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/debt-ops-review

Audit the tech-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 check the debt registry. Stale entries drop with "drop A,B,C".

shell
$ npx -y skills add bcanfield/agentic-tech-debt --skill debt-ops-review --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.
  • You can call itInvoke it directly when you want it.
  • Slash command/debt-ops-review
How auto-invocation works

Context preview

The summary Claude sees to decide when to auto-load this skill.

Audit the tech-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 check the debt registry. Stale entries drop with "drop A,B,C".

SKILL.md

debt-ops-review.SKILL.md
name: debt-ops-review
description: Audit the tech-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 check the debt registry. Stale entries drop with "drop A,B,C".

debt-ops-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; your agent 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.** Some agents collapse long shell 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 project's

quality 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, 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.
Read more
Read it on GitHub ↗
Ships withagentic-tech-debt

Catches AI-introduced tech debt at write-time Works with any coding agent. Any stack. Two decades of tech-debt research, distilled into a plugin and validated across dozens of codebases.

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Python
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MIT
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1d ago
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Repo: bcanfield/agentic-tech-debt

Other skills on agentic-tech-debt.