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 anurmatov/phleet --skill fleet-reviewgit clone --depth 1 https://github.com/anurmatov/phleetWrote 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/anurmatov/phleet/fleet-review)<a href="https://agentmods.dev/skills/anurmatov/phleet/fleet-review"><img src="https://agentmods.dev/badge/skills/anurmatov/phleet/fleet-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/anurmatov/phleet/fleet-review"><img src="https://agentmods.dev/badge/skills/anurmatov/phleet/fleet-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 | $0.00014 | $0.00255 |
| Opus 5 | $0.00007 | $0.00128 |
| Sonnet 5 | $0.00003 | $0.00051 |
| Haiku 4.5 | $0.00001 | $0.00026 |
Grade A, and why
fleet-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 11d 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
Fleet Code Review
Review Checklist
Correctness
- Code does what the PR description says
- Edge cases are handled
- Error handling is appropriate
- No regressions in existing functionality
Security
- No hardcoded secrets or credentials
- Input validation on external data
- No SQL injection, XSS, or command injection risks
- Authentication/authorization checks in place
Quality
- Code follows project conventions (CLAUDE.md)
- No unnecessary complexity
- Tests cover the changes
- All tests pass
Performance
- No obvious N+1 queries
- No unbounded collections or loops
- Async operations used where appropriate
Review Output Format
## Review: {PR Title}
**Verdict**: Approve / Request Changes
### Summary
Brief overview of the changes and their quality.
### Issues Found
1. **[severity]** file:line — description
### Suggestions
- Optional improvements (not blocking)
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.
- 11d ago First seen · 48 lines · 14 tokens per session scan A e4f0b95abe82
fleet-review is a skill published in the GitHub repository anurmatov/phleet (18 stars, last pushed yesterday), licensed MIT. It adds 14 tokens to every session and 255 once invoked, about $0.0001 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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