Anthropic Docs Updater

Overview

anthropic-docs-updater automatically keeps the anthropic-expert skill current by detecting, fetching, and integrating Anthropic documentation updates.

Purpose: Automated documentation maintenance for anthropic-expert

Update Workflow (5 steps):

1. Check for Updates - Detect new releases and documentation changes
2. Fetch Documentation - Download updated content from official sources
3. Process Content - Convert to skill reference format
4. Update Skill - Integrate new content into anthropic-expert
5. Validate Updates - Ensure quality maintained, no regressions

Automation: 80% automated (manual review for breaking changes)

Update Sources:

• GitHub Releases (SDK version updates)
• docs.claude.com/en/release-notes (API updates)
• code.claude.com/docs/en/changelog (Claude Code updates)
• anthropic.com/news (model announcements)

When to Use

• Weekly/monthly update checks (stay current)
• After Anthropic announces new features
• Before starting new Anthropic project (ensure latest docs)
• When anthropic-expert seems outdated
• Automated scheduled updates (cron job)

Prerequisites

• anthropic-expert skill installed
• Python 3.7+ with requests library
• GitHub API access (for release checking)
• Internet access (for fetching docs)

Update Workflow

Step 1: Check for Updates

Purpose: Detect new releases, documentation changes, feature announcements

Process:

1. Check GitHub Releases

   python scripts/check-updates.py --github

   • Queries GitHub API for latest releases
   • Checks: anthropic-sdk-python, claude-agent-sdk-python
   • Compares to current versions in changelog.md
   • Reports new releases found

2. Check Release Notes

   python scripts/check-updates.py --docs

   • Fetches docs.claude.com/en/release-notes
   • Compares to last check date
   • Identifies new entries

3. Check Claude Code Changelog

   python scripts/check-updates.py --claude-code

   • Fetches code.claude.com/docs/en/changelog
   • Detects new versions or features

4. Generate Update Report

   python scripts/check-updates.py --all

   • Runs all checks
   • Aggregates findings
   • Outputs: update-report.txt with detected changes

Validation:

• GitHub releases checked
• Release notes checked
• Claude Code changelog checked
• Update report generated
• New updates detected (or confirmed current)

Outputs:

• update-report.txt (what's new)
• List of detected changes
• Recommended update actions

Time Estimate: 10-15 minutes (automated)

Example Output:

Anthropic Documentation Update Check
=====================================
Date: 2025-11-15

GitHub Releases:
✅ anthropic-sdk-python: v0.45.0 (current: v0.42.0) - UPDATE AVAILABLE
✅ claude-agent-sdk-python: v1.12.0 (current: v1.10.0) - UPDATE AVAILABLE

Release Notes (docs.claude.com):
✅ New feature: Batch API cost reduction increased to 60%
✅ New model: Claude Sonnet 4.6 announced

Claude Code Changelog:
- No new updates since last check

Recommendation: UPDATE AVAILABLE
- 2 SDK updates
- 2 API feature updates
- Proceed to Step 2 (Fetch Documentation)

Step 2: Fetch Documentation

Purpose: Download updated content from official sources

Process:

1. Fetch SDK Documentation

   python scripts/fetch-docs.py --github-readmes

   • Downloads README.md from SDK repositories
   • Gets changelog/release notes from GitHub
   • Saves to temp/sdk-docs/

2. Fetch API Documentation

   python scripts/fetch-docs.py --api-docs

   • Fetches updated pages from docs.claude.com
   • Downloads release notes
   • Saves to temp/api-docs/

3. Fetch Claude Code Documentation

   python scripts/fetch-docs.py --claude-code-docs

   • Fetches updated pages from code.claude.com
   • Downloads changelog
   • Saves to temp/claude-code-docs/

4. Verify Downloads

   • Check all files downloaded successfully
   • Validate file integrity
   • Confirm no download errors

Validation:

• SDK docs fetched successfully
• API docs fetched successfully
• Claude Code docs fetched (if updates)
• All files saved to temp directory
• No download errors

Outputs:

• temp/sdk-docs/ (SDK documentation)
• temp/api-docs/ (API documentation)
• temp/claude-code-docs/ (Claude Code documentation)
• fetch-log.txt (download log)

Time Estimate: 15-30 minutes (automated, depends on amount of content)

Step 3: Process Documentation

Purpose: Convert fetched content to skill reference format

Process:

1. Parse Fetched Documentation

   python scripts/process-docs.py --input temp/ --output processed/

   • Parses markdown from temp/
   • Extracts relevant sections
   • Identifies code examples
   • Structures by product

2. Convert to Reference Format

   • Organize by product/capability
   • Format consistently with existing references
   • Extract code examples properly
   • Add navigation headers

3. Merge with Existing Content

   • Compare new vs existing documentation
   • Identify additions, changes, removals
   • Preserve custom examples/notes
   • Generate diff report

4. Validate Processed Content

   • Check markdown syntax
   • Verify code examples
   • Ensure consistent formatting

Validation:

