post-implementation-review

Runs a parallel review swarm with a deterministic checklist to verify completed implementations.

Updated Dec 24, 2025
One-click install
npx skills add https://github.com/JoyJoin-Tech-Limited/JoyJoin_app_v0.1 --skill post-implementation-review-joyjoin-tech-limited
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: post-implementation-review
Source: https://github.com/JoyJoin-Tech-Limited/JoyJoin_app_v0.1/tree/main/.github/skills/post-implementation-review
Command: npx skills add https://github.com/JoyJoin-Tech-Limited/JoyJoin_app_v0.1 --skill post-implementation-review-joyjoin-tech-limited

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? After an implementation agent finishes work, free-form LLM critique produces inconsistent reviews with invented criteria and nit-chasing. This Skill replaces ad-hoc critique with a deterministic checklist so every review evaluates the same items with the same severity, and only blocking issues trigger fix loops. ## Core Features & Use Cases - Parallel Review Swarm: Spawns Auto-Eval, QA Agent, Verifier, PM Advisor, and conditional Visual Designer and User Satisfaction Auditor agents, each running a fixed checklist from review-checklist-manifest.json. - Severity-Gated Verdicts: Converges findings into PASS, PARTIAL, or FAIL based only on BLOCKING items; CONCERN and NIT findings are logged without triggering fix loops. - Cost-Controlled Swarm Sizing: Scales from 2 agents for trivial changes up to 6 for UI-affecting or Sprint Contract work, with an adaptive escalation ladder capping fix iterations. - Use Case: After an implementation agent records turnStatus: done on a multi-file UI change, run the review swarm to verify the harness gate passes, claimed files exist, tests were added, and rendered screens have no text overflow before sign-off. ## Quick Start Run a post-implementation review on the turn that just completed and report the verdict with any blocking findings.

Frequently Asked Questions about post-implementation-review

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

FAQPage Schema
How do I run a post-implementation review after an agent finishes coding?

Trigger the review once the implementation agent records turnStatus: done. The supervisor loads review-checklist-manifest.json, spawns the parallel swarm sized to the change, and converges findings into a PASS, PARTIAL, or FAIL verdict.

What is a deterministic review checklist for AI code review?

It is a fixed manifest of checklist items with preset severities that every review agent evaluates identically each time. This replaces free-form prose critique, which causes LLM reviewers to invent new criteria and produce inconsistent results.

When should the post-implementation review not be used?

Skip it when the turn modified zero files, when skipReview: true is set in the turn summary, or when the agent is not an implementation agent. Running it in those cases wastes review capacity on nothing to inspect.

How does the review swarm decide between PASS, PARTIAL, and FAIL?

The verdict depends only on blocking items: zero blocking and zero concerns yields PASS, zero blocking with one to three concerns yields PARTIAL, and one or more blocking findings yields FAIL. Concerns and nits are logged but never trigger fix loops.

Why does the review limit free-form findings per agent?

Each agent is capped at three free-form findings and every finding must cite a checklist item ID. This forces checklist discipline, prevents nit-chasing and over-polishing, and keeps re-reviews consistent via the review fingerprint.

Does the review support delta review of only changed items?

Delta review is designed but not implemented; no persistence layer exists, so every review runs full and stateless. The delta_review_rules.enabled flag in the manifest is false to match that reality.