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 rjmurillo/ai-agents --skill reviewgit clone --depth 1 https://github.com/rjmurillo/ai-agentsWrote 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/rjmurillo/ai-agents/review)<a href="https://agentmods.dev/skills/rjmurillo/ai-agents/review"><img src="https://agentmods.dev/badge/skills/rjmurillo/ai-agents/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/rjmurillo/ai-agents/review"><img src="https://agentmods.dev/badge/skills/rjmurillo/ai-agents/review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 171 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00097 | $0.05996 |
| Opus 5 | $0.00048 | $0.02998 |
| Sonnet 5 | $0.00019 | $0.01199 |
| Haiku 4.5 | $0.00010 | $0.00600 |
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 5d 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.
How it starts
The opening of the file, as written. The whole thing — 193 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review
Review: $ARGUMENTS
If no argument, review the current branch diff against the base branch. Detect the base branch from gh pr view --json baseRefName or fall back to main.
Triggers
| Trigger Phrase | Operation |
|---|---|
/review |
Run the Stage-1 spec-compliance gate, then the Stage-2 review against the current branch diff |
/review BRANCH_OR_PR |
Run the Stage-1 gate, then the Stage-2 review against the named branch or PR |
review before merge |
Same as /review |
Convergence contract (REQ-008-04)
/review evaluates the canonical review axes by change risk, not by blind fan-out. The canonical axis prompts are authored at references/{role}.md co-located with this skill, with the canonical path expressed as .claude/skills/review/references/{role}.md in the source repo (the single source of truth). /review auto-discovers the axis set from references/*.md at runtime for --deep review; risk mode needs a table entry, or the axis is skipped (axis-selection.md). Enrollment is not edit-free: the axis names and counts in this body document that directory rather than drive it, and a contract test reds on drift. When CI exists in a project, the project syncs the canonical axes into its own CI prompts via the project's generator and drift checks. The build pipeline copies the whole skill directory into vendored plugin installs (see "Vendored install"), so the command runs with no CI dependency.
The canonical set is spec-compliance as the Stage-1 gate plus 11 Stage-2 canonical axes (analyst, architect, qa, security, devops, roadmap, reliability, observability, agent-safety, decision-rigor, code-quality). spec-compliance and analyst always run. Callers can pin additional always-on axes, and the remaining axes are selected from verified changed paths and diff effects by select_axes.py (Process step 4), never by prompt prose. spec-compliance runs first and gates Stage 2: only a CRITICAL_FAIL short-circuits the review (see Process step 2). A Stage-1 UNKNOWN (INCONCLUSIVE) does NOT short-circuit; Stage 2 still runs and the UNKNOWN is preserved as an UNKNOWN in the merge, because no spec or acceptance criteria could be located and that absence must never suppress a real Stage-2 finding. The caller decides how the merged verdict gates its workflow.
What ships with it
16 files 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.
- references/agent-safety.md 9.8 KB
- references/analyst.md 9.0 KB
- references/architect.md 11 KB
- references/code-quality.md 10 KB
- references/decision-rigor.md 10 KB
- references/devops.md 15 KB
- references/observability.md 9.2 KB
- references/qa.md 14 KB
- references/reliability.md 9.9 KB
- references/roadmap.md 9.3 KB
- references/security.md 11 KB
- references/spec-compliance.md 12 KB
- resources/axis-selection.md 13 KB
- scripts/select_axes.py 35 KB runs code
- scripts/validate_findings_scope.py 12 KB runs code
- scripts/validate_review_marker.py 16 KB runs code
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.
- 5d ago First seen · 193 lines · 97 tokens per session scan A 1f36f5f815d4
review is a skill published in the GitHub repository rjmurillo/ai-agents (45 stars, last pushed today), licensed MIT. It adds 97 tokens to every session and 5,996 once invoked, about $0.0005 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 2026-09-03.
Other skills, from other repositories
ax-annotation
@AX code annotation workflow skill for agent-driven tag application.
semantic-slicing
Build local semantic review slices by combining clawpatch feature maps, deepsec threat candidates, visual review maps, and optional gitcrawl/discrawl evidence for repos such as openclaw/openclaw.
code-review-skill
Reviews code for bugs, inefficiencies, and adherence to best practices, providing actionable improvement suggestions.
workspace-diff-review
Reviews the current workspace diff with a pre-landing mindset.
robin
Use whenever an agent creates, updates, reviews, or completes a GitHub pull request. Detect whether Robin is installed in the repository; when it is, automatically drive the PR through a bounded review, verified-fix, reply, thread-resolution, re-review, authorized-merge, and cleanup loop without requiring the user to…
install-gemini-code-review-action
Installs, configures, or upgrades Dazbo's PR code review & issue triage GitHub Action (gemini-review-action) in a target repository. Use when the user wants to set up, configure, or update automated AI code reviews, issue triaging, or Gemini model workflows for their GitHub repository.