manual_slop/docs

Documentation Index

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Overview

This documentation suite provides comprehensive technical reference for the Manual Slop application — a GUI orchestrator for local LLM-driven coding sessions. The guides follow a strict old-school technical documentation style, emphasizing architectural depth, state management details, algorithmic breakdowns, and structural formats.

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Guides

Guide	Contents
Architecture	Thread domains (GUI Main, Asyncio Worker, HookServer, Ad-hoc), cross-thread data structures (AsyncEventQueue, Guarded Lists, Condition-Variable Dialogs), event system (EventEmitter, SyncEventQueue, UserRequestEvent), application lifetime (boot sequence, shutdown sequence), task pipeline (producer-consumer synchronization), Execution Clutch (HITL mechanism with ConfirmDialog, MMAApprovalDialog, MMASpawnApprovalDialog), AI client multi-provider architecture (Gemini SDK, Anthropic, DeepSeek, Gemini CLI, MiniMax), Anthropic/Gemini caching strategies (4-breakpoint system, server-side TTL), context refresh mechanism (mtime-based file re-reading, diff injection), comms logging (JSON-L format), state machines (ai_status, HITL dialog state)
Meta-Boundary	Explicit distinction between the Application's domain (Strict HITL — gui_2.py, ai_client.py, multi_agent_conductor.py, dag_engine.py) and the Meta-Tooling domain (scripts/mma_exec.py, scripts/claude_mma_exec.py, scripts/tool_call.py, scripts/mcp_server.py, .gemini/, .claude/), preventing feature bleed and safety bypasses via shared bridges like mcp_client.py. Documents the Inter-Domain Bridges (cli_tool_bridge.py, claude_tool_bridge.py) and the GEMINI_CLI_HOOK_CONTEXT environment variable.
Tools & IPC	MCP Bridge 3-layer security model (Allowlist Construction, Path Validation, Resolution Gate), all 26 native tool signatures with parameters and behavior (File I/O, AST-Based, Analysis, Network, Runtime), Hook API GET/POST endpoints with request/response formats, ApiHookClient method reference (Connection Methods, State Query Methods, GUI Manipulation Methods, Polling Methods, HITL Method), /api/ask synchronous HITL protocol (blocking request-response over HTTP), session logging (comms.log, toolcalls.log, apihooks.log, clicalls.log, scripts/generated/*.ps1), shell runner (mcp_env.toml configuration, run_powershell function with timeout handling and QA callback integration)
MMA Orchestration	Ticket/Track/WorkerContext data structures (from models.py), DAG engine (TrackDAG class with cycle detection, topological sort, cascade_blocks; ExecutionEngine class with tick-based state machine), ConductorEngine execution loop (run method, _push_state for state broadcast, parse_json_tickets for ingestion), Tier 2 ticket generation (generate_tickets, topological_sort), Tier 3 worker lifecycle (run_worker_lifecycle with Context Amnesia, AST skeleton injection, HITL clutch integration via confirm_spawn and confirm_execution), Tier 4 QA integration (run_tier4_analysis, run_tier4_patch_callback), token firewalling (tier_usage tracking, model escalation), track state persistence (TrackState, save_track_state, load_track_state, get_all_tracks)
Simulations	Structural Testing Contract (Ban on Arbitrary Core Mocking, live_gui Standard, Artifact Isolation), live_gui pytest fixture lifecycle (spawning, readiness polling, failure path, teardown, session isolation via reset_ai_client), VerificationLogger for structured diagnostic logging, process cleanup (kill_process_tree for Windows/Unix), Puppeteer pattern (8-stage MMA simulation with mock provider setup, epic planning, track acceptance, ticket loading, status transitions, worker output verification), mock provider strategy (tests/mock_gemini_cli.py with JSON-L protocol, input mechanisms, response routing, output protocol), visual verification patterns (DAG integrity, stream telemetry, modal state, performance monitoring), supporting analysis modules (ASTParser with tree-sitter, summarize.py heuristic summaries, outline_tool.py hierarchical outlines)
