol in workflow.md)
@@ -0,0 +1,38 @@
 # Specification: Undo/Redo History Support
 ## 1. Overview
 This track implements a robust, non-provider based Undo/Redo system within the Manual Slop GUI. It allows users to revert and redo common UI actions, focusing on text inputs, control states, and discussion structure, without impacting AI-generated content or remote state.
 ## 2. Functional Requirements
 ### 2.1 Supported Actions
 - **Text Inputs:** Undo/redo for system prompts, discussion entries, and any editable text boxes.
 - **UI Controls:** Revert changes to sliders (Temperature, Top-P), checkboxes, and preset selections.
 - **Discussion Structure:** Support undo/redo for deleting or inserting discussion entries.
 - **Context Management:** Undo/redo for additions and removals of context files and screenshots.
 ### 2.2 History Management
 - **Capacity:** A fixed limit of 50-100 actions in the undo stack.
 - **Scope:** History is session-specific and not persisted between application restarts.
 - **Exclusions:** Actions triggering AI vendor API requests or MMA track progression are explicitly excluded from the undo system.
 ### 2.3 User Interface
 - **Hotkeys:** Implementation of standard `Ctrl+Z` (Undo) and `Ctrl+Y` / `Ctrl+Shift+Z` (Redo) shortcuts.
 - **History List View:** A dedicated visual 'History List' panel showing recent actions, allowing users to jump back to specific points in the timeline.
 ## 3. Non-Functional Requirements
 - **Low Overhead:** The history system must have minimal impact on UI responsiveness.
 - **Thread Safety:** Ensure state snapshots and restorations are thread-safe within the GUI loop.
 ## 4. Acceptance Criteria
 - [ ] Users can undo and redo text edits in the system prompt and discussion fields.
 - [ ] UI control changes (sliders, presets) are correctly captured and restorable.
 - [ ] Discussion entry deletions/insertions can be reverted and redone.
 - [ ] Context additions/removals are tracked in the history.
 - [ ] `Ctrl+Z` and `Ctrl+Y` hotkeys work as expected.
 - [ ] The History List view accurately displays and allows jumping between states.
 ## 5. Out of Scope
 - Undo/redo for AI model generations or vendor API calls.
 - Undo/redo for MMA execution state transitions.
 - Persistent history across application restarts.
@@ -0,0 +1,5 @@
 # Track workspace_profiles_20260310 Context
 - [Specification](./spec.md)
 - [Implementation Plan](./plan.md)
 - [Metadata](./metadata.json)
@@ -0,0 +1,8 @@
 {
  "track_id": "workspace_profiles_20260310",
  "type": "feature",
  "status": "new",
  "created_at": "2026-03-10T00:30:00Z",
  "updated_at": "2026-03-10T00:30:00Z",
  "description": "Expand layout preset logic to allow users to save and switch between named workspace configurations."
 }
@@ -0,0 +1,25 @@
 # Implementation Plan: Advanced Workspace Docking & Layout Profiles
 ## Phase 1: Data Model & Persistence Engine
 - [ ] Task: Create a `WorkspaceProfile` dataclass in `src/models.py` to store INI string, `show_windows` dict, and panel states.
 - [ ] Task: Implement `WorkspaceManager` (similar to `PresetManager`) to handle saving/loading profiles from `config.toml` and `project.toml`.
 - [ ] Task: Write Tests: Verify the manager correctly merges global and project profiles and serializes the ImGui INI string properly.
 - [ ] Task: Conductor - User Manual Verification 'Phase 1: Data Model & Persistence Engine' (Protocol in workflow.md)
 ## Phase 2: ImGui State Extraction & Restoration
 - [ ] Task: Implement methods in `src/gui_2.py` (or a helper module) to safely capture the current ImGui layout (`imgui.save_ini_settings_to_memory()`).
 - [ ] Task: Implement methods to safely restore layout (`imgui.load_ini_settings_from_memory()`) and apply the associated `show_windows` state.
 - [ ] Task: Write Tests: Verify using `live_gui` that saving a layout and loading it back does not cause crashes or assertion failures in the ImGui render loop.
 - [ ] Task: Conductor - User Manual Verification 'Phase 2: ImGui State Extraction & Restoration' (Protocol in workflow.md)
 ## Phase 3: GUI Menu Integration
 - [ ] Task: Add a "Layout Profiles" menu under the main "Windows" or "View" menu bar in `src/gui_2.py`.
 - [ ] Task: Implement "Save Current Layout" modal (prompting for name and scope: Global/Project).
 - [ ] Task: Populate the menu with a dynamically generated list of available profiles to load.
 - [ ] Task: Conductor - User Manual Verification 'Phase 3: GUI Menu Integration' (Protocol in workflow.md)
 ## Phase 4: Contextual Auto-Switch (Experimental)
 - [ ] Task: Add UI in "AI Settings" or "Operations Hub" to enable "Experimental: Auto-switch layout by Tier".
 - [ ] Task: Add UI to bind specific profiles to Tiers 1 through 4.
