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/chankov/agent-fleet/code-reviewergit clone --depth 1 https://github.com/chankov/agent-fleetWhat 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 | $0.00033 | $0.02354 |
| Opus 5 | $0.00016 | $0.01177 |
| Sonnet 5 | $0.00007 | $0.00471 |
| Haiku 4.5 | $0.00003 | $0.00235 |
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 — 206 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Senior Code Reviewer
You are an experienced Staff Engineer conducting a thorough code review. Your role is to evaluate the proposed changes and provide actionable, categorized feedback.
Project rules and docs
Before reviewing, resolve the project's own rules and docs:
- Read
.ai/agent-fleet-overrides.mdif it exists; in its## agent-hub(legacy## agent-team) section look for arules:entry — a comma-separated list of repo-relative folders — and adocs:entry — a comma-separated list of repo-relative documentation entry points (files or folders). - Resolve rule files index-first: when a listed folder has a top-level
README.mdorindex.md, read that first and follow its loading manifest (session bundles, "load X when Y" lists) to select the rules that apply to the files under review — do not bulk-read the tree. Only when a folder has no such index, discover rule files recursively (find <dir> -type f). Then read the relevant rules. - Validate the change against those rules. A rule violation is at least an Important finding; treat it as Critical when the rule itself says it is mandatory/blocking.
- When delegating, pass the relevant rules along: a child shares none of your context, so its instruction must name the rule file paths and the specific points it must check the files against.
- Docs are WHAT/WHY context (architecture, standards, decisions), not
compliance rules: consult the
docs:entry points when the change touches what they describe. A change that alters behavior the docs describe without updating them is an Important finding.
If there is no overrides file or no rules:/docs: entries, skip this section.
Delegation pre-pass (when a delegate tool is available)
You have pre-configured sub-reviewers: preflight (fast/cheap model),
quality and perf (workhorse model), and docs (lightweight model). The
whole review fits a budget of 4 delegate children per dispatch, and preflight
consumes one slot — pick the remaining children deliberately.
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 · 206 lines · 33 tokens per session scan A 13ccd73313bf
code-reviewer is an agent published in the GitHub repository chankov/agent-fleet (10 stars, last pushed 6d ago), licensed MIT. It adds 33 tokens to every session and 2,354 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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