Context Curation	Granular AST control (per-symbol masking as Def, Sig, or Hide for C/C++ files via ts_cpp_get_skeleton and ts_c_get_skeleton), Fuzzy Anchor Slices (resilient line ranges that survive file modifications via fuzzy_anchor.py), Interactive AST Tree Masking (modal flow for inspecting and masking individual classes/functions), Batch Operations (multi-select and batch state modification for the Context Panel), Context Snapshotting (per-Take state restoration via HistoryManager), Aggregation Pipeline integration (mask application order, view mode merging)
Shaders & Window	Hybrid shader injection strategy (ImDrawList primitives combined with PyOpenGL FBO for advanced effects), pure ImGui borderless window implementation (cross-platform compatible, custom drag/minimize/maximize/close via pywin32 on Windows), event metrics integration for shader performance tracking
RAG	Vector store lifecycle, chunking strategies (character-based and AST-aware), embedding providers (local sentence-transformers, Gemini Embedding 001), ChromaDB integration, parallelized indexing pipeline with mtime-based incremental updates, deep discussion integration with [RETRIEVED CONTEXT] injection, full public API surface with edge cases and limitations
Beads	Dolt-backed issue tracking (planned), current mock implementation (.beads_mock/beads.json), BeadsClient CRUD, MCP tool integration (bd_create, bd_list, bd_update, bd_ready), MMA integration roadmap, testing patterns, migration path from mock to real Dolt
Hot Reload	State-preserving module reloading (HotReloader and HotModule), UI delegation pattern enabling selective swap of rendering functions, capture-reload-restore-or-rollback lifecycle, keyboard trigger (Ctrl+Alt+R), visual error tint feedback, what can/cannot be safely reloaded
Personas	Unified agent profile model consolidating model settings (preferred_models), system prompt, tool preset, bias profile, context preset, and aggregation strategy, PersonaManager CRUD, scope-based inheritance (global vs project), MMA application flow in run_worker_lifecycle, editor modal fields
NERV Theme	"Black Void" palette with NERV orange/red/green/blue accents, zero-rounding geometry, CRT-style visual effects (scanlines, status flickering, alert animations), theme_nerv.py and theme_nerv_fx.py modules, FBO shader pipeline, configuration keys, performance cost, accessibility caveats
Workspace Profiles	Docking layouts and window visibility persistence, WorkspaceProfile schema with serialized docking_layout bytes, WorkspaceManager CRUD, scope inheritance (Global and Project), contextual auto-switch (experimental) binding profiles to MMA tier or task context, multi-monitor limitations
Command Palette	Fuzzy command resolution with subsequence matching and scoring, async context preview worker to prevent UI hangs, "Everything" mode for cross-domain search (commands, files, symbols, history, settings), streaming results via thread-safe queue, cancellation on query change, 50+ built-in commands, user-defined commands via TOML
Testing	273 test files, 5 test categories (unit, integration, live_gui, perf, simulation), 7 conftest fixtures (isolate_workspace, reset_paths, reset_ai_client, vlogger, kill_process_tree, mock_app, live_gui session-scoped), Hook API testing pattern, Puppeteer pattern for MMA simulation, mock provider strategy, opt-in clean install test, opt-in docker test, coverage targets, anti-patterns (no arbitrary core mocking, artifact isolation to tests/artifacts/), early-render C-level crash pattern (_ini_capture_ready defer-not-catch for imgui.save_ini_settings_to_memory), live_gui authoring contract (wait-for-ready pattern over time.sleep, narrow test paths over kitchen-sink render_main_interface mocks), test-ordering sensitivity (session-scoped fixture)
Themes	TOML-based theming system: file layout (themes/<name>.toml global + project_themes.toml per-project), schema (syntax_palette + [colors] table with imgui.Col_ snake_case keys), 4-syntax-palette upstream limit (imgui-bundle ships dark/light/mariana/retro_blue only), built-in vs TOML palette dispatch, load_themes_from_disk / get_syntax_palette_for_theme / apply_syntax_palette public API, hot-reload behavior, color-callable convention (C_LBL() / C_VAL() for theme-aware helpers)
