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 agentmods add skills/abilityai/abilities/reviewnpx skills add Abilityai/abilities --skill reviewgit clone --depth 1 https://github.com/Abilityai/abilitiesWhat 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 | $0.00060 | $0.03737 |
| Opus 5 | $0.00030 | $0.01869 |
| Sonnet 5 | $0.00012 | $0.00747 |
| Haiku 4.5 | $0.00006 | $0.00374 |
Grade A, and why
review-agent scanned grade A with 1 finding 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 2d 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.
Enumerates other installed skillslowAgent snooping
Other skills' SKILL.md files reveal prompts, capabilities and secrets that should be invisible to peers.
ls CLAUDE.md 2>/dev/null && ls -d .claude/skills 2>/dev/null Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
How it starts
The opening of the file, as written. The whole thing — 244 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review Agent
ℹ️ First, set expectations: before anything else, print one short line with this skill's version and its most recent change — the top entry of
metadata.changelogabove — e.g.review-agent vX.Y — recent: <summary>. Then proceed.
Audit an existing agent against best practices and produce a findings report. Read-only by construction — this skill has no Write/Edit tools and changes nothing. It is the detect-and-report half of the pair; /adjust-agent (agent-level) and /agent-dev:adjust-playbook (skill-level) are the apply half.
This skill is the single source of truth for the agent audit rubric. /adjust-agent invokes this skill to get its findings rather than duplicating the checks.
When to Use
- "review this agent", "audit my agent", "check best practices"
- Periodic health check on an established agent
- Before deploying or hardening an agent
- To apply fixes after reviewing → run
/adjust-agentor/agent-dev:adjust-playbook
Step 1: Locate and Read the Agent
If $0 (path) provided, use it. Otherwise assume the current working directory.
Verify it's an agent:
ls CLAUDE.md 2>/dev/null && ls -d .claude/skills 2>/dev/null
If CLAUDE.md doesn't exist, ask for the correct path.
Read all agent artifacts (a missing one is itself a finding):
CLAUDE.mdREADME.md,ARCHITECTURE.md,TARGET-ARCHITECTURE.md(a missing one is a Documentation Coherence finding)template.yaml.env.example.gitignore.mcp.json.templateor.mcp.json- All
SKILL.mdfiles:find .claude/skills -name "SKILL.md" 2>/dev/null - Any subagents:
ls .claude/agents/*.md 2>/dev/null - Top-level listing:
ls -la
If $ARGUMENTS names a focus area (e.g. "composition", "schedules", "trinity"), audit only that area; otherwise run the full audit.
Step 2: Audit
Evaluate each area and assign a status:
- PASS — meets best practice, no change needed
- IMPROVE — present but incomplete
- MISSING — not present at all
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.
- 2d ago First seen · 244 lines · 60 tokens per session scan A a6786a2c6178
review-agent is a skill published in the GitHub repository Abilityai/abilities (11 stars, last pushed 14d ago), licensed MIT. It adds 60 tokens to every session and 3,737 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (enumerates other installed skills). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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