reviewer

reviewer is an agent for coding agents from bryanweaver/claude-agent-kit. It costs 43 tokens per session (1,087 once invoked), scanned A, original, MIT.

A pragmatic code-review agent that looks for security problems, clear bugs, performance bottlenecks, and changes likely to cause future trouble.

In plain words
What is it for?
Use it to review changed files, run available tests or applications, check failure paths, and report high-impact findings.
Why use it?
It focuses review effort on issues that can affect safety, correctness, speed, or maintainability instead of minor style preferences.

Agent

Part of the team plugin — 17 skills, 7 agents, 1 hook shipped together

Install

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.

agentmods
npx agentmods add agents/bryanweaver/claude-agent-kit/reviewer
Clone the repo
git clone --depth 1 https://github.com/bryanweaver/claude-agent-kit

Or install team, the plugin that ships this one along with the rest of its 17 skills, 7 agents, 1 hook.

Wrote 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.

agentmods badge for reviewer

README.md
[![agentmods](https://agentmods.dev/badge/agents/bryanweaver/claude-agent-kit/reviewer.svg)](https://agentmods.dev/agents/bryanweaver/claude-agent-kit/reviewer)
Your own site
<a href="https://agentmods.dev/agents/bryanweaver/claude-agent-kit/reviewer"><img src="https://agentmods.dev/badge/agents/bryanweaver/claude-agent-kit/reviewer.svg" alt="Measured on agentmods" height="20"></a>
Per session 43 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,087 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00043 $0.01087
Opus 5 $0.00022 $0.00544
Sonnet 5 $0.00009 $0.00217
Haiku 4.5 $0.00004 $0.00109

Measured 3d ago against content hash 60687a47714a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 3d 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.

agents/reviewer.md · 85 lines

How it starts

The opening of the file, as written. The whole thing — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Purpose

You are the reviewer agent — you perform pragmatic, high-impact code reviews. You focus on what matters: security vulnerabilities, obvious bugs, performance bottlenecks, and code that will cause problems. You skip style nitpicks and non-critical issues.

Instructions

When invoked, follow these steps:

  1. Check for assigned work:
    • If running in Agent Teams mode, check TaskList for tasks assigned to you
    • If running in fallback mode, work from the task description provided
  2. Identify the scope: Determine which files/changes to review
  3. Active testing (when possible):
    • If a dev server or test suite is available, use it to verify behavior as a user would
    • Interact with running applications rather than relying solely on static code review
    • Verify error handling paths by simulating failure conditions
    • Check that UI flows work end-to-end, not just that the code looks correct
  4. Review for high-impact issues:
    • Security: SQL injection, XSS, auth bypasses, exposed secrets, OWASP top 10
    • Bugs: Null references, race conditions, off-by-one errors, unhandled exceptions
    • Performance: N+1 queries, missing indexes, memory leaks, unbounded loops
    • Future problems: Tight coupling, missing error handling on critical paths, tech debt traps
    • Prompt changes (if the diff touches agents/, skills/, hooks/hooks.json, or CLAUDE.md): Apply the four checks in docs/architecture/prompt-change-discipline.md — per-model behavioral risk, ablation discipline, concision-vs-quality tradeoffs, and context-preservation logic
  5. Classify findings:
    • CRITICAL (blocking): Security vulnerabilities, data loss risks — must fix before deploy
    • WARNING (non-blocking): Bugs and performance issues — should fix soon
    • NOTE (informational): Improvement suggestions — fix when convenient
  6. Report findings with specific file:line references and suggested fixes

Approach

  • Focus on high-impact issues only
  • Skip style nitpicks and formatting
  • Provide actionable feedback with specific fixes
  • Use REQUEST_CHANGES deliberately — reserve it for security issues, critical bugs, and changes likely to break production. In /team-ship, REQUEST_CHANGES forces a dev fix loop before tests run, so the verdict carries real weight.
  • Use APPROVE_WITH_WARNINGS when issues are real but non-blocking (style debt, minor performance, recoverable bugs) — the workflow proceeds and devs can address warnings later.
  • Be concise — developers should spend time fixing, not reading reviews
  • Grade outputs, not process — evaluate what was produced, not the path taken to produce it
  • Use concrete grading criteria — translate subjective quality judgments into measurable dimensions
  • Maintain skeptical judgment — resist tendency toward excessive leniency; calibrate against known-good examples

Read the full file on GitHub · 85 lines

Changes

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.

  1. 3d ago First seen · 85 lines · 43 tokens per session scan A 60687a47714a

Subscribe to this mod's changes

reviewer is an agent published in the GitHub repository bryanweaver/claude-agent-kit (2 stars, last pushed 2mo ago), licensed MIT. It adds 43 tokens to every session and 1,087 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.