GUI Main	src/gui_2.py reference: App class lifecycle, ~90 module-level render functions (UI Delegation Pattern), immgui immediate-mode rendering, Multi-Viewport docks, panel registry, command palette integration, ImGuiScope context managers, hot reload support, key bindings (Ctrl+Shift+P, Ctrl+Alt+R, Ctrl+Z/Y), _capture_workspace_profile defer-not-catch pattern (line 601-606, _ini_capture_ready flag for imgui.save_ini_settings_to_memory), theme color-callable pattern (e.g. DIR_COLORS/KIND_COLORS dicts store C_VAL not C_VAL() and are called at use site)
AI Client	src/ai_client.py reference: multi-provider LLM singleton (5 providers: Gemini, Anthropic, DeepSeek, MiniMax, Gemini CLI), async dispatch with asyncio.gather, threading.local for source tier tagging, context caching (Anthropic ephemeral + Gemini explicit), system prompt assembly, error interception for Tier 4 QA
API Hooks	src/api_hooks.py + src/api_hook_client.py reference: HookServer on 127.0.0.1:8999, ApiHookClient Python wrapper, 8+ endpoints (/status, /api/gui, /api/ask, /api/gui/mma_status, /api/performance, /api/comms, /api/diagnostics), Remote Confirmation Protocol via /api/ask (synchronous blocking HITL), custom_callback action for invoking any registered App method
MCP Client	src/mcp_client.py reference: 45 native tools (File I/O, Python AST, C/C++ AST, Analysis, Network, Runtime, Beads), 3-layer security model (Allowlist Construction, Path Validation, Resolution Gate), dispatch()/async_dispatch() entry points, ExternalMCPManager for external MCP servers (Stdio + SSE), JSON-RPC 2.0 engine, public API, configuration
App Controller	src/app_controller.py reference: headless orchestrator owning AppState and all subsystem managers (PresetManager, PersonaManager, ContextPresetManager, ToolPresetManager, ToolBiasEngine, RAGEngine, HistoryManager, WorkspaceManager, HookServer, HotReloader, PathManager), _predefined_callbacks and _gettable_fields registries for Hook API, SyncEventQueue bridge, preset/persona/context coordination, headless mode
MMA Engine	src/multi_agent_conductor.py + src/dag_engine.py reference: TrackDAG with cycle detection (iterative DFS) and topological sort (Kahn's variant), ExecutionEngine with Auto-Queue / Step Mode state machine, MultiAgentConductor with WorkerPool (configurable concurrency, default 4), mma_exec.py sub-agent invocation for Token Firewall, parse_plan_md utility, Beads mode delegation
Data Models	src/models.py reference: centralized data model registry using pydantic + dataclasses, model categories (Core, AI, Preset, Persona, Context, MMA, UI State, Logging, Hook, Workspace, RAG), AGENT_TOOL_NAMES canonical 45-tool list, PROVIDERS constant, parse_plan_md utility, validation patterns, SDM tags, serialization strategies (TOML, JSON-L)
Discussions	The Discussion system: 23-operation matrix A1-A7 (per-entry) + B1-B11 (discussion-level) + C1-C5 (undo/redo), Take naming convention (<base>_take_<n>), branching at any entry (project_manager.branch_discussion), promotion to top-level (project_manager.promote_take), user-managed role list (app.disc_roles), per-role filter linked to MMA persona focus, _disc_entries_lock thread-safety contract, Hook API session endpoints
State Lifecycle	Undo/redo via HistoryManager + UISnapshot (13 captured fields, 100-snapshot capacity, debounced change detection at render frame), reset flow (_handle_reset_session — clears 30+ fields, replaces project, preserves active_project_path per the 2026-06-08 regression fix), App.__getattr__/__setattr__ state delegation to Controller, 4-thread access pattern with 7 lock-protected regions, hot-reload integration
Context Aggregation	The aggregate.py (518-line) pipeline: 3 aggregation strategies (auto/summarize/full), 7 per-file view modes (full/summary/skeleton/outline/masked/custom/none), full FileItem schema (9 fields + __post_init__ normalizer), ContextPreset schema and ContextPresetManager, Tier 3 worker variant (build_tier3_context with FuzzyAnchor re-resolution and focus-file handling), force_full/auto_aggregate short-circuits, output file numbering, cache strategy (static prefix + dynamic history)

