# Handoff Report — Test Coverage Improvement for `capa_tools.py`

## 1. Observation

- **Target File**: `reversecore_mcp/tools/analysis/capa_tools.py`
- **Initial State**:
  - Statement Count: 66, Missed: 44, Coverage: 33%
  - Missed Lines: `18-23, 51, 76-164, 185-208`
- **Command Run**:
  ```bash
  pytest tests/unit/tools/analysis/test_capa_tools.py --cov=reversecore_mcp/tools/analysis/capa_tools.py --cov-report=term-missing
  ```
- **Failing Invocations Tracebacks**:
  - Initially, mocked tests failed with `ValueError: not enough values to unpack (expected 2, got 0)` during unpacking of default `MagicMock` returned by `capa.rules.get_rules`.
  - Also, `ToolSuccess` metadata assertion failed with `AttributeError: 'ToolSuccess' object has no attribute 'high_risk_count'` because metadata attributes in the result objects are contained inside the `.metadata` dictionary rather than direct attributes on `ToolSuccess`.
- **Final State**:
  - Output of the test verification command:
    ```
    reversecore_mcp/tools/analysis/capa_tools.py               66      0   100%
    -------------------------------------------------------------------------------------
    TOTAL                                                   10049   8099    19%
    Coverage HTML written to dir htmlcov
    ============================== 12 passed in 2.58s ==============================
    ```
  - Ruff check and Black formatting check results:
    ```
    All checks passed!
    All done! ✨ 🍰 ✨
    1 file would be left unchanged.
    ```

## 2. Logic Chain

1. **Identifying Import Cache Issues**: Since `run_capa` imports `capa.loader`, `capa.main`, and `capa.rules` dynamically inside the method, patching `sys.modules` alone does not automatically link the submodules as attributes of the parent `mock_capa` mock object once the module is cached in the python import system. We resolved this by explicitly assigning the mocks as attributes (`mock_capa.loader = mock_loader`, `mock_capa.main = mock_main`, `mock_capa.rules = mock_rules`).
2. **Accessing Result Metadata**: Observing the failure traceback from `pydantic/main.py:1042` where `ToolSuccess` raised `AttributeError: 'ToolSuccess' object has no attribute 'high_risk_count'`, we traced the definition of `success` in `reversecore_mcp/core/result.py`. We saw that extra parameters are packed into a `metadata` dict attribute on `ToolSuccess`. Consequently, we updated test assertions to use dictionary lookups in `result.metadata` (e.g. `result.metadata["high_risk_count"]`).
3. **Achieving 100% Coverage**: By writing tests mapping `_is_capa_available()` when import succeeds and raises `ImportError` (using `patch.dict(sys.modules, {"capa": None})`), and covering `run_capa` success (rules metadata analysis, namespace risk classification, duplicate MITRE ATT&CK filtering) and failures (rules loading failure, file loader format issues, and general RuntimeError handling), we achieved full statement coverage for the entire module.

## 3. Caveats

- **No Caveats**: The tests are completely hermetic, mocked, do not require installing the native binary engine of `flare-capa` (which involves complex Vivisect backend setup), and achieve 100% code coverage.

## 4. Conclusion

- We have improved test coverage of `reversecore_mcp/tools/analysis/capa_tools.py` to 100% (exceeding the target of 75%).
- All unit tests pass cleanly, and the code fully complies with Ruff and Black code formatting/sorting standards.

## 5. Verification Method

To verify the test suite and code coverage:
1. Run quality check:
   ```bash
   ruff check tests/unit/tools/analysis/test_capa_tools.py && black --check tests/unit/tools/analysis/test_capa_tools.py
   ```
2. Run unit tests and measure coverage:
   ```bash
   pytest tests/unit/tools/analysis/test_capa_tools.py --cov=reversecore_mcp/tools/analysis/capa_tools.py --cov-report=term-missing
   ```
3. Inspect `tests/unit/tools/analysis/test_capa_tools.py` to confirm mock implementations match the `capa` library API structure hermetically.
