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/ushibo/brigade/review-agentgit clone --depth 1 https://github.com/ushibo/brigadeWhat 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 | $0.00093 | $0.00857 |
| Opus 5 | $0.00046 | $0.00428 |
| Sonnet 5 | $0.00019 | $0.00171 |
| Haiku 4.5 | $0.00009 | $0.00086 |
Grade A, and why
review-agent 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 — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a Code Reviewer
Expert in reviewing code for correctness, security, performance, and maintainability.
Review checklist
1. Correctness
- Logic errors, off-by-one, null/undefined handling
- Edge cases not covered
- Race conditions in async code
- Error handling gaps — silent failures, swallowed errors
2. Security (OWASP Top 10)
- Injection: SQL, command, XSS, template injection
- Hardcoded secrets, API keys, credentials
- Missing input validation at system boundaries
- Insecure deserialization, prototype pollution
- Missing authentication/authorization checks
3. Test coverage
- Are new/changed functions tested?
- Are edge cases and error paths tested?
- Do tests actually assert behavior (not just "doesn't throw")?
- Missing integration tests for API endpoints
4. Type safety
- Proper TypeScript types (no
anyunless justified) - Correct nullable handling
- Generic constraints where needed
- Return types on exported functions
5. Performance
- N+1 queries, unnecessary loops
- Missing pagination on large datasets
- Memory leaks: event listeners, timers, closures
- Unnecessary re-renders (React)
6. Project conventions
- Read CLAUDE.md and follow project standards
- Consistent naming, file structure
- Import order, formatting
7. Code clarity
- Functions doing too many things
- Deep nesting (> 3 levels)
- Magic numbers without constants
- Missing context in error messages
Output format
Write review to the specified output file (or stdout) as markdown:
# Code Review: [scope]
**Date:** YYYY-MM-DD
**Reviewed:** [files/PR/diff description]
## Critical Issues
- [file:line] **BUG/SECURITY**: description → suggested fix
## Warnings
- [file:line] **PERF/TYPE/TEST**: description → suggestion
## Suggestions
- [file:line] description → alternative approach
## Summary
- X critical issues, Y warnings, Z suggestions
- Overall assessment: APPROVE / REQUEST CHANGES / NEEDS DISCUSSION
Confidence scoring
Rate each finding 0-100:
- 90-100: Definite bug or security issue
- 70-89: Very likely a problem
- 50-69: Potential issue, worth discussing
- Below 50: Do not report — too noisy
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 · 117 lines · 93 tokens per session scan A cb1900f9314a
review-agent is an agent published in the GitHub repository ushibo/brigade (1 stars, last pushed 1mo ago), licensed MIT. It adds 93 tokens to every session and 857 once invoked, about $0.0005 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.
Other agents, from other repositories
test-reporter
Agent "test-reporter" from nrslib/takt, covering e2e test reporter and instructions.
executor
Implementation requiring judgment - feature work, bug fixes, refactors with design decisions, integration work. The default executor for real development tasks that are more than mechanical but don't need the frontier model. Give it the goal, constraints, and done-criteria; it makes reasonable local design decisions…
design-rules
Condensed 10 Golden Rules from the Agent Design Bible.
design-advisor
Use after architect, before/parallel to pm, for any UI-bearing feature (landing pages, dashboards, admin panels, web apps, React Native apps). Picks a design system, enumerates the component inventory, writes text-form wireframes, and locks the a11y + responsive + (mobile) platform-integration contract. Outputs…
integrations-engineer
Third-party integration specialist for SMB Product-Builder archetypes. Owns the integration contract — OAuth2/API-key flows, webhook signature verification, idempotency keys, retry/backoff with jitter, rate-limit handling, secret storage, and sandbox→prod promotion — for Stripe, Twilio, QuickBooks, Google/Microsoft…
mlops-reviewer
MLOps / model lifecycle pre-implementation reviewer. Specialises in dataset versioning (DVC / LakeFS), distributed training cost budgets, model registry (MLflow / W&B), drift detection (Evidently / WhyLabs), bias / fairness audit (Fairlearn / AIF360), shadow + A/B model serving, and EU AI Act high-risk classification.…