swarm-code-review

Coordinate multi-lane code reviews by specialist agents and aggregate findings into a prioritized report.

Updated Apr 16, 2026

Search Tags:#automation #aggregation #swarm #evidence #code-review #lanes

Ready to run

npx skills add https://github.com/seshxn/ai-swarm --skill swarm-code-review

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: swarm-code-review
Source: https://github.com/seshxn/ai-swarm/tree/main/skills/swarm-code-review
Command: npx skills add https://github.com/seshxn/ai-swarm --skill swarm-code-review

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Coordinating code reviews across multiple specialist agents and preserving evidence for accountability and traceability.

Core Features & Use Cases

Multi-lane reviewer orchestration: assigns code surfaces to specialist roles (security, performance, maintainability) and aggregates findings.
Evidence-preserving aggregation: deduplicates, prioritizes issues, and preserves source attribution across lanes.
Final merged report: returns a prioritized, testable summary for human decision-making.

Quick Start

Trigger a PR review by assigning surfaces to specialist lanes and let the swarm aggregate findings into a final prioritized report.

Frequently Asked Questions about swarm-code-review

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

FAQPage Schema

How do I automate multi-lane code reviews for pull requests?▼

Automate multi-lane code reviews by assigning pull request surfaces to specialist agents, which then aggregate findings into a single prioritized report. This preserves evidence and deduplicates issues across lanes.

What is evidence-preserving aggregation in code review automation?▼

Evidence-preserving aggregation merges duplicate findings from multiple specialist review lanes while retaining source attribution. It ensures traceability and accountability by preserving the original evidence for each issue.

How do I coordinate multiple specialist agents to review security and performance separately?▼

Coordinate specialist agents by assigning distinct review lanes for security, performance, maintainability, and style. Each lane evaluates the code independently before the aggregator merges the results.

Can I merge duplicate code review findings from different analysis scenarios?▼

Yes, the aggregation process merges duplicate findings identified across different review lanes. It consolidates the issues while preserving the underlying evidence and source attribution for the final report.

What is the best way to generate a prioritized code review report across different categories?▼

Generate a prioritized report by orchestrating multiple specialist agents across security and performance lanes, then aggregating their findings. The final merged output ranks issues for human decision-making.

Does this multi-lane code review approach work for maintainability and style scenarios?▼

Yes, the multi-lane code review orchestration explicitly supports maintainability and style scenarios. Specialist lanes evaluate these areas independently before merging their findings into the final report.