peer-review

Coordinate multi-perspective code reviews using a blackboard architecture.

Updated Mar 1, 2026
One-click install
npx skills add https://github.com/dnhess/spectra --skill peer-review-dnhess
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: peer-review
Source: https://github.com/dnhess/spectra/tree/main/peer-review
Command: npx skills add https://github.com/dnhess/spectra --skill peer-review-dnhess

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill orchestrates structured, multi-perspective code reviews to improve quality and catch issues before merges.

Core Features & Use Cases

  • Structured multi-perspective review: coordinates Scout, Research, and reviewer agents using a blackboard architecture to surface diverse findings.
  • Session management: handles session creation, progress tracking, and synthesis of findings into a final document.
  • Usage scenarios: triggers include PRs, feature branches, or major refactors requiring rigorous scrutiny.

Quick Start

Conduct a peer-review session on the target codebase to produce a synthesized set of review findings.

Frequently Asked Questions about peer-review

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

FAQPage Schema
How do I automate multi-perspective code reviews for a feature branch?

Multi-perspective code review automation coordinates Scout, Research, and reviewer agents through a blackboard architecture to surface diverse findings. It enforces session lifecycle management to produce consumable review outputs for feature branches and modules.

What is a blackboard architecture for structured code review?

Blackboard architecture for code review coordinates independent Scout, Research, and reviewer agents to share findings on a common workspace. This enables synthesized, multi-perspective assessment of diffs and modules before merges.

How do I run a structured code review on a major refactor?

Run structured code review on major refactors by triggering a session on the target codebase. The session handles progress tracking and synthesizes agent findings into a final document with ADR-style documentation.

Does automated peer-review work on diffs and pull requests?

Automated peer-review works on diffs, pull requests, feature branches, and modules requiring rigorous scrutiny. It orchestrates session creation and synthesis to output consumable review findings tailored to the target codebase changes.

What is the best way to document code review findings for architecture decisions?

Document code review findings for architecture decisions by synthesizing multi-perspective agent outputs into ADR-style documentation. The review session lifecycle automatically progresses from tracking to final document generation.

When should I use multi-agent code review instead of a standard single-pass review?

Use multi-agent code review for major refactors, feature branches, or modules requiring rigorous scrutiny where standard single-pass reviews miss diverse issues. The blackboard architecture coordinates distinct agent perspectives to surface comprehensive findings.