feat(conductor): Consolidate MMA implementation into single multi-phase track and draft Agent Skill

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# MMA Core Engine Implementation
This track implements the 5 Core Epics defined during the MMA Architecture Evaluation.
### Navigation
- [Specification](./spec.md)
- [Implementation Plan](./plan.md)
- [Original Architecture Proposal / Meta-Track](../mma_implementation_20260224/index.md)

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{
"id": "mma_core_engine_20260224",
"title": "MMA Core Engine Implementation",
"status": "planning",
"created_at": "2026-02-24T00:00:00.000000"
}

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# Implementation Plan: MMA Core Engine Implementation
## Phase 1: Track 1 - The Memory Foundations (AST Parser)
- [ ] Task: Dependency Setup
- [ ] Add `tree-sitter` and `tree-sitter-python` to `pyproject.toml` / `requirements.txt`
- [ ] Task: Core Parser Class
- [ ] Create `ASTParser` in `file_cache.py`
- [ ] Task: Skeleton View Extraction
- [ ] Write query to extract `function_definition` and `class_definition`
- [ ] Replace bodies with `pass`, keep type hints and signatures
- [ ] Task: Curated View Extraction
- [ ] Keep class structures, module docstrings
- [ ] Preserve `@core_logic` or `# [HOT]` function bodies, hide others
## Phase 2: Track 2 - State Machine & Data Structures
- [ ] Task: The Dataclasses
- [ ] Create `models.py` defining `Ticket` and `Track`
- [ ] Task: Worker Context Definition
- [ ] Define `WorkerContext` holding `Ticket` ID, model config, and ephemeral messages
- [ ] Task: State Mutator Methods
- [ ] Implement `ticket.mark_blocked()`, `ticket.mark_complete()`, `track.get_executable_tickets()`
## Phase 3: Track 3 - The Linear Orchestrator & Execution Clutch
- [ ] Task: The Engine Core
- [ ] Create `multi_agent_conductor.py` containing `ConductorEngine` and `run_worker_lifecycle`
- [ ] Task: Context Injection
- [ ] Format context strings using `file_cache.py` target AST views
- [ ] Task: The HITL Execution Clutch
- [ ] Before executing `write_file`/`shell_runner.py` tools in step-mode, prompt user for confirmation
- [ ] Provide functionality to mutate the history JSON before resuming execution
## Phase 4: Track 4 - Tier 4 QA Interception
- [ ] Task: The Interceptor Loop
- [ ] Catch `subprocess.run()` execution errors inside `shell_runner.py`
- [ ] Task: Tier 4 Instantiation
- [ ] Make a secondary API call to `default_cheap` model passing `stderr` and snippet
- [ ] Task: Payload Formatting
- [ ] Inject the 20-word fix summary into the Tier 3 worker history
## Phase 5: Track 5 - UI Decoupling & Tier 1/2 Routing (The Final Boss)
- [ ] Task: The Event Bus
- [ ] Implement an `asyncio.Queue` linking GUI actions to the backend engine
- [ ] Task: Tier 1 & 2 System Prompts
- [ ] Create structured system prompts for Epic routing and Ticket creation
- [ ] Task: The Dispatcher Loop
- [ ] Read Tier 2 JSON flat-lists, construct Tickets, execute Stub resolution paths
- [ ] Task: UI Component Update
- [ ] Refactor `gui_2.py` to push `UserRequestEvent` instead of blocking on API generation

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# Specification: MMA Core Engine Implementation
## 1. Overview
This track consolidates the implementation of the 4-Tier Hierarchical Multi-Model Architecture into the `manual_slop` codebase. The architecture transitions the current monolithic single-agent loop into a compartmentalized, token-efficient, and fully debuggable state machine.
## 2. Functional Requirements
### Phase 1: The Memory Foundations (AST Parser)
- Integrate `tree-sitter` and `tree-sitter-python` into `pyproject.toml` / `requirements.txt`.
- Implement `ASTParser` in `file_cache.py` to extract strict memory views (Skeleton View, Curated View).
- Strip function bodies from dependencies while preserving `@core_logic` or `# [HOT]` logic for the target modules.
### Phase 2: State Machine & Data Structures
- Create `models.py` incorporating strict Pydantic/Dataclass schemas for `Ticket`, `Track`, and `WorkerContext`.
- Enforce rigid state mutators governing dependencies between tickets (e.g., locking execution until a stub generation ticket completes).
### Phase 3: The Linear Orchestrator & Execution Clutch
- Build `multi_agent_conductor.py` and a `ConductorEngine` dispatcher loop.
- Embed the "Execution Clutch" allowing developers to pause, review, and manually rewrite payloads (JSON history mutation) before applying changes to the local filesystem.
### Phase 4: Tier 4 QA Interception
- Augment `shell_runner.py` with try/except wrappers capturing process errors (`stderr`).
- Rather than feeding raw stack traces to an expensive model, instantly forward them to a stateless `default_cheap` sub-agent for a 20-word summarization that is subsequently injected into the primary worker's context.
### Phase 5: UI Decoupling & Tier 1/2 Routing (The Final Boss)
- Disconnect `gui_2.py` from direct LLM inference requests.
- Bind the GUI to a synchronous or `asyncio.Queue` Event Bus managed by the Orchestrator, allowing dynamic tracking of parallel worker executions without thread-locking the interface.
## 3. Acceptance Criteria
- [ ] A 1000-line script can be successfully parsed into a 100-line AST Skeleton.
- [ ] Tickets properly block and resolve depending on stub-generation dependencies.
- [ ] Shell errors are compressed into >50-token hints using the cheap utility model.
- [ ] The GUI remains responsive during multi-model generation phases.
## 4. Meta-Track Reference
For the original rationale, API formatting recommendations (e.g., Godot ECS schemas vs Nested JSON), and strict token firewall workflows, refer back to the architectural planning meta-track: `conductor/tracks/mma_implementation_20260224/`.

