Fetch GitHub pull request review data into canonical JSON and markdown reports.
npx skills add https://github.com/prisma/prisma --skill review-fetch-phase
Please help me install this Agent Skill. Skill: review-fetch-phase Source: https://github.com/prisma/prisma/tree/main/skills-contrib/review-fetch-phase Command: npx skills add https://github.com/prisma/prisma --skill review-fetch-phase
This skill eliminates the manual effort required to gather, validate, and summarize complex GitHub pull request review data, ensuring you have a clean, canonical state for triage.
Run the review-fetch-phase skill by providing the URL of the pull request you want to analyze and the directory where you want the artifacts saved.
High-intent search queries and answers about installing and using this skill.
To extract and normalize GitHub pull request review data, you can fetch unresolved threads, review bodies, and issue comments into a canonical JSON schema to generate deterministic markdown reports and triage targets.
Automating GitHub PR review state acquisition targets specific pull request URLs to fetch unresolved threads and comments, validating data integrity and enforcing artifact safety through git-ignore to ensure a clean canonical state.
Yes, you can generate machine-readable triage targets from GitHub pull request reviews by fetching and normalizing the review data into a versioned JSON format for downstream processing.
No specific external dependencies are required to run the GitHub PR review data extraction, as it operates through self-contained scripts provided by the official Prisma author.
To get a human-readable markdown summary of a large GitHub pull request review, provide the specific PR URL and target directory to automatically render comprehensive markdown summaries from the fetched review data.
When automating GitHub PR review state acquisition, note that it operates specifically on individual pull request URLs and enforces artifact safety through git-ignore, meaning it focuses on deterministic data extraction rather than interactive UI navigation.
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