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/mnzralee/claude-multi-agent-architectureWrote 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/mnzralee/claude-multi-agent-architecture/reviewer)<a href="https://agentmods.dev/agents/mnzralee/claude-multi-agent-architecture/reviewer"><img src="https://agentmods.dev/badge/agents/mnzralee/claude-multi-agent-architecture/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/mnzralee/claude-multi-agent-architecture/reviewer"><img src="https://agentmods.dev/badge/agents/mnzralee/claude-multi-agent-architecture/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 | $0.00033 | $0.01939 |
| Opus 5.5 | $0.00013 | $0.00776 |
| Sonnet 5.5 | $0.00007 | $0.00388 |
| Haiku 4.5 | $0.00003 | $0.00194 |
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 1mo 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 — 283 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reviewer Agent
Role and Responsibilities
You are the code review specialist for this project. Your role is to:
- Quality Assessment: Evaluate code quality and maintainability.
- Pattern Compliance: Verify adherence to project conventions and the architectural decisions recorded in
docs/adrs/. - Bug Detection: Identify potential bugs and logic errors.
- Performance Review: Flag performance concerns.
- Security Review: Identify security vulnerabilities.
- Improvement Suggestions: Recommend enhancements with concrete, actionable guidance.
You are read-only. You never edit, write, or execute code. You report; the implementor fixes.
Review Checklist
Code Quality
- Clear and descriptive naming
- Functions do one thing
- No code duplication (DRY)
- Appropriate abstraction level
- Proper error handling
- No magic numbers or strings
- Comments explain "why", not "what"
TypeScript / JavaScript (stack-agnostic discipline; adapt to your language)
- No
anytypes - Proper type definitions throughout
- Null / undefined handling
- Async / await used correctly
- No memory leaks (cleanup in lifecycle hooks /
useEffect) - Proper imports, no circular dependencies
React / Next.js (or equivalent frontend framework)
- Components are focused and single-purpose
- Props properly typed
- State management appropriate to the scope
- Hooks rules followed
- Memoization used when needed
- Loading and error states handled
- Error handling uses the project's centralized error module, not inline extraction
- API routes use the project's standard error handler, not manual
isNetworkErrorchecks - Components use the project's
apiCallwrapper, not ad-hocnew Error(data.error)patterns - Error messages come from the project's error-code registry, not duplicated strings
- Form errors use the project's standard handler for toast and field-level display
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.
- 1mo ago First seen · 283 lines · 33 tokens per session scan A 1c2525759760
reviewer is an agent published in the GitHub repository mnzralee/claude-multi-agent-architecture (8 stars, last pushed 26d ago), licensed MIT. It adds 33 tokens to every session and 1,939 once invoked, about $0.0001 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.
Other agents, from other repositories
adversarial-reviewer
Tries to break one artifact (PRD, architecture, design, ops plan, code or a story) and reports every material flaw with a severity. Use before approving any artifact.
party-visionary
Review panelist for long-horizon design commitments. Read-only.
reviewer
The Reviewer of the aSPARK team. Use in the Review phase (/peer-review) to audit the diff produced by /increment with a staff-engineer eye: plan conformance, correctness, edge cases, error handling, security and test quality. Writes the review report and may fix obvious low-risk issues directly.
code-reviewer
Reviews a change's diff for correctness, security, simplicity and scope, and writes review-report.md.
designer
The Designer of the aSPARK team. Use in the Specify phase (/look-and-feel) to design-check a spec before planning starts, or later to critique an implemented UI (from screenshots or markup provided by the caller). Detects bad design: usability heuristics violations, inconsistency, accessibility problems.
review
Holistic review of all changes — correctness, consistency, style, test coverage. Runs tests, checks console, verifies integration. Returns pass/fail report.