conductor(checkpoint): Checkpoint end of Phase 1
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C:/projects/manual_slop/mma-orchestrator
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---
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name: mma-orchestrator
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description: Enforces the 4-Tier Hierarchical Multi-Model Architecture (MMA) within Gemini CLI using Token Firewalling and sub-agent task delegation.
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---
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# MMA Token Firewall & Tiered Delegation Protocol
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You are operating within the MMA Framework, acting as either the **Tier 1 Orchestrator** (for setup/init) or the **Tier 2 Tech Lead** (for execution). Your context window is extremely valuable and must be protected from token bloat (such as raw, repetitive code edits, trial-and-error histories, or massive stack traces).
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To accomplish this, you MUST delegate token-heavy or stateless tasks to **Tier 3 Workers** or **Tier 4 QA Agents** by spawning secondary Gemini CLI instances via `run_shell_command`.
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**CRITICAL Prerequisite:**
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To ensure proper environment handling and logging, you MUST NOT call the `gemini` command directly for sub-tasks. Instead, use the wrapper script:
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`uv run python scripts/mma_exec.py --role <Role> "..."`
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## 0. Architecture Fallback & Surgical Methodology
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**Before creating or refining any track**, consult the deep-dive architecture docs:
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- `docs/guide_architecture.md`: Thread domains, event system (`AsyncEventQueue`, `_pending_gui_tasks` action catalog), AI client multi-provider architecture, HITL Execution Clutch blocking flow, frame-sync mechanism
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- `docs/guide_tools.md`: MCP Bridge 3-layer security model, full 26-tool inventory with params, Hook API GET/POST endpoints with request/response formats, ApiHookClient method reference
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- `docs/guide_mma.md`: Ticket/Track/WorkerContext data structures, DAG engine (cycle detection, topological sort), ConductorEngine execution loop, Tier 2 ticket generation, Tier 3 worker lifecycle with context amnesia
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- `docs/guide_simulations.md`: `live_gui` fixture lifecycle, Puppeteer pattern, mock provider JSON-L protocol, visual verification patterns
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### The Surgical Spec Protocol (MANDATORY for track creation)
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When creating tracks (`activate_skill mma-tier1-orchestrator`), follow this protocol:
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1. **AUDIT BEFORE SPECIFYING**: Use `get_code_outline`, `py_get_definition`, `grep_search`, and `get_git_diff` to map what already exists. Previous track specs asked to re-implement existing features (Track Browser, DAG tree, approval dialogs) because no audit was done. Document findings in a "Current State Audit" section with file:line references.
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2. **GAPS, NOT FEATURES**: Frame requirements as what's MISSING relative to what exists.
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- GOOD: "The existing `_render_mma_dashboard` (gui_2.py:2633-2724) has a token usage table but no cost column."
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- BAD: "Build a metrics dashboard with token and cost tracking."
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3. **WORKER-READY TASKS**: Each plan task must specify:
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- **WHERE**: Exact file and line range (`gui_2.py:2700-2701`)
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- **WHAT**: The specific change (add function, modify dict, extend table)
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- **HOW**: Which API calls (`imgui.progress_bar(...)`, `imgui.collapsing_header(...)`)
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- **SAFETY**: Thread-safety constraints if cross-thread data is involved
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4. **ROOT CAUSE ANALYSIS** (for fix tracks): Don't write "investigate and fix." List specific candidates with code-level reasoning.
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5. **REFERENCE DOCS**: Link to relevant `docs/guide_*.md` sections in every spec.
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6. **MAP DEPENDENCIES**: State execution order and blockers between tracks.
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## 1. The Tier 3 Worker (Execution)
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When performing code modifications or implementing specific requirements:
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1. **Pre-Delegation Checkpoint:** For dangerous or non-trivial changes, ALWAYS stage your changes (`git add .`) or commit before delegating to a Tier 3 Worker. If the worker fails or runs `git restore`, you will lose all prior AI iterations for that file if it wasn't staged/committed.
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2. **Code Style Enforcement:** You MUST explicitly remind the worker to "use exactly 1-space indentation for Python code" in your prompt to prevent them from breaking the established codebase style.
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3. **DO NOT** perform large code writes yourself.
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4. **DO** construct a single, highly specific prompt with a clear objective. Include exact file:line references and the specific API calls to use (from your audit or the architecture docs).
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5. **DO** spawn a Tier 3 Worker.
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*Command:* `uv run python scripts/mma_exec.py --role tier3-worker "Implement [SPECIFIC_INSTRUCTION] in [FILE_PATH] at lines [N-M]. Use [SPECIFIC_API_CALL]. Use 1-space indentation."`
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6. **Handling Repeated Failures:** If a Tier 3 Worker fails multiple times on the same task, it may lack the necessary capability. You must track failures and retry with `--failure-count <N>` (e.g., `--failure-count 2`). This tells `mma_exec.py` to escalate the sub-agent to a more powerful reasoning model (like `gemini-3-flash`).
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7. The Tier 3 Worker is stateless and has tool access for file I/O.
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## 2. The Tier 4 QA Agent (Diagnostics)
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If you run a test or command that fails with a significant error or large traceback:
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1. **DO NOT** analyze the raw logs in your own context window.
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2. **DO** spawn a stateless Tier 4 agent to diagnose the failure.