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Legacy MMA Reference (Deprecated)

These documents are preserved for historical context. They describe a pre-Feb 2026 architecture and may not reflect current implementation. Prefer the guides above.

• MMA_Support Overview
• MMA_Support Architecture Recommendation
• MMA_Support Data Pipelines and Config
• MMA_Support Final Analysis Report
• MMA_Support Implementation Tracks
• MMA_Support Orchestrator Engine
• MMA_Support Tier 1 Orchestrator
• MMA_Support Tier 2 Tech Lead
• MMA_Support Tier 3 Workers
• MMA_Support Tier 4 Utility
• MMA_Support Original Discussion
• MMA_Support mma_tiered_orchestrator_skill

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GUI Panels

Context Hub

The primary panel for project and file management.

• Project Selector: Switch between <project>.toml configurations. Changing projects swaps the active file list, discussion history, and settings.
• Git Directory: Path to the repository for commit tracking and git operations.
• Main Context File: Optional primary context document for the project.
• Output Dir: Directory where generated markdown files are written.
• Word-Wrap Toggle: Dynamically swaps text rendering in large read-only panels between unwrapped (code formatting) and wrapped (prose).
• Summary Only: When enabled, sends file structure summaries instead of full content to reduce token usage.
• Auto-Scroll Comms/Tool History: Automatically scrolls to the bottom when new entries arrive.

Files & Media Panel

Controls what context is compiled and sent to the AI.

• Base Dir: Root directory for path resolution and MCP tool constraints.
• Paths: Explicit files or wildcard globs (src/**/*.py).
• File Flags:
  • Auto-Aggregate: Include in context compilation.
  • Force Full: Bypass summary-only mode for this file.
• Cache Indicator: Green dot (●) indicates file is in provider's context cache.

Discussion Hub

Manages conversational branches to prevent context poisoning across tasks.

• Discussions Sub-Menu: Create separate timelines for different tasks (e.g., "Refactoring Auth" vs. "Adding API Endpoints").
• Git Commit Tracking: "Update Commit" reads HEAD from the project's git directory and stamps the discussion.
• Entry Management: Each turn has a Role (User, AI, System, Context, Tool, Vendor API). Toggle between Read/Edit modes, collapse entries, or open in the Global Text Viewer via [+ Max].
• Auto-Add: When toggled, Message panel sends and Response panel returns are automatically appended to the current discussion.
• Truncate History: Reduces history to N most recent User/AI pairs.

AI Settings Panel

• Provider: Switch between API backends (Gemini, Anthropic, DeepSeek, Gemini CLI, MiniMax).
• Model: Select from available models for the current provider.
• Fetch Models: Queries the active provider for the latest model list.
• Temperature / Max Tokens: Generation parameters.
• History Truncation Limit: Character limit for truncating old tool outputs.

Token Budget Panel

• Current Usage: Real-time token counts (input, output, cache read, cache creation).
• Budget Percentage: Visual indicator of context window utilization.
• Provider-Specific Limits: Anthropic (180K prompt), Gemini (900K input).

Cache Panel

• Gemini Cache Stats: Count, total size, and list of cached files.
• Clear Cache: Forces cache invalidation on next send.

Tool Analytics Panel

• Per-Tool Statistics: Call count, total time, failure count for each tool.
• Session Insights: Burn rate estimation, average latency.

Message & Response Panels

• Message: User input field with auto-expanding height.
• Gen + Send: Compiles markdown context and dispatches to the AI via AsyncEventQueue.
• MD Only: Dry-runs the compiler for context inspection without API cost.
• Response: Read-only output; flashes green on new response.

Operations Hub

• Focus Agent Filter: Show comms/tool history for specific tier (All, Tier 2, Tier 3, Tier 4).
• Comms History: Real-time display of raw API traffic (timestamp, direction, kind, provider, model, payload preview).
• Tool Calls: Sequential log of tool invocations with script/args and result preview.

MMA Dashboard

The 4-tier orchestration control center.

• Track Browser: List of all tracks with status, progress, and actions (Load, Delete).
• Active Track Summary: Color-coded progress bar, ticket status breakdown (Completed, In Progress, Blocked, Todo), ETA estimation.
• Visual Task DAG: Node-based visualization using imgui-node-editor with color-coded states (Ready, Running, Blocked, Done).
• Ticket Queue Management: Bulk operations (Execute, Skip, Block), drag-and-drop reordering, priority assignment.
• Tier Streams: Real-time output from Tier 1/2/3/4 agents.

Tier Stream Panels

Dedicated windows for each MMA tier:

• Tier 1: Strategy: Orchestrator output for epic planning and track initialization.
• Tier 2: Tech Lead: Architectural decisions and ticket generation.
• Tier 3: Workers: Individual worker output streams (one per active ticket).
• Tier 4: QA: Error analysis and diagnostic summaries.

Log Management

• Session Registry: Table of all session logs with metadata (start time, message count, size, whitelist status).
• Star/Unstar: Mark sessions for preservation during pruning.
• Force Prune: Manually trigger aggressive log cleanup.

Diagnostics Panel

• Performance Telemetry: FPS, Frame Time, CPU %, Input Lag with moving averages.
• Detailed Component Timings: Per-panel rendering times with threshold alerts.
• Performance Graphs: Historical plots for selected metrics.

