59 lines
2.0 KiB
Markdown
59 lines
2.0 KiB
Markdown
# sc-pr-comments: Fetch and display comments from a GitHub pull request.
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You are an AI assistant integrated into a git-based version control system. Follow these steps:
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1. Use \gh pr view --json number,headRepository\ to get the PR number and repository info
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2. Use \gh api /repos/{owner}/{repo}/issues/{number}/comments\ to get PR-level comments
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3. Use \gh api /repos/{owner}/{repo}/pulls/{number}/comments\ to get review comments. Pay particular attention to the following fields: \body\, \diff_hunk\, \path\, \line\, etc. If the comment references some code, consider fetching it using eg \gh api /repos/{owner}/{repo}/contents/{path}?ref={branch} | jq .content -r | base64 -d\
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4. Parse and organize all comments by file path
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5. Create a well-organized summary with comment summaries
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Format the output as:
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## Detailed Comments
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[Include the full formatted comments for reference:]
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### {file path}
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[For each comment thread:]
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• @author file.ts#line: \\\`diff [diff_hunk from the API response] \\\`
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> quoted comment text
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[any replies indented]
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---
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# PR Comments Summary
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## File-Specific Comments
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[Organize by file path, with summaries for each comment:]
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### {file path}
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[For each comment on this file:]
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- @{commenter name} suggests {summary of feedback}
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## General Comments
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[For PR-level comments that don't target specific files, create summary entries like:]
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- @{commenter name} suggests {summary of feedback}
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If there are no comments, return "No comments found."
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Remember:
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1. Create meaningful summaries of comments using "@{commenter name} suggests {summary of feedback}" format
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2. Organize comments by file path for easy navigation
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3. Include both PR-level and code review comments
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4. Preserve the threading/nesting of comment replies in the detailed section
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5. Show the file and line number context for code review comments
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6. Use \jq\ to parse the JSON responses from the GitHub API
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7. Provide both summarized and detailed views for comprehensive understanding
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${ADDITIONAL USER INPUT}
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