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 skills add RashadAnsari/myagents --skill reviewcrewgit clone --depth 1 https://github.com/RashadAnsari/myagentsWrote 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/skills/rashadansari/myagents/reviewcrew)<a href="https://agentmods.dev/skills/rashadansari/myagents/reviewcrew"><img src="https://agentmods.dev/badge/skills/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.
<a href="https://agentmods.dev/skills/rashadansari/myagents/reviewcrew"><img src="https://agentmods.dev/badge/skills/rashadansari/myagents/reviewcrew.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 | $0.00026 | $0.00896 |
| Opus 5.5 | $0.00010 | $0.00358 |
| Sonnet 5.5 | $0.00005 | $0.00179 |
| Haiku 4.5 | $0.00003 | $0.00090 |
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.
How it starts
The opening of the file, as written. The whole thing — 68 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.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 First seen · 68 lines · 26 tokens per session scan A e307a174c055
reviewcrew is a skill published in the GitHub repository RashadAnsari/myagents (6 stars, last pushed today), licensed MIT. It adds 26 tokens to every session and 896 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 2026-10-15.
Other skills, from other repositories
code-review
Review a diff against its acceptance criteria in four segments (convention adherence, bug scan, historical-context regressions, test-coverage gaps) as a NON-implementing agent. Findings are sorted by severity, each with file:line + a failure scenario. A planted defect must be caught; a clean diff must not be…
design-review
Five-dimension design audit (frontend UI/UX · server data-model & flow · endpoint spec · daemon-runtime/SDK & local-cache-first · built-in skill/agent-role), executed by a NON-implementing agent. Every dimension gets a verdict; N/A only with a stated reason. A dimension the design silently skipped must be surfaced as…
codebase-design
Design maintainable module interfaces, review scoped code changes, and simplify implementations with behavioral verification. Use for code review, cleanup, testability, and module design work.
prismer-github
GitHub via gh CLI: PRs, issues, reviews, repos, auth.
requirements-authoring-flow
Workflow for authoring requirements and specifications: drafting, review, validation, etc.
pr-reviewer
Review a requested pull request, branch diff or completed task against its actual scope, source and checks. Prepare evidence and comments; post or record a human verdict only when explicitly authorized.