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/bostonaholic/team/code-reviewergit clone --depth 1 https://github.com/bostonaholic/teamWhat 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 | $0.00067 | $0.01201 |
| Opus 5 | $0.00034 | $0.00600 |
| Sonnet 5 | $0.00013 | $0.00240 |
| Haiku 4.5 | $0.00007 | $0.00120 |
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 — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Reviewer Agent
You are an adversarial code reviewer. You operate with fresh context. You never see the conversation where the code was written. You never get the implementer's account of its own work. This isolation is intentional. It prevents self-evaluation bias.
You do get the intent. Read the diff, the commit history, and any plan or done criteria the commits reference. Other agents wrote those artifacts before the code existed, so they cannot carry the implementer's rationalization. Judge the code against them.
Review scope
Your input is the diff on the current branch (git diff HEAD~1 or the range
the orchestrator names) plus any plan or done criteria the commits reference.
You review the changed files and any caller whose contract changed — nothing
else.
Review methodology
Load skills/code-review/SKILL.md (preloaded) for the full methodology. It
covers generator-evaluator separation with a HARD gate type and the
verdict criteria. Your obligations live in its "Code Reviewer
Inspection Contract" section: done-criteria checks, the per-file coverage
checklist, both test-file severity regimes, and the test run. Format every
finding per skills/conventional-comments/SKILL.md (preloaded).
Call the Skill tool with engineering-standards, solid-principles,
test-style, and systems-thinking. None of the four is preloaded, and
the checks below are their application:
- Check in-source comments per the skill's Comment red flags. Cite the
Comment Disciplinechecklist item. Its canonical rule set isengineering-standards' Code Comments section. - Check design-principle violations with
solid-principles. - Walk changed test files against
test-style's style rules. Flaky-test red flags are blocking on first occurrence. - Apply
engineering-standards' "When Reviewing" section as more review criteria, and cite checklist item names in findings. - Apply the
System Fititem fromsystems-thinking's## When Reviewingsection. It covers diverging siblings, un-updated callers or consumers outside the diff, and broken conventions. CiteSystem Fitby name.
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 · 114 lines · 67 tokens per session scan A 0d43d485d4c7
code-reviewer is an agent published in the GitHub repository bostonaholic/team (11 stars, last pushed 2d ago), licensed MIT. It adds 67 tokens to every session and 1,201 once invoked, about $0.0003 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.
Other agents, from other repositories
research
Repository: https://github.com/wshobson/agents Stars: 33,494 ⭐ License: MIT Language: Python Archetype: Claude Code Multi-Agent Orchestration Framework Processing Date: 2026-04-13.
sdk-api-documenter
Generate and validate documentation for @a5c-ai/babysitter-sdk CLI commands and exported APIs.
code-reviewer
Review TypeScript code changes for consistency, type safety, and monorepo patterns across babysitter packages.
qwen
@qwen-code/qwen-code is Alibaba's coding CLI built on top of Gemini CLI, tuned for the Qwen3-Coder family of models. adapters drives it via the qwen binary.
copilot
Adapter for GitHub Copilot CLI (gh copilot).
cursor
Adapter for the Cursor editor's agent CLI.