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/agentskill-sh/ags/review-skillnpx skills add agentskill-sh/ags --skill review-skillgit clone --depth 1 https://github.com/agentskill-sh/agsWrote 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/agentskill-sh/ags/review-skill)<a href="https://agentmods.dev/skills/agentskill-sh/ags/review-skill"><img src="https://agentmods.dev/badge/skills/agentskill-sh/ags/review-skill.svg" alt="Measured on agentmods" 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 | $0.00090 | $0.01060 |
| Opus 5 | $0.00045 | $0.00530 |
| Sonnet 5 | $0.00018 | $0.00212 |
| Haiku 4.5 | $0.00009 | $0.00106 |
Grade A, and why
review-skill 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 4d 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 — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Reviewer
Review agent skills against best practices and rewrite weak areas.
When to Use
- After writing or editing a SKILL.md
- Before publishing a skill to agentskill.sh or sharing with a team
- When a skill underperforms (low ratings, poor triggering, inconsistent output)
- When asked to audit, review, or improve a skill
Review Process
Step 1: Read the Skill
Read the full SKILL.md and all referenced files (references/, scripts/, assets/). Note the skill's purpose, target audience, and complexity.
Step 2: Score Against 10 Dimensions
Evaluate each dimension on a 1-5 scale using the rubric in references/rubric.md.
Skill Review: <skill-name>
| # | Dimension | Score | Key Issue |
|---|------------------------|-------|----------------------------------|
| 1 | Frontmatter | ?/5 | |
| 2 | Description Quality | ?/5 | |
| 3 | Conciseness | ?/5 | |
| 4 | Structure | ?/5 | |
| 5 | Instruction Clarity | ?/5 | |
| 6 | Freedom Calibration | ?/5 | |
| 7 | Error Handling | ?/5 | |
| 8 | Progressive Disclosure | ?/5 | |
| 9 | Scripts Quality | ?/5 | |
|10 | Completeness | ?/5 | |
Overall: ?/50
Step 3: List Specific Issues
For each dimension scoring 3 or below, list concrete issues:
### Issues
1. [D2] Description is 15 characters, too vague to trigger reliably
2. [D3] Lines 45-80 explain what a CSV is; the agent already knows this
3. [D6] Three PDF libraries listed as equal options; pick a default
Step 4: Rewrite Problem Areas
For each issue, show the current text and a rewritten version. Apply changes directly if the user asks for it, otherwise present as suggestions.
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.
- 4d ago First seen · 122 lines · 90 tokens per session scan A db60691813e1
review-skill is a skill published in the GitHub repository agentskill-sh/ags (35 stars, last pushed 3mo ago), licensed MIT. It adds 90 tokens to every session and 1,060 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 2026-08-30.
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