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 xg-gh-25/SwarmAI --skill s_code-reviewgit clone --depth 1 https://github.com/xg-gh-25/SwarmAIWrote 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/xg-gh-25/swarmai/s_code-review)<a href="https://agentmods.dev/skills/xg-gh-25/swarmai/s_code-review"><img src="https://agentmods.dev/badge/skills/xg-gh-25/swarmai/s_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/xg-gh-25/swarmai/s_code-review"><img src="https://agentmods.dev/badge/skills/xg-gh-25/swarmai/s_code-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00052 | $0.00176 |
| Opus 5.5 | $0.00021 | $0.00070 |
| Sonnet 5.5 | $0.00010 | $0.00035 |
| Haiku 4.5 | $0.00005 | $0.00018 |
Grade A, and why
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 1mo 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
Code Review
This skill loads full instructions on activation. Read INSTRUCTIONS.md before proceeding.
TRIGGER: "review code", "code review", "review PR", "review this file", "check code quality", "review my changes", "PR review" DO NOT USE: for UI/frontend-specific review (use web-design-review) or for auto-fixing code (use simplify)
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.
- 1mo ago First seen · 18 lines · 52 tokens per session scan A df1d2cd9dbec
code-review is a skill published in the GitHub repository xg-gh-25/SwarmAI (55 stars, last pushed 8d ago), licensed MIT. It adds 52 tokens to every session and 176 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 2026-08-30.
Other skills, from other repositories
preflight
Executed pre-completion checklist — third sibling of /prospect (before execution) and /retrospect (after shipping). Six checks, three outcomes each (PASS/FAIL/INVALID); an unrun check blocks the verdict. Catches failures that emit no error: a check whose FORM bounds what it finds, and a decision correct in isolation…
audit
Umbrella for the audit family — the canonical way to run every sub-audit: '/audit knowledge' (scan memory and plans for extractable knowledge, backlog-to-promotion review), '/audit config' (CLAUDE.md/settings/docs drift and staleness), '/audit style' (mine session-log history for revealed working-style rules), '/audit…
learn-from-sage
Detection-gap (miss) analysis for Code Review Sage. Learn from shipped fixes, acted-on human comments, and design outcomes to close reviewer blind spots. Inline during review stages a candidate; a human triggers a one-shot AI consolidation into the live ruleset.
gsd-ns-review
Invoke this Pi skill with /skill:gsd-ns-review.
make-pr-easy-to-review
Prepare PRs for review by cleaning noisy history, improving PR descriptions, and adding reviewer guidance without changing code behavior. Use for "make this easy to review", "tidy this PR", "clean up commits", or "annotate the diff".
thermo-nuclear-code-quality-review
Run an extremely strict maintainability review for abstraction quality, giant files, and spaghetti-condition growth. Use for a thermo-nuclear code quality review, thermonuclear review, deep code quality audit, or especially harsh maintainability review.