team-review

team-review is a command for coding agents from wshobson/agents. It costs 12 tokens per session (726 once invoked), scanned A, original, MIT.

A command that coordinates several specialized code reviewers at the same time and combines their findings into one report.

In plain words
What is it for?
Use it to review files, folders, code changes, or pull requests with selected review areas and a chosen base branch.
Why use it?
Different reviewers can inspect separate concerns, such as security, performance, and architecture, so problems are less likely to be overlooked.

Command

Part of the agent-teams plugin — 6 skills, 7 commands, 4 agents shipped together

About the project

Agentic Plugin Marketplace is a collection of reusable plugins, agents, skills, commands, and rules for coding-agent tools including Claude Code, Codex CLI, Cursor, OpenCode, Antigravity CLI, and GitHub Copilot. It is for developers assembling agentic workflows across multiple harnesses from shared Markdown sources, and the catalogue entries are examples or subsets of those workflow components.

wshobson/agents · 39,428 stars · on GitHub · sethhobson.com

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 commands/wshobson/agents/team-review
Clone the repo
git clone --depth 1 https://github.com/wshobson/agents

Or install agent-teams, the plugin that ships this one along with the rest of its 6 skills, 7 commands, 4 agents.

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 team-review

README.md
[![agentmods](https://agentmods.dev/badge/commands/wshobson/agents/team-review.svg)](https://agentmods.dev/commands/wshobson/agents/team-review)
Your own site
<a href="https://agentmods.dev/commands/wshobson/agents/team-review"><img src="https://agentmods.dev/badge/commands/wshobson/agents/team-review.svg" alt="Measured on agentmods" height="20"></a>
Per session 12 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 726 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 5.1 $0.00012 $0.00726
Opus 5 $0.00006 $0.00363
Sonnet 5 $0.00002 $0.00145
Haiku 4.5 $0.00001 $0.00073

Measured 6d ago against content hash 4082b340224f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

team-review 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 6d 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

plugins/agent-teams/commands/team-review.md · 79 lines

How it starts

The opening of the file, as written. The whole thing — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Team Review

Orchestrate a multi-reviewer parallel code review where each reviewer focuses on a specific quality dimension. Produces a consolidated, deduplicated report organized by severity.

Pre-flight Checks

  1. Verify CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1 is set
  2. Parse $ARGUMENTS:
    • <target>: file path, directory, git diff range (e.g., main...HEAD), or PR number (e.g., #123)
    • --reviewers: comma-separated dimensions (default: security,performance,architecture)
    • --base-branch: base branch for diff comparison (default: main)

Phase 1: Target Resolution

  1. Determine target type:
    • File/Directory: Use as-is for review scope
    • Git diff range: Use Bash to run git diff {range} --name-only to get changed files
    • PR number: Use Bash to run gh pr diff {number} --name-only to get changed files
  2. Collect the full diff content for distribution to reviewers
  3. Display review scope to user: "{N} files to review across {M} dimensions"

Phase 2: Team Spawn

  1. Use TeamCreate tool to create the team with team_name: "review-{timestamp}" and description
  2. For each requested dimension, use Agent tool to spawn a teammate:
    • name: {dimension}-reviewer (e.g., "security-reviewer")
    • subagent_type: "agent-teams:team-reviewer"
    • prompt: Include the dimension assignment, target files, and diff content
  3. Use TaskCreate for each reviewer's task:
    • Subject: "Review {target} for {dimension} issues"
    • Description: Include file list, diff content, and dimension-specific checklist

Phase 3: Monitor and Collect

  1. Wait for all review tasks to complete (check TaskList periodically)
  2. As each reviewer completes, collect their structured findings
  3. Track progress: "{completed}/{total} reviews complete"

Phase 4: Consolidation

  1. Deduplicate: Merge findings that reference the same file:line location
  2. Resolve conflicts: If reviewers disagree on severity, use the higher rating
  3. Organize by severity: Group findings as Critical, High, Medium, Low
  4. Cross-reference: Note findings that appear in multiple dimensions

Read the full file on GitHub · 79 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. 6d ago First seen · 79 lines · 12 tokens per session scan A 4082b340224f

Subscribe to this mod's changes

team-review is a command published in the GitHub repository wshobson/agents (39,428 stars, last pushed 3d ago), licensed MIT. It adds 12 tokens to every session and 726 once invoked, about $0.0001 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.