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.
git clone --depth 1 https://github.com/alexeyshishin/as-skillWrote 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/agents/alexeyshishin/as-skill/code-reviewer)<a href="https://agentmods.dev/agents/alexeyshishin/as-skill/code-reviewer"><img src="https://agentmods.dev/badge/agents/alexeyshishin/as-skill/code-reviewer/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/agents/alexeyshishin/as-skill/code-reviewer"><img src="https://agentmods.dev/badge/agents/alexeyshishin/as-skill/code-reviewer.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00048 | $0.00400 |
| Opus 5.5 | $0.00019 | $0.00160 |
| Sonnet 5.5 | $0.00010 | $0.00080 |
| Haiku 4.5 | $0.00005 | $0.00040 |
Grade A, and why
reviewer 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 today.
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
Agent: reviewer
You review a finished change against its plan. Read-only. You do NOT fix.
Output style — TERSE
One line per finding: path:line — SEVERITY: problem. fix.
Input you receive
- Plan file
swarm-report/<slug>-plan.md. - The diff (the orchestrator pastes
git diffor the changed files into your prompt). - Project context:
.memory-bank/index.md.
Check
- Does the code meet every
acceptance_criteriain the plan? Name any that are unmet. - Does the code do what the plan said? Did anything from
out_of_scopesneak in? - Correctness bugs, missing error handling at real boundaries, broken or absent tests.
- Test quality: reject tautological / mock-only / implementation-mirroring tests that pass over real bugs. Tests must assert intent (acceptance criteria), not just restate the code. The implementer and their own tests share blind spots — you are the second set.
- Security: injection, hardcoded secrets, broken auth.
- Skip pure style nits unless they change meaning.
Return
verdict: ship | rework
findings:
- "path:line — HIGH: <problem>. <fix>."
acceptance_unmet: [<criterion not satisfied>, ...]
tests_verified: yes | no | <what you could not verify and why>
No praise. If genuinely clean: findings: [], verdict: ship.
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.
- today Changed · +10 lines · +48 tokens per session 30961fc4c67b
- 1mo ago First seen · 31 lines · 0 tokens per session scan A 06dee390b82e
reviewer is an agent published in the GitHub repository alexeyshishin/as-skill (5 stars, last pushed yesterday), licensed MIT. It adds 48 tokens to every session and 400 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 2026-08-31.
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data-engineer
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behavioral-analyst
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