Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add bcanfield/agentic-tech-debt --skill debt-ops-reviewgit clone --depth 1 https://github.com/bcanfield/agentic-tech-debtWrote 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.
[](https://agentmods.dev/skills/bcanfield/agentic-tech-debt/debt-ops-review)<a href="https://agentmods.dev/skills/bcanfield/agentic-tech-debt/debt-ops-review"><img src="https://agentmods.dev/badge/skills/bcanfield/agentic-tech-debt/debt-ops-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.
<a href="https://agentmods.dev/skills/bcanfield/agentic-tech-debt/debt-ops-review"><img src="https://agentmods.dev/badge/skills/bcanfield/agentic-tech-debt/debt-ops-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00072 | $0.00964 |
| Opus 5 | $0.00036 | $0.00482 |
| Sonnet 5 | $0.00014 | $0.00193 |
| Haiku 4.5 | $0.00007 | $0.00096 |
Grade A, and why
debt-ops-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 9d ago.
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.
This is a copy
86% identical to review — 72 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 84 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
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: ."
- 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_triggeror 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.
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.
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.
- 9d ago First seen · 84 lines · 72 tokens per session scan A 9ac24ae23f50
debt-ops-review is a skill published in the GitHub repository bcanfield/agentic-tech-debt (8 stars, last pushed today), licensed MIT. It adds 72 tokens to every session and 964 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to review, differing in 72 lines, and is treated as a copy.
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