### expert_build/cli.py
VERDICT: PASS
CORRECTNESS: VALID
SPEC_COMPLIANCE: N/A
ISSUE_COMPLIANCE: N/A
BELIEF_COMPLIANCE: CONSISTENT
TEST_COVERAGE: COVERED
INTEGRATION: WIRED
REASONING: The CLI changes correctly integrate the new `index-sources` command. It uses the established `_lazy` loading pattern for subcommands, ensuring fast startup. The argument definitions are clear and provide sensible defaults.
---

### expert_build/index_sources.py
VERDICT: CONCERN
CORRECTNESS: VALID
SPEC_COMPLIANCE: N/A
ISSUE_COMPLIANCE: N/A
BELIEF_COMPLIANCE: CONSISTENT
TEST_COVERAGE: COVERED
INTEGRATION: WIRED
REASONING: 1. **Performance Bottleneck**: In `_insert_chunks`, the FTS5 index is rebuilt from scratch (`INSERT INTO chunks_fts(chunks_fts) VALUES('rebuild')`) for *every file* being indexed. Since `_insert_chunks` is called inside the file loop in `cmd_index_sources`, this results in O(N^2) complexity relative to the total number of chunks. For large document sets, this will be extremely slow. The rebuild should be moved outside the loop or replaced with incremental FTS inserts. 2. **Path Robustness**: Already-indexed files are tracked using `str(source_path)`. This check is sensitive to whether the user provided a relative or absolute path to `--input-dir` and the current working directory. Normalizing paths (e.g., via `.resolve()`) would make this more robust. 3. **Multiple Commits**: `_insert_chunks` calls `conn.commit()` twice per file, which adds unnecessary overhead.
---

### tests/test_index_sources.py
VERDICT: PASS
CORRECTNESS: VALID
SPEC_COMPLIANCE: N/A
ISSUE_COMPLIANCE: N/A
BELIEF_COMPLIANCE: CONSISTENT
TEST_COVERAGE: COVERED
INTEGRATION: WIRED
REASONING: The tests are comprehensive and well-structured. They verify the database schema, handle various file types (Markdown, Python), test the recursive/non-recursive globbing logic, and confirm that the FTS5 search functionality is actually working. The use of `tmp_path` and `monkeypatch.chdir` ensures tests are isolated and don't pollute the local environment.
---

### SELF_REVIEW
LIMITATIONS: I had access to the full bodies of the primary modified functions and the entire new test file. While I did not see the full `expert_build/chunk_docs.py`, the observations provided the specific implementation of the chunking functions used, which was sufficient for verifying integration and logic.
---

### FEATURE_REQUESTS
- It would be useful to have a "Performance Analysis" observation type that flags potential O(N^2) patterns in loops involving I/O or database operations.
---
