Good. Now here's my review:

---

### ftl_code_expert/cli.py:_build_negative_issue_body
VERDICT: PASS
CORRECTNESS: VALID
SPEC_COMPLIANCE: N/A
ISSUE_COMPLIANCE: N/A
BELIEF_COMPLIANCE: N/A
TEST_COVERAGE: UNTESTED
INTEGRATION: WIRED
REASONING: Clean parallel to `_build_issue_body` for negative beliefs. Correctly references the belief ID in the retract command. Simpler body is appropriate since negative beliefs don't have gated dependents. Integrated via `file_issues` command.
---

### ftl_code_expert/cli.py:_extract_source_file
VERDICT: CONCERN
CORRECTNESS: QUESTIONABLE
SPEC_COMPLIANCE: N/A
ISSUE_COMPLIANCE: N/A
BELIEF_COMPLIANCE: N/A
TEST_COVERAGE: UNTESTED
INTEGRATION: WIRED
REASONING: The function reads the first 5 lines of an entry file looking for `# File: `. Two concerns: (1) No path traversal guard — if `entry_path` (from `node.get("source")`) contains `../` segments, `Path(base) / entry_path` could escape the project directory. The data is internal but defense-in-depth would check `resolve()` stays within `base`. (2) If the header format ever changes (e.g. `## File:` or `# Source:`), this silently returns None and grep fallback kicks in — acceptable degradation.
---

### ftl_code_expert/cli.py:_gather_confirmation_context
VERDICT: CONCERN
CORRECTNESS: QUESTIONABLE
SPEC_COMPLIANCE: N/A
ISSUE_COMPLIANCE: N/A
BELIEF_COMPLIANCE: N/A
TEST_COVERAGE: UNTESTED
INTEGRATION: WIRED
REASONING: Three concerns: (1) `read_file` is called with `max_lines=300` but the function signature defaults to 200 — this is fine since it accepts the parameter, just noting the override. (2) The grep term extraction `terms = [t for t in bid.replace("-", " ").split() if len(t) > 3][:3]` derives search terms from belief IDs, which are slugified identifiers. This will produce useful terms for IDs like `sql-injection-user-input` but poor ones for IDs like `issue-1234-fix`. No fallback uses the belief *text* for grep, which would often be more informative. (3) The `grep` call doesn't pass a `glob` parameter, so it defaults to `"*.py"` — this silently excludes non-Python files (JS, TS, Go, etc.) that may be relevant in polyglot repos.
---

### ftl_code_expert/cli.py:_parse_confirmation
VERDICT: PASS
CORRECTNESS: VALID
SPEC_COMPLIANCE: N/A
ISSUE_COMPLIANCE: N/A
BELIEF_COMPLIANCE: N/A
TEST_COVERAGE: UNTESTED
INTEGRATION: WIRED
REASONING: Regex `r"\{[^{}]*\}"` correctly extracts a flat JSON object (no nesting needed for `{id: bool}` map). Returns empty dict on failure, and callers treat missing keys as `True` (default to filing), so parse failures fail open. Sound approach.
---

### ftl_code_expert/cli.py:_confirm_beliefs
VERDICT: CONCERN
CORRECTNESS: QUESTIONABLE
SPEC_COMPLIANCE: N/A
ISSUE_COMPLIANCE: N/A
BELIEF_COMPLIANCE: N/A
TEST_COVERAGE: UNTESTED
INTEGRATION: WIRED
REASONING: (1) `asyncio.run()` is called inside a synchronous Click command. This works for CLI invocation but will raise `RuntimeError` if the code is ever called from within an existing event loop (e.g., Jupyter, or if the CLI is embedded in an async framework). The rest of the codebase likely has the same pattern so this is consistent. (2) The fail-open design (on LLM error, include all beliefs) is the right choice — avoids silently dropping legitimate issues. (3) Batch size of 10 is hardcoded; not configurable via CLI but reasonable default. (4) The prompt format is well-structured and unambiguous, with a clear expected output format.
---

