code-review

Diff branch changes against a base and generate scored findings reports.

226|55|Updated Mar 19, 2026
One-click install
npx skills add https://github.com/Miosa-osa/canopy --skill code-review-miosa-osa
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: code-review
Source: https://github.com/Miosa-osa/canopy/tree/main/library/skills/development/code-review
Command: npx skills add https://github.com/Miosa-osa/canopy --skill code-review-miosa-osa

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Branch code reviews are slow and error-prone; this skill provides a structured review workflow that scores changes against project guidelines, surfaces categorized findings with severities, and generates LLM-based fix prompts to guide remediation.

Core Features & Use Cases

  • Scored reports with categorized findings and severity levels
  • Auto-generated prompts for fixes that can be executed by an LLM
  • Quality gate: post review to PR if score meets threshold
  • Supports diff-based review between base and target branches, with configurable base and branch
  • Flexible output formats (markdown or JSON) for CI integration

Quick Start

Run the /code-review command to review your current branch against the main baseline and produce a structured report.

Frequently Asked Questions about code-review

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

FAQPage Schema
How do I automate code reviews on a pull request branch?▼

Automate code reviews by diffing changes against a base branch and producing a scored findings report with actionable fix prompts. The review prioritizes logic and tests, generating a final pass/fail verdict for your pull request.

How does a quality gate work for pull request code reviews?▼

A quality gate evaluates the review score against a threshold and posts the review to the pull request if it meets requirements. This gates merges by surfacing categorized findings and severities directly on the pull request.

Can I generate code review reports in JSON format for CI workflows?▼

Yes, code review reports support flexible output formats including JSON and markdown for CI integration. The report contains categorized findings, severity levels, and auto-generated LLM fix prompts to guide remediation.

What is the best way to get actionable fix prompts for code review findings?▼

Generate actionable fix prompts by running a structured code review that scores changes against project guidelines. The review automatically categorizes findings by severity and produces LLM-based prompts to guide remediation.

Does automated code review work across multiple programming languages?▼

Yes, automated code review applies across languages by diffing branch changes against a configurable base. It prioritizes logic and tests to produce a scored report with a pass/fail verdict regardless of language.

Why use scored findings reports instead of manual code reviews?▼

Scored findings reports replace slow, error-prone manual reviews by structuring the review workflow against project guidelines. This surfaces categorized findings with severities and generates actionable fix prompts for faster remediation.