review

review is a skill for Claude Code from bcanfield/agentic-tech-debt. It costs 70 tokens per session (985 once invoked), scanned A, original, MIT.

A review tool for a tech-debt registry, a list of known codebase shortcuts and maintenance problems. It audits the list, ranks remaining entries, and can guide the user through selected fixes afterward.

In plain words
What is it for?
Use it to review technical debt, see the top items to address, drop stale entries, or work through selected paydown tasks one at a time.
Why use it?
It turns a broad debt list into a short order of priorities based on code churn, meaning how often affected code changes, and the kind of debt involved. It also helps remove entries that are no longer relevant.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: mentions Claude Code.

Runs only inside its plugin — its command needs a path that Claude Code sets for a plugin’s own hooks and for nothing else. Install the plugin, not this.

Part of the debt-ops plugin — 4 skills, 4 hooks shipped together

Good fit Use it to review technical debt, see the top items to address, drop stale entries, or work through selected paydown tasks one at a time.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.

Claude Code
/plugin marketplace add bcanfield/agentic-tech-debt
Claude Code
/plugin install debt-ops

Made for: Claude Code.

Or install debt-ops, the plugin that ships this one along with the rest of its 4 skills, 4 hooks.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for review

README.md
[![agentmods](https://agentmods.dev/badge/skills/bcanfield/agentic-tech-debt/review/github.svg)](https://agentmods.dev/skills/bcanfield/agentic-tech-debt/review)
Your own site
<a href="https://agentmods.dev/skills/bcanfield/agentic-tech-debt/review"><img src="https://agentmods.dev/badge/skills/bcanfield/agentic-tech-debt/review/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for review

Your own site · 80×15
<a href="https://agentmods.dev/skills/bcanfield/agentic-tech-debt/review"><img src="https://agentmods.dev/badge/skills/bcanfield/agentic-tech-debt/review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 70 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 985 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00070 $0.00985
Opus 5.5 $0.00028 $0.00394
Sonnet 5.5 $0.00014 $0.00197
Haiku 4.5 $0.00007 $0.00098

Measured 1mo ago against content hash 6787ed3cab86, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/review.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

claude-code/skills/review/SKILL.md · 60 lines

How it starts

The opening of the file, as written. The whole thing — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/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

python3 ${CLAUDE_PLUGIN_ROOT}/skills/review/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. Claude Code collapses long bash outputs behind a +N lines, ctrl+o to expand placeholder — if you don't print it yourself, the user never sees 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: ."
  • 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 → invoke /code-review on 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.

Read the full file on GitHub · 60 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago First seen · 60 lines · 70 tokens per session scan A 6787ed3cab86

Subscribe to this mod's changes

review is a skill published in the GitHub repository bcanfield/agentic-tech-debt (8 stars, last pushed today), licensed MIT. It adds 70 tokens to every session and 985 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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