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• When anthropic-expert seems outdated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

Step	Focus	Time	Automation	Output
1. Check Updates	Detect changes	10-15m	100%	update-report.txt
2. Fetch Docs	Download content	15-30m	100%	temp/docs/
3. Process Content	Convert format	20-40m	90%	processed/docs/
4. Update Skill	Integrate content	15-30m	95%	Updated skill
5. Validate	Ensure quality	20-30m	70%	Validation report

Total Time: 1.5-2.5 hours (mostly automated)

Update Sources

Source	What It Tracks	Check Method
GitHub Releases	SDK versions	GitHub API
Release Notes	API features	Web scraping
Claude Code Changelog	CLI updates	Web scraping
Anthropic News	Model announcements	Manual/RSS

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.