### ftl_code_expert/cli.py:_get_negative_beliefs
VERDICT: CONCERN
CORRECTNESS: QUESTIONABLE
SPEC_COMPLIANCE: N/A
ISSUE_COMPLIANCE: N/A
BELIEF_COMPLIANCE: N/A
TEST_COVERAGE: UNTESTED
INTEGRATION: WIRED
REASONING: The regex `r"\s*\[-\]\s+([\w-]+):\s+(.+)"` parses `reasons list-negative` output. Two concerns: (1) This creates a tight coupling to the CLI output format of `reasons list-negative`. If that format changes, the parsing silently fails and falls back to keyword detection — acceptable degradation but could cause confusion if the `reasons` tool is installed but the regex no longer matches (user sees keyword-based results instead of LLM-classified ones with no warning). (2) The `-m model` flag is passed to `reasons list-negative` — this requires the reasons CLI to support that flag. If it doesn't, `returncode != 0` triggers the fallback, which is fine.
---

### ftl_code_expert/cli.py:file_issues (command)
VERDICT: CONCERN
CORRECTNESS: QUESTIONABLE
SPEC_COMPLIANCE: N/A
ISSUE_COMPLIANCE: N/A
BELIEF_COMPLIANCE: N/A
TEST_COVERAGE: UNTESTED
INTEGRATION: WIRED
REASONING: The refactored command correctly unifies gated blockers and negative beliefs into a single candidate pipeline. Key concerns: (1) **Dry-run still runs LLM confirmation** — confirmation is gated on `not skip_confirm and remaining and check_model_available(model)` but NOT on `not dry_run`. This means `--dry-run` incurs LLM costs and latency. This may be intentional (to show accurate preview) but should be documented or reconsidered since dry-run typically implies no external calls. (2) **`_find_existing_issues` parameter names are misleading** — the parameters are named `blocker_ids` and `blocker_texts` in the function signature, but now they receive all candidate IDs (including negatives). The function still works correctly since it's just doing string matching, but the parameter names are now inaccurate. (3) The summary line `len(candidates) - len(remaining) - len(existing)` for "filtered" count is correct mathematically only when `existing` was already subtracted from `remaining`. Since `remaining = [c for c in candidates if c["id"] not in existing]`, the filtered count = `len(candidates) - len(remaining)` already includes existing, so `- len(existing)` double-counts. Wait — let me re-check: `candidates` = all, `remaining` = candidates minus existing minus LLM-rejected. So `len(candidates) - len(remaining)` = existing + LLM-rejected. Then `- len(existing)` = just LLM-rejected. That's what "filtered" means here. The math is correct.
---

### README.md
VERDICT: PASS
CORRECTNESS: VALID
SPEC_COMPLIANCE: N/A
ISSUE_COMPLIANCE: N/A
BELIEF_COMPLIANCE: N/A
TEST_COVERAGE: N/A
INTEGRATION: N/A
REASONING: Documentation accurately reflects the new behavior — negative beliefs, `--skip-confirm`, `--no-negative`, `reasons-gate`/`reasons-negative` labels, and the confirmation step. Clear and consistent with the implementation.
---

### ftl_code_expert/data/SKILL.md
VERDICT: PASS
CORRECTNESS: VALID
SPEC_COMPLIANCE: N/A
ISSUE_COMPLIANCE: N/A
BELIEF_COMPLIANCE: N/A
TEST_COVERAGE: N/A
INTEGRATION: N/A
REASONING: Skill documentation updated to list new flags and add natural language mapping for negative belief queries. Consistent with implementation.
---

## Summary

The change is well-structured and extends `file-issues` in a logical way. The fail-open design for LLM confirmation is the right call. The main concerns are:

1. **No tests at all** — the most significant gap. The new confirmation logic, negative belief parsing, and unified candidate pipeline all have testable units.
2. **`--dry-run` triggers LLM confirmation** — potentially unexpected cost/latency for what users expect to be a no-op preview.
3. **Grep context only searches `*.py` files** — the default glob in `observations.grep` limits confirmation context in polyglot repos.
4. **Grep terms derived from belief IDs, not text** — belief text would often produce better search terms.

None of these are blockers for a tool at this stage, but the dry-run behavior and grep limitations could cause user confusion.

---

### SELF_REVIEW
LIMITATIONS: Could not verify whether `reasons list-negative -m model` is an actual supported invocation of the reasons CLI. Could not see the full `_find_existing_issues` implementation to verify it handles the expanded input correctly. No test files were available to check for regressions. Could not verify the `CONFIRM_PROMPT` template's effectiveness empirically.
---

### FEATURE_REQUESTS
- Include the full body of modified functions (not just diff hunks) so reviewers can see surrounding logic like error handling paths and early returns
- Show the import block to verify all new imports are present
- Include test files alongside implementation changes, or flag when tests are absent for the modified module
---
