Captain Obvious

Deletes tests that assert what is already guaranteed — by the compiler, by the mock framework, or by the laws of logic. These tests burn CI time, inflate coverage confidence, and can never catch a regression. They are the signature of AI-generated test suites (empirical studies find test smells in 38–100% of LLM-generated tests).

The heavy lifting is done by two deterministic scripts in scripts/. Your job is orchestration: run them, interpret the report, clean up the residue, and verify nothing broke. Do not hand-scan test files or spawn subagents per file — one script invocation scans the whole project.

Workflow

1. Detect the stack(s)

• TypeScript: a tsconfig.json and *.test.ts / *.spec.ts / __tests__ files.
• Python: test_*.py / *_test.py files (pytest).
• A repo can have both; run both detectors.

2. Safety first

The fix step edits test files in place. Both scripts enforce this themselves: --fix exits 2 unless the target is a git repository with a clean working tree (untracked files are fine). If it refuses, stash or commit rather than reaching for --force — --force removes the only undo path there is (git checkout -- <files>), so use it only when the user has explicitly accepted that.

Trust boundary: scanning executes the project's own toolchain. mypy loads [tool.mypy] plugins from the repo's config as in-process Python; --mypy "uv run mypy" / "poetry run mypy" resolve (and can run) the repo's dependencies; the TS side loads the repo's own typescript package. Run the scan only on repositories you would be willing to run mypy/tsc in yourself.

Note: when installed as a plugin, a write-time PreToolUse hook may also be active — if a test-file Write/Edit is denied with a "captain-obvious:" reason during cleanup rewrites, fix the flagged assertions instead of re-trying the same content (see references/prevention.md). Both scanners also support --file <path> [--stdin] for a syntactic-only single-file scan (JSON to stdout; no mypy/tsc, no side effects).

3. Scan (report-only)

node <skill-dir>/scripts/captain_obvious_ts.mjs --project <repo> --json /tmp/co-ts.json
python3 <skill-dir>/scripts/captain_obvious_py.py --path <repo> --json /tmp/co-py.json

• The Python detector shells out to mypy for the type-guaranteed category. Use the project's own environment: pass --mypy "uv run mypy" for uv projects, --mypy "poetry run mypy" for poetry, etc. If mypy isn't available it degrades gracefully to the syntactic categories.
• Note: the mypy pass briefly writes _cap_obv_shadow_* copies next to test files (removed when the run ends) — so a "report-only" scan does touch the working tree. Pass --no-types for a strictly read-only scan; if the tree is not writable the scan degrades to syntactic categories and says so.
• The TS detector resolves the project's own typescript package; without a tsconfig it degrades to syntactic categories.
• If the project already produces coverage (or you can cheaply run it), pass --coverage <file> (lcov / istanbul coverage-final.json / coverage.py coverage json). This is the dynamic half of the ICSE'19 rotten-green analysis: a conditional-assert whose line never ran is promoted to proven rotten, and one that did run is dropped as a confirmed false positive. It turns the noisiest advisory category into a trustworthy one — use it whenever coverage is available.

Show the user the summary table and the findings before deleting anything.

4. Understand the two levels

• proven — cannot fail, by construction. The scripts guard the known escape hatches (any/unknown, as casts, !, index signatures, unchecked index access, structural instanceof, custom assertion helpers). Safe to auto-delete.
• advisory — almost certainly useless but not provable (assertion-free tests, structural instanceof, mock-echo variants, index-signature-backed checks, rotten-green conditional asserts, unawaited async assertions). The script never auto-deletes these, but it records exactly why each is uncertain, plus a deletable hint (aggressive = usually a deletion, report-only = usually needs a rewrite). That reason is a question you are equipped to answer against the surrounding code — so advisories are adjudicated by you (step 6), not dumped on the user.

See references/detectors.md for the full category catalog and the reasoning behind each guard.

5. Fix the proven tier (deterministic)

node <skill-dir>/scripts/captain_obvious_ts.mjs --project <repo> --fix
python3 <skill-dir>/scripts/captain_obvious_py.py --path <repo> --fix

Plain --fix removes only the proven findings — no judgment required, no LLM. This is the safe deterministic core; run it first.

6. Adjudicate the advisory tier (you decide, then confirm)

Advisories are the cases determinism can't settle — and that's your job, not a report line for the user. Do not just forward the list. For each advisory finding:

1. Read the test and the code it exercises. The finding's reason field is a pointed question — e.g. "structural instanceof — a shaped non-instance could sneak in" → check whether anything actually constructs a non-instance of that type; "mock-echo, indirect" → check whether a real code path runs between stub and assert.
2. Decide one of: delete (the doubt doesn't hold — it really is useless), keep (the doubt holds — it's a real check), or rewrite (the intent is valid but the assertion is broken). Rewrite is the advisory tier's real value: fix the unawaited .rejects (await it), narrow a pytest.raises(Exception) to the specific type, repair a rotten-green conditional-assert so it actually runs. Note no-assert findings are smoke tests — legitimate by design (ICSE'19); default to keep unless the test clearly meant to assert something and forgot.
3. Propose before acting. Present a compact per-item table — finding, verdict, one-line rationale, and the exact edit for rewrites — and apply only what the user approves. Never auto-delete or auto-rewrite an advisory.

For a large advisory set, delegate the per-item code reads to a Sonnet subagent (batch the findings; have it return verdict + rationale + proposed edit per item) and keep the final proposal/synthesis here — don't burn the main loop reading files one by one. The proven tier is never handed to a subagent; it's already decided.

7. Clean the residue

The scripts delete whole test blocks or individual assertion lines. That can leave behind: unused imports/variables (noUnusedLocals will flag them), empty describe() blocks, empty test classes, orphaned fixtures/mocks. Fix those by hand — the typechecker output is your worklist.

8. Verify

Run the project's typecheck AND full test suite (tsc --noEmit + the test command from package.json / pytest). Everything must pass with the same result as before (minus the deleted tests). If anything regresses, git checkout -- <files> and report what happened instead of pushing through.

9. Report

Tell the user: proven tests/assertions removed (per-category counts, lines saved), the advisory verdicts you applied (deleted / rewritten, with the fix), and anything you chose to keep with the reason the doubt held — that last group is the tool earning trust, not failing.

What NOT to flag (the scripts already know, but so should you)

• toBeDefined() on .find() / Map.get() results — the type is T | undefined, the check is real.
• Enum/constant contract locks (expect(ExitCode.OK).toBe(0)) — they catch renumbering.
• Assertions on values read from files/APIs at test time — real regression tests.
• Tests asserting via custom helpers (expectAllow(x), self._check(...)).
• "Must not raise" contract tests for fail-open code paths.

When NOT to run this at all

• Mid red-green. During TDD a test is supposed to be failing, and a freshly-written test may not have its assertion yet. This is post-hoc cleanup — run it once the suite is green, never between red and green.
• On a branch under review. Scan (--json) is fine; --fix is not. Rewriting test files while a reviewer or a merge gate is reading the diff invalidates what they reviewed.
• As a coverage or CI-time optimizer. It deletes tests that cannot fail, which is a correctness argument, not a speed one. "CI is slow" is not a reason to reach for it — a slow suite full of real tests stays slow.