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3. *Command:* `uv run python scripts/mma_exec.py --role tier4-qa "Analyze this failure and summarize the root cause: [LOG_DATA]"`
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4. **Mandatory Research-First Protocol:** Avoid direct `read_file` calls for any file over 50 lines. Use `get_file_summary`, `py_get_skeleton`, or `py_get_code_outline` first to identify relevant sections. Use `git diff` to understand changes.
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## 3. Persistent Tech Lead Memory (Tier 2)
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Unlike the stateless sub-agents (Tiers 3 & 4), the **Tier 2 Tech Lead** maintains persistent context throughout the implementation of a track. Do NOT apply "Context Amnesia" to your own session during track implementation. You are responsible for the continuity of the technical strategy.
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## 4. AST Skeleton & Outline Views
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To minimize context bloat for Tier 2 & 3:
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1. Use `py_get_code_outline` or `get_tree` to map out the structure of a file or project.
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2. Use `py_get_skeleton` and `py_get_imports` to understand the interface, docstrings, and dependencies of modules.
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3. Use `py_get_definition` to read specific functions/classes by name without loading entire files.
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4. Use `py_find_usages` to pinpoint where a function or class is called instead of searching the whole codebase.
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5. Use `py_check_syntax` after making string replacements to ensure the file is still syntactically valid.
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6. Only use `read_file` with `start_line` and `end_line` for specific implementation details once target areas are identified.
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7. Tier 3 workers MUST NOT read the full content of unrelated files.
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## 5. Cross-Skill Activation
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When your current role requires capabilities from another tier, use `activate_skill`:
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- **Track creation/refinement**: `activate_skill mma-tier1-orchestrator` — applies the Surgical Spec Protocol
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- **Track execution**: `activate_skill mma-tier2-tech-lead` — applies persistent context and TDD workflow
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- **Quick code task**: Spawn via `mma_exec.py --role tier3-worker` (stateless, no skill activation needed)
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- **Error analysis**: Spawn via `mma_exec.py --role tier4-qa` (stateless, no skill activation needed)
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<examples>
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### Example 1: Spawning a Tier 4 QA Agent
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**User / System:** `pytest tests/test_gui.py` failed with 400 lines of output.
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**Agent (You):**
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```json
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{
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"command": "python scripts/mma_exec.py --role tier4-qa \"Summarize this stack trace into a 20-word fix: [snip first 30 lines...]\"",
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"description": "Spawning Tier 4 QA to compress error trace statelessly."
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}
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```
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### Example 2: Spawning a Tier 3 Worker with Surgical Prompt
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**User:** Please implement the cost tracking column in the token usage table.
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**Agent (You):**
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```json
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{
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"command": "python scripts/mma_exec.py --role tier3-worker \"In gui_2.py, modify _render_mma_dashboard (lines 2685-2699). Extend the token usage table from 3 columns to 5 by adding 'Model' and 'Est. Cost' columns. Use imgui.table_setup_column() for the new columns. Import cost_tracker and call cost_tracker.estimate_cost(model, input_tokens, output_tokens) for each tier row. Add a total row at the bottom. Use 1-space indentation.\"",
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"description": "Delegating surgical implementation to Tier 3 Worker with exact line refs."
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}
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```
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### Example 3: Creating a Track with Audit
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**User:** Create a track for adding dark mode support.
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**Agent (You):**
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1. First, audit the codebase: `py_get_code_outline gui_2.py` → find `_render_theme_panel` (lines 2993-3030).
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2. Read the existing implementation: `py_get_definition gui_2.py _render_theme_panel`.
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3. Check for existing color constants: `grep_search "vec4\|C_" gui_2.py`.
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4. Now write the spec with a "Current State Audit" section documenting what the theme panel already does.
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5. Write tasks referencing the exact lines and imgui color APIs to use.
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</examples>
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<triggers>
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- When asked to write large amounts of boilerplate or repetitive code (Coding > 50 lines).
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- When encountering a large error trace from a shell execution (Errors > 100 lines).
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- When explicitly instructed to act as a "Tech Lead" or "Orchestrator".
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- When managing complex, multi-file Track implementations.
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- When creating or refining conductor tracks (MUST follow Surgical Spec Protocol).
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</triggers>
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@@ -8,7 +8,7 @@ This file tracks all major tracks for the project. Each track has its own detail
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*The following tracks MUST be executed in this exact order to safely resolve tech debt before feature development.*
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1. [ ] **Track: Test Suite Stabilization & Consolidation** (Active/Next)
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1. [~] **Track: Test Suite Stabilization & Consolidation** (Active/Next)
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*Link: [./tracks/test_stabilization_20260302/](./tracks/test_stabilization_20260302/)*
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2. [ ] **Track: Strict Static Analysis & Type Safety**
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8
conductor/tracks/ux_sim_test_20260302/metadata.json
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8
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{
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"id": "ux_sim_test_20260302",
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"title": "UX_SIM_TEST",
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"description": "Simulation testing for GUI UX",
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"type": "feature",
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"status": "new",
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"progress": 0.0
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}
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3
conductor/tracks/ux_sim_test_20260302/plan.md
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# Implementation Plan: UX_SIM_TEST
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- [ ] Task 1: Initialize
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5
conductor/tracks/ux_sim_test_20260302/spec.md
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# Specification: UX_SIM_TEST
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Type: feature
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Description: Simulation testing for GUI UX
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