fetch-star-repos

name	fetch-star-repos
description	Fetch GitHub starred repos, analyze one with LLM, and propose improvements via PR
allowed-tools	Bash, Read
user-invocable	true

Fetch Stars & Analyze — GitHub Stars to Improvement PRs

Fetches your recently starred GitHub repos (last 30 days), then runs the research scout to analyze ONE repo and propose concrete code improvements via PR.

Steps

1. Load env vars from .env.local and fetch starred repos:

set -a && source .env.local && set +a && LOOKBACK_DAYS=30 python3 scripts/fetch_github_stars.py

Required env vars in .env.local:

• GITHUB_USERNAME — Your GitHub username
• OPENROUTER_API_KEY — For LLM analysis

2. Show the updated bookmarks count:

cat .claude/bookmarks.json | python3 -c "import sys,json; bm=json.load(sys.stdin); print(f'Total starred repos: {len(bm)}'); [print(f'  - [{b.get(\"source\",\"?\")}] {b[\"url\"][:80]}') for b in bm[-10:]]"

3. Run the research scout (analyzes ONE unprocessed repo via LLM):

set -a && source .env.local && set +a && LOOKBACK_DAYS=30 python3 scripts/run_research_scout.py

4. If improvements were found (.claude/research-scout-findings.md exists), create a PR:

BRANCH="research-scout/$(date +%Y-%m-%d-%H%M)"
git checkout -b "$BRANCH"
git add .claude/research-scout-state.json .claude/bookmarks.json .claude/research-scout-findings.md
git commit -m "research-scout: improvement proposal from $(date +%Y-%m-%d)"
git push -u origin "$BRANCH"
gh pr create --title "research-scout: improvement proposal $(date +%Y-%m-%d)" --body "$(cat .claude/research-scout-findings.md)" --label "research-scout"
git checkout main

Output

Report: how many repos were fetched, which repo was analyzed, what improvements were proposed, and whether a PR was created.