Automated maintenance scripts for the AgentReady research report.

The update_research.py script runs weekly via GitHub Actions to:

1. Search for recent research on AI-assisted development
2. Analyze relevance using Claude API
3. Update agent-ready-codebase-attributes.md with new citations
4. Create a pull request for review

pip install anthropic pyyaml requests python-dotenv

export ANTHROPIC_API_KEY="sk-ant-api03-..."

Edit research_config.yaml to customize:

• max_updates_per_run: How many attributes to update per week
• min_citation_quality_score: Threshold for including updates
• priority_attributes: Which attributes get updated first

python scripts/update_research.py

# Verify config loads correctly
python -c "import yaml; print(yaml.safe_load(open('scripts/research_config.yaml')))"

The workflow runs automatically every Monday at 9 AM UTC.

Manual trigger:

gh workflow run research-update.yml

View recent runs:

gh run list --workflow=research-update.yml

• 0: Changes made, PR should be created
• 1: No changes needed or error occurred

• agent-ready-codebase-attributes.md: Research report content
  • Updated attribute sections with new findings
  • New citations added
  • Version incremented
  • Date updated to current

update_settings:
  max_updates_per_run: 5          # Limit changes per PR
  min_citation_quality_score: 0.7  # Claude relevance threshold
  search_recency_months: 12        # Only recent research

priority_attributes:
  - "1.1"  # CLAUDE.md
  - "2.1"  # README
  # ... Tier 1 attributes processed first

search_domains:
  prioritized:
    - anthropic.com
    - arxiv.org
    # ... High-authority sources
  blocked:
    - spam-site.com
    # ... Low-quality sources to avoid

from update_research import ResearchUpdater

updater = ResearchUpdater()
results = updater.search_recent_research("1.1", "CLAUDE.md Configuration Files")
print(f"Found {len(results)} results")

from update_research import ResearchUpdater

updater = ResearchUpdater()
analysis = updater.analyze_relevance(
    "1.1",
    search_results,
    "Current attribute content..."
)
print(f"Relevance score: {analysis['relevance_score']}")

# Comment out the write operations in update_attribute_section()
# to test without modifying files

Possible causes:

• min_citation_quality_score too high
• No recent research found
• Search API issues

Solutions:

• Lower threshold in config
• Check search functionality manually
• Verify API credentials

Possible causes:

• Script exited with code 1 (no changes)
• GitHub Actions permissions issue
• Branch conflicts

Solutions:

• Check workflow logs: gh run view --log
• Verify repository permissions
• Delete stale automated/research-update branch

Claude API:

• Default: 1,000 requests/minute
• Cost: ~$0.30 per weekly run
• Caching: Search results cached 7 days

Mitigation:

• Reduce max_updates_per_run
• Increase search_recency_months (fewer new results)

• Search generation: 5 × ~2K tokens = 10K tokens
• Relevance analysis: 5 × ~6K tokens = 30K tokens
• Total: ~40K tokens/week ≈ $0.30/week

• ~$15-20/year for weekly automation
• Scales linearly with max_updates_per_run

• Store only in GitHub Secrets (never commit)
• Rotate quarterly or after team changes
• Use least-privilege API keys

• All URLs verified before adding
• Malicious content filtered
• JSON parsing validated to prevent injection

• research-update.skill.md: Complete skill documentation
• .github/workflows/research-update.yml: GitHub Actions workflow
• agent-ready-codebase-attributes.md: The research report

Last Updated: 2025-12-03 Maintainer: Jeremy Eder