A command that runs a full codebase audit by assigning different reviewers to areas such as security, architecture, performance, and testing, then combines their findings.

Use it for broad repository reviews and to produce a REVIEW_REPORT.md file with findings from specialist reviewers.

It provides one consolidated report instead of requiring separate manual reviews across many technical concerns.

reviewcrew — Command for Claude Code by RashadAnsari

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.

Clone the repo

git clone --depth 1 https://github.com/RashadAnsari/myagents

Made for: Claude Code.

Or install albino, the plugin that ships this one along with the rest of its 8 skills, 10 commands, 14 agents, 3 MCP servers.

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.

README.md

[![agentmods](https://agentmods.dev/badge/commands/rashadansari/myagents/reviewcrew/github.svg)](https://agentmods.dev/commands/rashadansari/myagents/reviewcrew)

Your own site

<a href="https://agentmods.dev/commands/rashadansari/myagents/reviewcrew"><img src="https://agentmods.dev/badge/commands/rashadansari/myagents/reviewcrew/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.

Your own site · 80×15

<a href="https://agentmods.dev/commands/rashadansari/myagents/reviewcrew"><img src="https://agentmods.dev/badge/commands/rashadansari/myagents/reviewcrew.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 23 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 883 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

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.

Model	Per session	Once invoked
Fable 5.1	$0.00023	$0.00883
Opus 5	$0.00012	$0.00441
Sonnet 5	$0.00005	$0.00177
Haiku 4.5	$0.00002	$0.00088

Measured yesterday against content hash 75b32861a1c1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

reviewcrew 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 yesterday.

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.

plugins/albino/commands/reviewcrew.md · 66 lines

How it starts

The opening of the file, as written. The whole thing — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Review Crew

Spawn all specialist review agents in parallel, collect their findings, and write a single consolidated report to REVIEW_REPORT.md in the project root.

Step 1: Load Memory

Before spawning any reviewer, call project_search and user_search with relevant terms to load project conventions and user preferences. Use findings to inform how you brief each reviewer and to flag known gotchas or decisions that are relevant to the review.

Step 2: Spawn All Reviewers in Parallel

Spawn all of the following agents simultaneously. Do not wait for one to finish before starting the next. Each agent prompt MUST begin with:

MANDATORY: Read AGENTS.md and follow its rules before doing anything.

Agents to spawn in parallel:

security-reviewer: security vulnerabilities across all categories
code-reviewer: correctness, style, patterns, anti-patterns
architecture-reviewer: structure, coupling, separation of concerns, SOLID
performance-reviewer: bottlenecks, complexity, memory, queries
test-reviewer: coverage, quality, missing cases, flakiness
logging-reviewer: logging gaps, monitoring, audit trail
dependency-reviewer: outdated, vulnerable, unused packages
docs-reviewer: accuracy, completeness, staleness
agents-md-reviewer: AGENTS.md rule inconsistencies
accessibility-reviewer: WCAG compliance, ARIA, keyboard navigation, screen reader compatibility
api-design-reviewer: REST/GraphQL naming, HTTP semantics, versioning, error shape, backward compatibility
database-reviewer: schema design, migration safety, indexing, constraints, query patterns
i18n-reviewer: hardcoded strings, date/number formatting, pluralization, RTL, locale handling
unused-code-reviewer: unused code, tests, CI, infrastructure, containers, scripts, schema, config, docs, and assets

Step 3: Collect All Results

Wait for all agents to complete. Collect every finding from every agent. Do not discard or summarize findings: preserve the full output of each reviewer.

Read the full file on GitHub · 66 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.

yesterday Changed · +1 lines 75b32861a1c1
9d ago First seen · 65 lines · 23 tokens per session scan A 9312dabc7e20

Subscribe to this mod's changes

reviewcrew is a command published in the GitHub repository RashadAnsari/myagents (6 stars, last pushed 2d ago), licensed MIT. It adds 23 tokens to every session and 883 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 2026-08-31.

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