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Configuration Files

config.toml (Global)

[ai]
provider = "gemini"
model = "gemini-2.5-flash-lite"
temperature = 0.0
max_tokens = 8192
history_trunc_limit = 8000
system_prompt = ""

[projects]
active = "path/to/project.toml"
paths = ["path/to/project.toml"]

[gui]
separate_message_panel = false
separate_response_panel = false
separate_tool_calls_panel = false
show_windows = { "Context Hub": true, ... }

[paths]
logs_dir = "logs/sessions"
scripts_dir = "scripts/generated"
conductor_dir = "conductor"

[mma]
max_workers = 4

.toml (Per-Project)

[project]
name = "my_project"
git_dir = "./my_repo"
system_prompt = ""
main_context = ""

[files]
base_dir = "."
paths = ["src/**/*.py"]
tier_assignments = { "src/core.py" = 1 }

[screenshots]
base_dir = "."
paths = []

[output]
output_dir = "./md_gen"

[gemini_cli]
binary_path = "gemini"

[deepseek]
reasoning_effort = "medium"

[agent.tools]
run_powershell = true
read_file = true
list_directory = true
search_files = true
get_file_summary = true
web_search = true
fetch_url = true
py_get_skeleton = true
py_get_code_outline = true
get_file_slice = true
set_file_slice = false
edit_file = false
py_get_definition = true
py_update_definition = false
py_get_signature = true
py_set_signature = false
py_get_class_summary = true
py_get_var_declaration = true
py_set_var_declaration = false
get_git_diff = true
py_find_usages = true
py_get_imports = true
py_check_syntax = true
py_get_hierarchy = true
py_get_docstring = true
get_tree = true
get_ui_performance = true

[mma]
epic = ""
active_track_id = ""
tracks = []

credentials.toml

[gemini]
api_key = "YOUR_KEY"

[anthropic]
api_key = "YOUR_KEY"

[deepseek]
api_key = "YOUR_KEY"

[minimax]
api_key = "YOUR_KEY"

mcp_env.toml (Optional)

[path]
prepend = ["C:/custom/bin"]

[env]
MY_VAR = "some_value"
EXPANDED = "${HOME}/subdir"

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Environment Variables

Variable	Purpose
SLOP_CONFIG	Override path to config.toml
SLOP_CREDENTIALS	Override path to credentials.toml
SLOP_MCP_ENV	Override path to mcp_env.toml
SLOP_TEST_HOOKS	Set to "1" to enable test hooks
SLOP_LOGS_DIR	Override logs directory
SLOP_SCRIPTS_DIR	Override generated scripts directory
SLOP_CONDUCTOR_DIR	Override conductor directory
GEMINI_CLI_HOOK_CONTEXT	Set by bridge scripts to bypass HITL for sub-agents
CLAUDE_CLI_HOOK_CONTEXT	Set by bridge scripts to bypass HITL for sub-agents

---

Exit Codes

Code	Meaning
0	Normal exit
1	General error
2	Configuration error
3	API error
4	Test failure

