review

Audit Claude session transcripts and generate verdicts from Stop hook signals.

1|1|Updated Apr 13, 2026
One-click install
npx skills add https://github.com/Cheggin/request-for-startups --skill review-cheggin
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: review
Source: https://github.com/Cheggin/request-for-startups/tree/main/skills/review
Command: npx skills add https://github.com/Cheggin/request-for-startups --skill review-cheggin

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill provides third-party reviews of finished Claude sessions by reading completion signals, detecting patterns such as repeated skill invocations or plan-only runs, and surfacing actionable verdicts to guide improvements.

Core Features & Use Cases

  • Reads completion signals produced by the Stop hook and enumerates pending sessions awaiting review.
  • Analyzes transcripts for patterns like skill-heavy vs code-light loops, duplicates in skill invocations, and context thrash.
  • Writes formal verdicts to .harness/metrics/ and appends actionable learnings to .harness/learnings/knowledge.md to feed back into chain configuration.
  • Use cases include auditing autonomous runs, identifying failure modes, and informing future refinements of prompts and skill choreography.

Quick Start

Run the reviewer against all pending signals by executing the review.mjs script.

Frequently Asked Questions about review

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

FAQPage Schema
How do I audit Claude session transcripts for actionable insights?

Auditing Claude session transcripts involves reading completion signals stored during the Stop hook to generate deterministic verdicts for each session. The review process operates out-of-process to avoid bias and surfaces actionable learnings for future prompt refinement.

How do I review pending session signals from autonomous Claude runs?

Reviewing pending session signals requires executing the review script to process payloads stored under .harness/signals. The workflow targets either all pending signals or a specific signal file, analyzing them for patterns like skill-heavy loops or context thrash.

What is the best way to detect failure modes in autonomous Claude sessions?

Detecting failure modes in autonomous Claude sessions is done by analyzing completion signals for patterns like repeated skill invocations, plan-only runs, and duplicates. The process reads transcript metadata to identify these loops and writes formal verdicts to a metrics directory.

Does the Claude session review process store metrics and learnings in specific locations?

The Claude session review process enforces deterministic output paths, emitting metrics to .harness/metrics and appending actionable learnings to .harness/learnings/knowledge.md. This structured storage feeds back into chain configuration to guide improvements.

Can I analyze a specific signal file instead of all pending Claude session signals?

Analyzing a specific signal file instead of all pending Claude session signals is supported by the review workflow. You can target a single signal payload stored under .harness/signals to process individual sessions and generate a verdict without reviewing all pending files.

Why should I use an out-of-process workflow to review Claude sessions?

Using an out-of-process workflow to review Claude sessions ensures a simple, deterministic review that avoids bias. Operating externally from the active sessions allows the reviewer to objectively read completion signals and generate accurate verdicts without session interference.