fetch-pr-feedback

What This Skill Does

The fetch-pr-feedback skill is a powerful automation utility for OpenClaw that streamlines the code review process by aggregating feedback from GitHub pull requests. Instead of manually parsing through fragmented review comments, discussions, and line-specific suggestions, this skill automatically retrieves all relevant feedback from your PR. It filters out noise—such as the PR author’s own updates or the current user’s contributions—to provide a clean, actionable summary of what needs to be addressed. By leveraging the receive-feedback skill, it transforms raw GitHub comments into a structured analysis, allowing you to focus on resolving issues rather than hunting for them in the UI.

Installation

To integrate this skill into your OpenClaw environment, execute the following command in your terminal:

clawhub install openclaw/skills/skills/anderskev/fetch-pr-feedback

Ensure that you have the GitHub CLI (gh) configured and authenticated on your system, as this skill relies on the local environment to handle API interactions securely.

Use Cases

• Automated PR Summaries: Quickly generate a concise digest of reviewer suggestions before you begin your coding session.
• Feedback Synthesis: Evaluate complex, multi-reviewer threads to identify consensus or conflicting suggestions.
• Reviewer Accountability: Easily separate feedback from core maintainers versus casual observers to prioritize your response strategy.
• Context Restoration: If you are returning to an old PR, use this skill to instantly parse and understand pending feedback without re-reading the entire history.

Example Prompts

1. "@openclaw fetch-pr-feedback for PR #42 and summarize the main blockers."
2. "Please run fetch-pr-feedback on this branch, including comments from the author, so I can review my own context too."
3. "Fetch PR feedback for the current branch and pass it to receive-feedback so I can create a follow-up task list."

Tips & Limitations

• Filtering: The skill intelligently ignores common noise patterns, such as auto-generated AI analysis chains and standardized tips, ensuring you see only human-authored feedback.
• Truncation: To prevent overwhelming the AI context window, comments exceeding 4,000 characters are automatically truncated, appended with a truncation notice.
• Permissions: Ensure your GitHub CLI token has repo scope permissions to fetch comments successfully. If you encounter issues, try running gh auth status to confirm your authentication state.
• Dependencies: This skill works best when paired with the receive-feedback skill to interpret the resulting data.