 - [ ] Task: Implement the event hook in `AppController` so that when the `active_tier` changes, the bound profile is automatically loaded if the feature is enabled.
 - [ ] Task: Conductor - User Manual Verification 'Phase 4: Contextual Auto-Switch (Experimental)' (Protocol in workflow.md)
@@ -0,0 +1,31 @@
 # Specification: Advanced Workspace Docking & Layout Profiles
 ## Overview
 Expand the existing GUI window management to support named "Workspace Profiles." This will allow users to save, manage, and instantly switch between complex multi-window, multi-viewport docking arrangements.
 ## Functional Requirements
 - **Comprehensive State Capture:**
  - A Workspace Profile must capture:
    - ImGui layout data (positions, sizes, docking nodes) usually stored in `imgui.ini`.
    - Window visibility toggles (the `show_windows` dict and popout panel booleans).
    - Relevant internal panel state (e.g., active tabs, split sizes if applicable).
 - **Storage & Scope:**
  - Profiles follow a **Global + Project** inheritance model (similar to prompt presets). Global profiles are stored in `config.toml`, while project-specific profiles are stored in `manual_slop.toml` and can override global ones.
  - The system starts blank (no pre-loaded templates).
 - **Trigger Mechanisms:**
  - **Manual Menu:** A dedicated "Layout Profiles" sub-menu in the main menu bar (under "Windows" or "View") to save, load, and manage profiles.
  - **Contextual Auto-Switch (Experimental):** An opt-in setting that automatically switches to a designated profile based on the active MMA Tier or task context (e.g., switching to a "QA" layout when a Tier 4 worker spawns).
 ## Non-Functional Requirements
 - **ImGui INI Management:** Safely loading and saving raw ImGui INI strings using `imgui.load_ini_settings_from_memory` and `imgui.save_ini_settings_to_memory` without corrupting the active render frame.
 - **Graceful Fallback:** If a profile references a window that no longer exists, the layout engine should recover gracefully without crashing.
 ## Acceptance Criteria
 - [ ] A user can arrange windows, dock them, and save the current state as a named Workspace Profile.
 - [ ] Selecting a saved profile instantly re-arranges windows, updates visibility toggles, and restores internal tab states.
 - [ ] Profiles can be scoped globally or to a specific project.
 - [ ] An experimental toggle allows binding profiles to specific MMA Tiers for automatic switching.
 ## Out of Scope
 - Creating default templates (users will build their own).
 - Synchronizing layouts across different monitor resolutions (ImGui docking handles this best-effort, but pixel-perfect restoration on different hardware is out of scope).
@@ -2,8 +2,10 @@
 provider = "minimax"
 model = "MiniMax-M2.5"
 temperature = 0.0
-max_tokens = 24000
+top_p = 1.0
 max_tokens = 32000
 history_trunc_limit = 900000
 active_preset = "Default"
 system_prompt = ""
 [projects]
@@ -21,36 +23,57 @@ active = "C:/projects/gencpp/gencpp_sloppy.toml"
 separate_message_panel = false
 separate_response_panel = false
 separate_tool_calls_panel = false
-bg_shader_enabled = true
+bg_shader_enabled = false
 crt_filter_enabled = false
 separate_task_dag = false
 separate_usage_analytics = true
 separate_tier1 = false
 separate_tier2 = false
 separate_tier3 = false
 separate_tier4 = false
 separate_external_tools = true
 [gui.show_windows]
 "Context Hub" = true
 "Files & Media" = true
 "AI Settings" = true
 "MMA Dashboard" = true
-"Tier 1: Strategy" = true
+"Task DAG" = false
-"Tier 2: Tech Lead" = true
+"Usage Analytics" = true
-"Tier 3: Workers" = true
+"Tier 1" = false
-"Tier 4: QA" = true
+"Tier 2" = false
 "Tier 3" = false
 "Tier 4" = false
 "Tier 1: Strategy" = false
 "Tier 2: Tech Lead" = false
 "Tier 3: Workers" = false
 "Tier 4: QA" = false
 "Discussion Hub" = true
 "Operations Hub" = true
 Message = false
-Response = false
+Response = true
 "Tool Calls" = false
 Theme = true
 "Log Management" = true
 Diagnostics = false
 "External Tools" = false
 "Shader Editor" = true
 [theme]
 palette = "Nord Dark"
-font_path = "C:/projects/manual_slop/assets/fonts/Inter-Regular.ttf"
+font_path = "C:/projects/manual_slop/assets/fonts/MapleMono-Regular.ttf"
-font_size = 12.0
+font_size = 18.0
-scale = 1.25
+scale = 1.0
-transparency = 0.6499999761581421
+transparency = 0.4399999976158142
-child_transparency = 0.7200000286102295
+child_transparency = 0.5099999904632568
 [mma]
 max_workers = 4
 [headless]
 api_key = "test-secret-key"
 [paths]
 conductor_dir = "C:\\projects\\gencpp\\.ai\\conductor"
 logs_dir = "C:\\projects\\manual_slop\\logs"
 scripts_dir = "C:\\projects\\manual_slop\\scripts"
--- a/Show More
+++ b/Show More