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{
"id": "mma_state_machine_data_structures_20260224",
"title": "State Machine & Data Structures",
"status": "planning",
"created_at": "2026-02-24T22:44:11.756941"
}

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# Implementation Plan: State Machine & Data Structures
- [ ] Task: Create \ ests/test_models.py\.
- [ ] Task: Write failing tests that instantiate \Track\, \Ticket\, and \WorkerContext\ with various valid and invalid schemas.
- [ ] Task: Write tests that assert state transitions (e.g., from \pending\ to \locked\, from \step_paused\ to \completed\) correctly update internal flags and dependencies.
- [ ] Task: **Red Phase:** Tests fail because \models.py\ classes are undefined or lack transition methods.
- [ ] Task: **Green Phase:** Implement the dataclasses and state mutators.

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# Specification: State Machine & Data Structures
## Goal
Define the rigid Python objects (Pydantic/Dataclasses) that AI agents will pass to each other, enforcing structured data over loose chat strings.

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{
"id": "mma_the_linear_orchestrator_execution_clutch_20260224",
"title": "The Linear Orchestrator & Execution Clutch",
"status": "planning",
"created_at": "2026-02-24T22:44:11.757962"
}

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# Implementation Plan: The Linear Orchestrator & Execution Clutch
- [ ] Task: Create \ ests/test_conductor.py\.
- [ ] Task: Write tests that mock the AI client response (e.g., returning a mock tool call like \write_file\).
- [ ] Task: Test that \
- [ ] Task: Test that execution pauses (waits for a simulated human signal) when the \ rust_level\ dictates.
- [ ] Task: **Red Phase:** Failure occurs because \multi_agent_conductor.py\ lacks the lifecycle execution loop.
- [ ] Task: **Green Phase:** Implement the \ConductorEngine\ core execution block.

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# Specification: The Linear Orchestrator & Execution Clutch
## Goal
Build the synchronous, debuggable core loop that runs a single Tier 3 Worker and pauses for human approval.

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{
"id": "mma_the_memory_foundations_ast_parser_20260224",
"title": "The Memory Foundations (AST Parser)",
"status": "planning",
"created_at": "2026-02-24T22:44:11.755925"
}

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# Implementation Plan: The Memory Foundations (AST Parser)
- [ ] Task: Create `tests/test_file_cache_ast.py`.
- [ ] Task: Define mock Python source files containing various structures (classes, functions, docstrings, `@core_logic` decorators, `# [HOT]` comments).
- [ ] Task: Write failing tests that instantiate `ASTParser` and assert that `get_skeleton_view()` and `get_curated_view()` return the precisely filtered strings.
- [ ] Task: **Red Phase:** Ensure tests fail because `ASTParser` does not exist.
- [ ] Task: **Green Phase:** Implement the tree-sitter logic iteratively until strings match exactly.

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# Specification: The Memory Foundations (AST Parser)
## Goal
Build the engine that prevents token-bloat by turning massive source files into curated memory views.

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{
"id": "mma_tier_4_qa_interception_20260224",
"title": "Tier 4 QA Interception",
"status": "planning",
"created_at": "2026-02-24T22:44:11.758965"
}

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# Implementation Plan: Tier 4 QA Interception
- [ ] Task: Create \ ests/test_shell_runner.py\.
- [ ] Task: Write tests that mock a local execution failure (e.g., returning a mock 3000-line Python stack trace).
- [ ] Task: Test that the error is intercepted and passed to a mock Tier 4 agent.
- [ ] Task: Test that the output is compressed into a 20-word fix before returning.
- [ ] Task: **Red Phase:** Fails because no interception loop exists in \shell_runner.py\.
- [ ] Task: **Green Phase:** Implement the try/except logic handling \subprocess.run()\ with \

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# Specification: Tier 4 QA Interception
## Goal
Stop error traces from destroying the Worker's token window by routing crashes through a cheap, stateless translator.

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{
"id": "mma_ui_decoupling_tier_1_2_routing_the_final_boss_20260224",
"title": "UI Decoupling & Tier 1/2 Routing (The Final Boss)",
"status": "planning",
"created_at": "2026-02-24T22:44:11.759465"
}

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# Implementation Plan: UI Decoupling & Tier 1/2 Routing (The Final Boss)
- [ ] Task: Create \ ests/test_gui_decoupling.py\.
- [ ] Task: Write tests that instantiate a mocked GUI instance listening to an \syncio.Queue\.
- [ ] Task: Mock pushing \TrackStateUpdated\ and \TicketStarted\ events into the queue and ensure the GUI updates its view state rather than calling LLM endpoints directly.
- [ ] Task: **Red Phase:** Failure occurs because \gui_2.py\ is tightly coupled with \i_client.py\ logic.
- [ ] Task: **Green Phase:** Implement the \AgentBus\ messaging system linking \multi_agent_conductor.py\ to \gui_2.py\.

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# Specification: UI Decoupling & Tier 1/2 Routing (The Final Boss)
## Goal
Bring the whole system online by letting Tier 1 and Tier 2 generate Tickets dynamically, managed via an asynchronous Event Bus.