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 gabriele-mastrapasqua/codex-lean-team --skill focused-code-reviewgit clone --depth 1 https://github.com/gabriele-mastrapasqua/codex-lean-teamWrote 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/gabriele-mastrapasqua/codex-lean-team/focused-code-review)<a href="https://agentmods.dev/skills/gabriele-mastrapasqua/codex-lean-team/focused-code-review"><img src="https://agentmods.dev/badge/skills/gabriele-mastrapasqua/codex-lean-team/focused-code-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/gabriele-mastrapasqua/codex-lean-team/focused-code-review"><img src="https://agentmods.dev/badge/skills/gabriele-mastrapasqua/codex-lean-team/focused-code-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 | $0.00029 | $0.00142 |
| Opus 5 | $0.00015 | $0.00071 |
| Sonnet 5 | $0.00006 | $0.00028 |
| Haiku 4.5 | $0.00003 | $0.00014 |
Grade A, and why
focused-code-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 8d 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
Review the actual diff plus enough surrounding code to validate behavior.
Check:
- Functional correctness and edge cases.
- Error handling and cleanup.
- Concurrency, async, ownership, and lifecycle.
- Security and data integrity.
- Public contracts and backward compatibility.
- Tests: whether they would fail before the fix and cover realistic regressions.
- Language-specific hazards.
Return only actionable findings ordered by severity, followed by residual risks and validation gaps. Avoid style-only comments unless they hide correctness or maintenance risk.
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.
- 8d ago First seen · 18 lines · 29 tokens per session scan A c9dcffaf2969
focused-code-review is a skill published in the GitHub repository gabriele-mastrapasqua/codex-lean-team (3 stars, last pushed 1mo ago), licensed MIT. It adds 29 tokens to every session and 142 once invoked, about $0.0001 per session on Opus 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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review-code
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review-security
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evidence-review
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code-review-excellence
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openlore-execute-refactor
Apply a confirmed .openlore/refactor-plan.md with a test gate after each change. Use when asked to execute or continue an OpenLore refactoring plan.
openlore-review-changes
Review code changes using OpenLore risk, call, coverage, and cluster evidence without editing code. Use when asked for a change review, pre-PR safety check, or merge recommendation.