feat(iterate-pr): Add scripts for structured CI and feedback data#34
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feat(iterate-pr): Add scripts for structured CI and feedback data#34
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Add helper scripts that pre-process GitHub API data to reduce token usage and improve feedback categorization: - fetch_pr_checks.py: Fetches CI checks and extracts relevant failure snippets using pattern matching instead of full logs - fetch_pr_feedback.py: Categorizes PR feedback as blocking, suggestion, bot, or resolved Update SKILL.md to: - Reference the optional helper scripts with fallback to gh commands - Add Step 6 for handling subjective feedback with user prompts - Present suggestion-type feedback as numbered list for user selection Co-Authored-By: Claude <noreply@anthropic.com>
Restructure SKILL.md to follow OpenAI skill patterns: - Scripts are now the primary approach, not optional - Reduced from 185 to 131 lines by removing redundant gh CLI docs - Moved fallback commands to a single section at the end - Clearer workflow with numbered steps Co-Authored-By: Claude <noreply@anthropic.com>
trevor-e
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Feb 3, 2026
plugins/sentry-skills/skills/iterate-pr/scripts/fetch_pr_feedback.py
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Update fetch_pr_feedback.py to detect and use Sentry's LOGAF scale: - h: / [h] / high: → high priority (must fix) - m: / [m] / medium: → medium priority (should fix) - l: / [l] / low: → low priority (optional) Categories renamed from blocking/suggestion to high/medium/low to align with Sentry's code review guidelines. Refs: https://develop.sentry.dev/engineering-practices/code-review/#logaf-scale Co-Authored-By: Claude <noreply@anthropic.com>
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Add helper scripts that pre-process GitHub API responses to reduce token usage and improve the iterate-pr workflow.
Inspired by OpenAI's agent skills which use scripts to extract only relevant information rather than dumping raw API output.
Scripts:
fetch_pr_checks.py- Fetches CI check status and extracts failure snippets:fetch_pr_feedback.py- Fetches and categorizes PR review feedback:blocking,suggestion,bot,resolvedSKILL.md changes:
ghCLI documentation