Review

Orchestrates parallel multi-agent code review with severity classification and verification contract gating.

1|Updated Apr 25, 2026
One-click install
npx skills add https://github.com/htxryan/claude-code-config-profiles --skill review-htxryan
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: Review
Source: https://github.com/htxryan/claude-code-config-profiles/tree/main/.agents/skills/compound/review
Command: npx skills add https://github.com/htxryan/claude-code-config-profiles --skill review-htxryan

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? Code reviews often miss critical issues because a single reviewer cannot cover security, architecture, performance, testing, and design simultaneously, and past lessons are forgotten between sessions. ## Core Features & Use Cases - Parallel Multi-Agent Review: Spawns specialized reviewers (security, architecture, performance, test-coverage, simplicity, and more) in an AgentTeam, scaling from 4 reviewers for small diffs to 13+ for large ones. - Lesson-Calibrated Reviewers: Pre-loads each reviewer with 3-5 relevant past lessons via memory search, with contradiction detection escalated to humans instead of auto-resolved. - Contract-Driven Verification: Validates Acceptance Criteria and Verification Contract evidence from the epic, conditionally triggering runtime verification, QA engineering, design craft review, and Playwright screenshots. - Use Case: After implementing a feature touching UI and API code, run this skill to verify every acceptance criterion, capture browser evidence at four viewports, classify all findings P0-P3, and block merge until the implementation-reviewer gate approves. ## Quick Start Ask the AI to run the review skill on the current epic's implementation to verify acceptance criteria and produce a severity-classified review report.

Frequently Asked Questions about Review

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run a multi-agent code review on a pull request?▼

Invoke the review skill against the current epic; it reads the epic description, runs baseline quality gates, then spawns specialized reviewers in parallel based on diff size. Findings are consolidated, deduplicated, and classified by severity before a final approval gate.

How many reviewers run for different diff sizes?▼

Small diffs under 100 lines use 4 core reviewers covering security, test coverage, simplicity, and Codex patterns. Medium diffs of 100-500 lines add architecture, performance, and scenario reviewers for 9 total, while large diffs over 500 lines run all reviewers.

What is lesson-calibrated review and how does it work?▼

Each reviewer is pre-loaded with 3-5 relevant past lessons retrieved via memory search, filtered by domain match and recency. If a finding contradicts a high-severity lesson, the contradiction is escalated to a human rather than auto-resolved.

When does runtime verification or browser screenshot evidence run?▼

Runtime verification and Playwright screenshots run only when the epic's Verification Contract requires evidence such as runtime_startup, browser_evidence, or responsive_check. Non-UI projects without these contract entries skip the step and record an informational note.

What happens if the epic has no Acceptance Criteria section?▼

A missing Acceptance Criteria section is flagged as a P1 process finding, since the plan phase should have generated the table. The review still proceeds against baseline quality gates and risk-based evidence requirements.

Can the review complete with unresolved P1 findings?▼

No. All P1 findings must be fixed, all acceptance criteria must pass, and the implementation-reviewer must return APPROVED before the phase gate allows proceeding. P1 findings also create tracked issues for follow-up.