• All fetched docs processed
• Content converted to reference format
• Organized by product/capability
• Code examples extracted correctly
• Diff report generated (what changed)
• Processed content validated

Outputs:

• processed/ (processed documentation)
• diff-report.txt (what changed)
• Formatted content ready for integration

Time Estimate: 20-40 minutes (automated with manual review of diff)

Step 4: Update anthropic-expert Skill

Purpose: Integrate new content into anthropic-expert skill safely

Process:

1. Backup Current Skill

   python scripts/update-skill.py --backup

   • Creates backup of anthropic-expert
   • Saves to anthropic-expert.backup-YYYYMMDD/
   • Preserves all files

2. Integrate New Content

   python scripts/update-skill.py --integrate processed/

   • Updates relevant reference files
   • Adds new features to appropriate sections
   • Preserves custom content
   • Updates changelog.md with changes

3. Update Version

   • Increments version number
   • Updates changelog with:
     • Version number
     • Date
     • Changes summary
     • New features
     • Updated documentation

4. Review Changes

   • Display diff of what changed
   • Prompt for confirmation (if manual mode)
   • Allow rollback if issues

Validation:

• Current skill backed up
• New content integrated successfully
• Changelog updated with version and changes
• No merge conflicts
• All reference files valid markdown
• Ready for validation step

Outputs:

• Updated anthropic-expert skill
• Backup in anthropic-expert.backup-*/
• Updated changelog.md
• Integration log

Time Estimate: 15-30 minutes (automated, quick review)

Step 5: Validate Updates

Purpose: Ensure updates maintain quality and don't introduce regressions

Process:

1. Run Structure Validation

   python ../../review-multi/scripts/validate-structure.py ../anthropic-expert

   • Validates YAML frontmatter
   • Checks file structure
   • Verifies naming conventions
   • Ensures progressive disclosure
   • Must pass (5/5 or 4/5)

2. Test Search Functionality

   python ../anthropic-expert/scripts/search-docs.py "test query"

   • Verify search still works
   • Check can find content in updated files
   • Ensure no search errors

3. Manual Spot Check

   • Review 2-3 updated sections
   • Verify accuracy of new content
   • Check code examples valid
   • Ensure formatting consistent

4. Validation Decision

   • PASS: All validations successful → Finalize update
   • FAIL: Issues found → Rollback and investigate

5. Rollback if Failed (if validation fails)

   python scripts/update-skill.py --rollback

   • Restores from backup
   • Reverts to previous version
   • Logs failure for investigation

Validation:

• Structure validation passes (≥4/5)
• Search functionality works
• Spot check confirms accuracy
• No regressions detected
• Quality maintained
• Update finalized OR rolled back if issues

Outputs:

• Validation report
• Final updated skill (if passed)
• OR restored backup (if failed)
• Update success/failure status

Time Estimate: 20-30 minutes

Post-Workflow: Update Complete

If Successful:

1. ✅ anthropic-expert updated with latest documentation
2. ✅ Changelog.md updated with changes
3. ✅ Quality validated (structure 5/5)
4. ✅ Ready to use with latest Anthropic features

If Failed:

1. ❌ Updates rolled back
2. 📋 Investigation needed (check logs)
3. 🔄 Manual review of changes
4. 🛠️ Fix issues and retry

Next Check: Weekly or when Anthropic announces updates

Best Practices

1. Schedule Regular Updates

Practice: Weekly automated check for updates

Implementation: Cron job or scheduled task

# Weekly check (Mondays at 9am)
0 9 * * 1 cd /path/to/skills && python anthropic-docs-updater/scripts/check-updates.py --all

2. Review Breaking Changes Manually

Practice: For major version updates, review changes before applying

Why: Breaking changes may require manual updates to examples

3. Backup Before Updating

Practice: Always backup (Step 4 does this automatically)

Why: Can rollback if updates cause issues

4. Validate After Updates

Practice: Always run Step 5 (validation)

Why: Ensures updates don't break skill quality

5. Track Update History

Practice: Maintain detailed changelog

Why: Understand what changed when, aids troubleshooting

Quick Reference

The 5-Step Update Workflow

Total Time: 1.5-2.5 hours (mostly automated)

Update Sources

Common Commands

# Check for updates
python scripts/check-updates.py --all

# Fetch new documentation
python scripts/fetch-docs.py --all

# Process fetched docs
python scripts/process-docs.py --input temp/ --output processed/

# Apply updates
python scripts/update-skill.py --integrate processed/

# Validate
python scripts/update-skill.py --validate

# Rollback if needed
python scripts/update-skill.py --rollback

Automation Schedule

Recommended: Weekly checks, monthly comprehensive updates

Cron Example (check weekly, update monthly):

# Check for updates every Monday
0 9 * * 1 python check-updates.py --all > /tmp/anthropic-updates.log

# Full update first Monday of month
0 10 1-7 * 1 bash run-full-update.sh

anthropic-docs-updater ensures anthropic-expert stays current with the latest Anthropic products, features, and documentation through automated update detection, fetching, processing, and integration.