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 existential-birds/beagle --skill review-skillgit clone --depth 1 https://github.com/existential-birds/beagleWrote 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/existential-birds/beagle/review-skill)<a href="https://agentmods.dev/skills/existential-birds/beagle/review-skill"><img src="https://agentmods.dev/badge/skills/existential-birds/beagle/review-skill/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/existential-birds/beagle/review-skill"><img src="https://agentmods.dev/badge/skills/existential-birds/beagle/review-skill.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 | $0.00045 | $0.01312 |
| Opus 5.5 | $0.00018 | $0.00525 |
| Sonnet 5.5 | $0.00009 | $0.00262 |
| Haiku 4.5 | $0.00005 | $0.00131 |
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 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.
How it starts
The opening of the file, as written. The whole thing — 164 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Review
Review Agent Skill PRs for structural validity, design quality, and marketplace consistency.
Arguments
$ARGUMENTS: Output file path for review results (required, passed by the calling harness or the user)--base <branch>: Base branch for diff comparison (default:main)
Workflow
Step 1: Parse Arguments
Extract the output path from $ARGUMENTS. If no path is provided, default to .review-output.md. Extract --base if provided, otherwise default to main.
Step 2: Identify Changed Skills
git diff --name-only $(git merge-base HEAD <base>)..<HEAD> | grep -E '(SKILL\.md|skills/[^/]+/)'
Group changed files by skill directory. Each unique skill directory is a review target. If no skill files changed, write "No skill files changed" to the output path and stop.
Step 3: Read Each Changed Skill End-to-End
For each changed skill:
- Read the full
SKILL.md(not just diff lines) - Read all files in the skill directory (references, scripts)
- Note the parent plugin directory and locate its
plugin.json
Step 4: Run Structural Checks (HIGH Confidence)
Apply every check in references/structural-checks.md. These are binary pass/fail — violations are clear-cut.
Structural violations are HIGH confidence because they can be verified mechanically.
Step 5: Run Design Checks (MEDIUM Confidence)
Apply every check in references/design-checks.md. These require judgment — flag only when the issue is clear, not when the approach is merely different from what you'd choose.
Design issues are MEDIUM confidence because they involve subjective assessment.
Step 6: Run Marketplace Checks (HIGH Confidence)
Apply every check in references/marketplace-checks.md. These verify the skill integrates correctly with the marketplace it belongs to.
Marketplace violations are HIGH confidence because they can be verified by reading manifest files.
What ships with it
3 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.
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 · 164 lines · 45 tokens per session scan A ccd484bd991e
review-skill is a skill published in the GitHub repository existential-birds/beagle (84 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 45 tokens to every session and 1,312 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.
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