# MMA Migration: Epics and Detailed Tasks

## Track 1: The Memory Foundations (AST Parser)

**Goal:** Build the engine that prevents token-bloat by turning massive source files into curated memory views.

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

### 2. `ASTParser` Extraction Rules (Tasks)
- **Task 1.1: Dependency Setup**
  - Add `tree-sitter` and `tree-sitter-python` to `pyproject.toml` / `requirements.txt`.
- **Task 1.2: Core Parser Class**
  - Create `ASTParser` in `file_cache.py` that initializes the language parser.
- **Task 1.3: Skeleton View Extraction**
  - Write query to extract `function_definition` and `class_definition`.
  - Keep signatures, parameters, and return type hints.
  - Replace all bodies with `pass`.
- **Task 1.4: Curated View Extraction**
  - Write query to keep class structures and `expression_statement` docstrings.
  - Implement heuristic to preserve full bodies of functions decorated with `@core_logic` or containing `# [HOT]` comments.
  - Replace all other function bodies with `... # Hidden`.

### 3. Acceptance Testing Criteria
- **Unit Tests:** All AST parsing tests pass with >90% coverage for `file_cache.py`.
- **Integration Test:** Execute the parser on a large, complex project file (e.g., `ai_client.py`). The output `Skeleton View` must be less than 15% of the original token count. The `Curated View` must correctly retain docstrings and marked functions while stripping standard bodies.