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Review

Skill bcanfield/agentic-tech-debt/codex/skills/review

Every shortcut your coding agent takes, saved to your repo as it happens. Fix them when you're ready.

Install
npx -y skills add bcanfield/agentic-tech-debt --skill review

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 9 stars9 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Audit the debt registry, rank survivors by churn × Fowler quadrant, surface a top-N list, then walk paydown on user follow-up. Use when the user asks to review debt, see what to pay down, work through entries, or invokes $review. Stale entries drop with "drop A,B,C".

SKILL.md

3.8 KB, as published. Nobody here has run it

review — audit + (on follow-up) walk paydown

Two modes. First turn: print the audit and stop. On a user follow-up ("fix the top one," "walk these," "do A," "pay some down"), apply the rubric below.

First turn: print the audit

Run the bundled review.py (it lives in this skill's scripts/ directory — reference it with the relative path; Codex resolves it against the skill root):

python3 scripts/review.py

Optional: --top N to surface more than the default 3 candidates.

Re-emit the helper's stdout verbatim in a fenced code block. Codex may collapse long bash outputs — if you don't print it yourself, the user might not see it. Copy exactly: no preamble, no summary, no "want me to fix the top one?" The fenced block preserves column alignment.

Then stop. The user picks the next move.

Paydown mode (only on user follow-up)

Work through requested entries one at a time. Confirm before each fix. Never auto-batch. Never auto-commit.

For each entry, read the registry file, the hotspot, and adjacent tests. Apply this rubric:

  • Already fixed? If the marker/symptom the entry describes no longer appears in the hotspot file, say so and add the entry's letter to the drop list. Don't re-fix.
  • Cold area? Churn=0 since created: and age >90d → propose deferring. ~20% of files generate ~80% of debt-related rework; don't pay down vanity refactors.
  • Prudent-deliberate with payoff_trigger not met? Honor the trigger. Skip with a one-line "trigger not met: <quote>."
  • Fix candidate? Propose the smallest change that resolves the entry. Improvement, not perfection — don't refactor surrounding code.

When you fix

  • Read the repo first. Check the test framework, adjacent tests, the cached feedback commands. Adapt to what exists; don't impose a new style.
  • TDD where tests exist. Write a failing test that pins the deferral, then make it pass. Don't weaken or delete existing tests to make a fix pass.
  • No tests in this area? Surface that and ask: write one, or fix without?
  • Explain why this resolves the entry. Cite the entry's payoff_trigger or body — don't commit code you can't explain.
  • Risky fix? Auth, payments, migrations, public APIs, or ai_authored: true → run a fresh-context review of the diff before suggesting commit. Fresh-context review catches what the writer's motivated reasoning misses.
  • Don't commit. Show the diff. The user runs the gates, drops the entry with drop A, and commits.

Pacing

Aim for 3–10 entries per session — continuous paydown outperforms stop-the-world batches. If the user says "do them all," push back once: unsupervised AI cleanup measurably increases duplicate blocks and short-term churn. If they insist, still one-at-a-time with diffs surfaced.

Speak plainly

The frontmatter uses a research taxonomy (quadrant, category) for ranking and grounding — it is not user-facing vocabulary. When you talk about an entry, describe it in plain words; never say "prudent-inadvertent", "reckless-deliberate", "code_rot", etc. to the user. Use the entry's body and a plain phrase (e.g. "a planned tradeoff", "a shortcut you knew about", "came up later") instead. The review.py output is already translated — match its tone.

Don't

  • Don't ask the user to confirm before running review.py.
  • Don't paraphrase the helper's stdout. Copy it verbatim into the fenced code block.
  • Don't enter paydown mode on the first turn. Stop after the report. Wait for the user's intent.
  • Don't auto-commit. Ever.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.