What is 'Radical Transparency' in this context?

It is the practice of documenting every technical decision, categorization, and implementation step as a public comment in the PR thread for clarity, reviewer trust, and future reference.

How does this skill prevent future review comments?

The workflow includes a final codification step where it suggests updates to your project's rules or documentation to catch similar patterns automatically in future PRs.

How does this skill handle multiple feedback sources?

It uses the GitHub CLI to fetch and aggregate review comments, issue comments, and top-level review summaries via paginated API calls to ensure no feedback is missed.

Can I get second opinions on complex suggestions?

Yes, the skill is designed to use the Moonbridge MCP to spawn additional AI agents to provide external perspectives on architectural or controversial changes.

Transparent PR Review Response

Name: Transparent PR Review Response
Author: phrazzld

byphrazzld

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Collaboration Tools

Automates the pull request feedback lifecycle by categorizing comments, seeking second opinions, and documenting every technical decision publicly.

The Transparent PR Review Response skill streamlines the code review process by implementing a workflow centered on 'Radical Transparency.' It aggregates feedback from GitHub review comments, issue comments, and summaries, then uses a multi-agent approach via Moonbridge to provide second opinions on complex architectural decisions. By enforcing public documentation of every judgment—from categorizing fixes to narrating implementation steps—it creates a comprehensive audit trail that improves team communication, institutional memory, and overall code quality. Finally, it helps teams codify learnings into project rules to prevent recurring issues.

Key Features

01Public narration of implementation steps via real-time PR commenting

025 GitHub stars

03Automated categorization into Critical, In-scope, Follow-up, and Declined buckets

04Multi-agent reasoning using Moonbridge for complex architectural tradeoffs

05Multi-source feedback aggregation from GitHub review and issue comments

06Post-resolution codification to capture and automate preventive measures

Use Cases

01Managing high-volume code reviews with complex, overlapping feedback

02Standardizing documentation for architectural decisions within pull requests

03Onboarding new developers by providing a transparent history of technical trade-offs

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add phrazzld/claude-config respond

For use in Claude.ai and ChatGPT

Download Skill