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 katalalab/katala-os --skill github-deep-reviewgit clone --depth 1 https://github.com/katalalab/katala-osWrote 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/katalalab/katala-os/github-deep-review)<a href="https://agentmods.dev/skills/katalalab/katala-os/github-deep-review"><img src="https://agentmods.dev/badge/skills/katalalab/katala-os/github-deep-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/katalalab/katala-os/github-deep-review"><img src="https://agentmods.dev/badge/skills/katalalab/katala-os/github-deep-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 | $0.00055 | $0.00453 |
| Opus 5.5 | $0.00022 | $0.00181 |
| Sonnet 5.5 | $0.00011 | $0.00091 |
| Haiku 4.5 | $0.00006 | $0.00045 |
Grade A, and why
github-deep-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 2mo 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.
What it actually says
github-deep-review — comprehensive PR/commit analysis
Performs a multi-layer review: diff reading → call-path tracing → risk assessment → test coverage check.
When to use
- "この PR を深くレビューして"
- "マージ前に regression リスクを確認して"
- "セキュリティ観点で見てほしい"
- "テストが十分か確認して"
Do not use for:
- Quick style or formatting checks (use
/code-reviewinstead) - Reviewing your own just-written code (too much context bias)
Review layers
1. Diff surface
gh pr diff <pr-number>
gh pr view <pr-number> --json title,body,files,reviews,checksums
2. Call-path impact
Use code_mapper subagent or rg to trace callers of changed functions.
3. Risk dimensions (report each separately)
- Correctness: logic errors, off-by-one, null handling
- Regressions: changed behavior in existing callers
- Security: injection, auth bypass, secret exposure, SSRF
- Data loss: destructive ops, migration safety, rollback path
- Concurrency: race conditions, lock order, shared state mutation
- Test coverage: uncovered branches, missing edge cases
4. Verdict
APPROVE / REQUEST_CHANGES / NEEDS_DISCUSSION
Confidence: high | medium | low
Blockers: [list]
Non-blockers: [list]
Hard-rule reminders
- Report confidence level for each finding.
- Distinguish "blocking" from "non-blocking" issues.
- Check if CI passed before calling coverage adequate.
- Destructive PRs (migrations, schema changes) require multi-agent consensus per CLAUDE.md.
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.
- 2mo ago First seen · 58 lines · 55 tokens per session scan A 2a74ee95b176
github-deep-review is a skill published in the GitHub repository katalalab/katala-os (2 stars, last pushed 9d ago), licensed MIT. It adds 55 tokens to every session and 453 once invoked, about $0.0002 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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