---

File Layout

manual_slop/
├── conductor/              # Conductor system
│   ├── tracks/             # Track directories
│   │   └── <track_id>/     # Per-track files
│   │       ├── spec.md
│   │       ├── plan.md
│   │       ├── metadata.json
│   │       └── state.toml
│   ├── archive/            # Completed tracks
│   ├── product.md          # Product definition
│   ├── product-guidelines.md
│   ├── tech-stack.md
│   ├── workflow.md
│   ├── index.md
│   └── edit_workflow.md
├── docs/                   # Deep-dive documentation (24 guides + specs/plans)
│   ├── guide_architecture.md
│   ├── guide_meta_boundary.md
│   ├── guide_tools.md
│   ├── guide_mma.md
│   ├── guide_simulations.md
│   ├── guide_context_curation.md
│   ├── guide_shaders_and_window.md
│   ├── guide_rag.md
│   ├── guide_beads.md
│   ├── guide_hot_reload.md
│   ├── guide_personas.md
│   ├── guide_nerv_theme.md
│   ├── guide_workspace_profiles.md
│   ├── guide_command_palette.md
│   ├── guide_themes.md
│   ├── guide_testing.md
│   ├── Readme.md
│   ├── MMA_Support/        # Legacy MMA reference (deprecated)
│   ├── reports/            # Phase 5 reports
│   └── superpowers/        # Specs and plans for design work
├── src/                    # Core implementation (53 modules)
│   ├── gui_2.py            # Primary ImGui interface
│   ├── app_controller.py   # Headless controller
│   ├── ai_client.py        # Multi-provider LLM (Gemini, Anthropic, DeepSeek, MiniMax)
│   ├── mcp_client.py       # 45 MCP tools with 3-layer security
│   ├── api_hooks.py        # HookServer REST API on :8999
│   ├── api_hook_client.py  # Python client for the Hook API
│   ├── multi_agent_conductor.py  # ConductorEngine
│   ├── dag_engine.py       # TrackDAG + ExecutionEngine
│   ├── models.py           # Ticket, Track, WorkerContext, etc.
│   ├── events.py           # EventEmitter, SyncEventQueue
│   ├── project_manager.py  # TOML persistence, discussion management
│   ├── session_logger.py   # JSON-L + markdown audit trails
│   ├── rag_engine.py       # RAG (ChromaDB + embedding providers)
│   ├── beads_client.py     # Beads/Dolt issue tracking client
│   ├── hot_reloader.py     # State-preserving module reloader
│   ├── personas.py         # Unified agent profile manager
│   ├── presets.py          # System prompt preset manager
│   ├── context_presets.py  # Context composition preset manager
│   ├── tool_presets.py     # Tool preset manager
│   ├── tool_bias.py        # Tool bias engine
│   ├── command_palette.py  # Command palette + fuzzy matcher
│   ├── commands.py         # 32 registered commands
│   ├── workspace_manager.py # Workspace profile save/load
│   ├── theme_2.py          # Theme system (palette/font/etc.)
│   ├── theme_nerv.py       # NERV Tactical Console theme
│   ├── theme_nerv_fx.py    # NERV FX (scanlines, flicker, alert)
│   ├── shell_runner.py     # PowerShell execution
│   ├── file_cache.py       # ASTParser (tree-sitter)
│   ├── summarize.py        # Heuristic file summaries
│   ├── outline_tool.py     # Hierarchical code outline
│   ├── fuzzy_anchor.py     # Fuzzy anchor slice algorithm
│   ├── history.py          # Undo/redo HistoryManager
│   ├── imgui_scopes.py     # ImGui context managers
│   ├── performance_monitor.py  # FPS/CPU tracking
│   ├── log_registry.py     # Session metadata
│   ├── log_pruner.py       # Automated log cleanup
│   ├── paths.py            # Centralized path resolution
│   ├── cost_tracker.py     # Token cost estimation
│   ├── gemini_cli_adapter.py  # CLI subprocess adapter
│   ├── mma_prompts.py      # Tier-specific system prompts
│   ├── summary_cache.py    # SHA256-keyed summary LRU cache
│   ├── markdown_helper.py  # Markdown rendering helpers
│   ├── patch_modal.py      # Patch approval modal
│   ├── diff_viewer.py      # Diff rendering
│   ├── external_editor.py  # External editor integration
│   ├── orchestrator_pm.py  # Orchestrator project manager
│   ├── conductor_tech_lead.py  # Tier 2 ticket generation
│   ├── synthesis_formatter.py  # Multi-take synthesis
│   ├── thinking_parser.py  # AI thinking-trace extraction
│   └── __init__.py
├── simulation/             # Test simulations
│   ├── sim_base.py         # BaseSimulation class
│   ├── workflow_sim.py     # WorkflowSimulator
│   ├── user_agent.py       # UserSimAgent
│   ├── sim_context.py      # ContextSimulation
│   ├── sim_execution.py    # ExecutionSimulation
│   ├── sim_ai_settings.py  # AISettingsSimulation
│   └── sim_tools.py        # ToolsSimulation
├── tests/                  # Test suite (251 files)
│   ├── conftest.py         # Fixtures (live_gui, isolate_workspace, etc.)
│   ├── mock_gemini_cli.py   # Mock provider for integration tests
│   ├── test_*.py           # Unit tests
│   ├── *_sim.py            # Integration tests using live_gui
│   ├── test_clean_install.py  # Opt-in: clones repo and verifies hooks
│   ├── test_docker_build.py   # Opt-in: builds Docker image
│   ├── artifacts/          # Git-ignored; test outputs
│   └── logs/               # Git-ignored; live_gui log files
├── scripts/                # Utility scripts
│   ├── generated/          # AI-generated scripts
│   ├── check_test_toml_paths.py  # Audit script (CI gate)
│   ├── docker_build.sh
│   └── docker_run.sh
├── sloppy.py               # Main entry point
├── config.toml             # Global configuration
├── manual_slop.toml        # Active project config (current)
└── credentials.toml        # API keys (gitignored)