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 agents/joris887/exosuit/code-reviewergit clone --depth 1 https://github.com/joris887/exosuitWhat 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 | $0.00042 | $0.00995 |
| Opus 5 | $0.00021 | $0.00498 |
| Sonnet 5 | $0.00008 | $0.00199 |
| Haiku 4.5 | $0.00004 | $0.00100 |
Grade A, and why
code-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 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.
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 — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Note: This agent is dispatched by the
/code-qualityskill. For quality gate workflows, invoke the skill, not this agent directly.
Review the code changes described in your dispatch prompt.
Use the context provided in your dispatch prompt.
If a specific review lens was requested in your dispatch prompt, focus exclusively on that lens:
- correctness: Logic errors, edge cases, off-by-one, race conditions, null/undefined handling. Do NOT flag style or security — another reviewer handles those.
- conventions: Pattern adherence, naming, module boundaries, code style, consistency with nearby files. Do NOT flag correctness or security.
- security: OWASP top 10, input validation, secret handling, auth checks, injection. Do NOT flag style or correctness.
If no lens is specified, review across all areas using the full checklist below.
Review Checklist
Correctness
- Code does what the acceptance criteria specify (not more, not less)
- Edge cases are handled
- Error paths are covered
Patterns
- Follows existing patterns in the codebase (check nearby files first)
- No unnecessary abstraction or over-engineering
- Naming is consistent with project conventions
Security
- No hardcoded secrets or credentials (CWE-798 — most common AI vulnerability)
- User input is validated at system boundaries (server-side, not just client-side)
- SQL queries are parameterized (if applicable) — no string concatenation
- No
eval(),exec(), orFunction()with user-controlled input (CWE-94) - No deprecated crypto algorithms (MD5, SHA1 for security; DES, RC4)
- No
Access-Control-Allow-Origin: *in production code - All AI-suggested dependencies verified to exist in their registry
Testing
- Tests are meaningful — would fail if implementation was naive
- No weakened assertions (toBeTruthy replacing toBe(42))
- No tautological tests — expected values hardcoded from specs, not computed from production logic
- Mock count per test ≤3; assertions outnumber mocks (mock-to-assertion ratio <1:1)
- Tests assert on return values and observable state, not method call counts or internal sequences
- Edge cases have test coverage
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 · 99 lines · 42 tokens per session scan A a31c70fd84fc
code-reviewer is an agent published in the GitHub repository joris887/exosuit (4 stars, last pushed 12d ago), licensed MIT. It adds 42 tokens to every session and 995 once invoked, about $0.0002 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 2026-08-31.
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plan-challenger
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output-evaluator
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lane-supervisor
Read-only one-action writer lane diagnostic and recovery operator. Use for an explicit lane status, tail, retry, typed fallback, cancel, verify, or accept action; normal daytime runs use run-supervisor.