name: document-hub-update description: Comprehensive review and update of the documentation hub. Analyzes recent code changes, detects drift, validates structure, and proposes specific updates to keep documentation synchronized with the codebase.

Document Hub: Update

Intelligently update documentation based on code changes and drift detection.

Helper Scripts Available:

• scripts/analyze_changes.py - Analyzes git history since last doc update
• scripts/detect_drift.py - Finds undocumented modules and technologies
• scripts/validate_hub.py - Validates documentation structure
• scripts/extract_glossary.py - Extracts new domain terms

Always run scripts with --help or check scripts/README.md first to understand their usage and output format.

What This Skill Does

Performs a comprehensive review and update of all documentation hub files:

1. Analyzes what changed since last doc update (via git)
2. Detects drift between docs and codebase
3. Proposes specific, scoped updates
4. Validates result after updates

Decision Tree: Update Strategy

User requests update → Is this a git repository?
    ├─ Yes → Analyze changes since last doc update
    │         ├─ No changes → Check drift anyway (dependencies might have changed)
    │         └─ Changes detected → Categorize and scope update
    │
    └─ No git → Full drift analysis
        ├─ Low drift (<0.15) → Minor updates only
        ├─ Medium drift (0.15-0.35) → Focused updates
        └─ High drift (>0.35) → Comprehensive review needed

Update Workflow

Phase 1: Pre-Update Analysis

Step 1: Validate Current State

Always validate before making changes:

python scripts/validate_hub.py /path/to/project

If validation fails:

• Fix structural errors first
• Address broken cross-references
• Repair invalid Mermaid diagrams
• Then proceed with content updates

Step 2: Analyze Recent Changes

Use git history to scope the update:

# Auto-detect since last doc update
python scripts/analyze_changes.py /path/to/project

# Or specify a commit/date
python scripts/analyze_changes.py /path/to/project abc123

This returns JSON categorizing changes.

Step 3: Detect Drift

Even if no recent changes, check for drift:

python scripts/detect_drift.py /path/to/project

This identifies undocumented modules, missing technologies, and documented-but-removed code.

Phase 2: Propose Updates

Based on analysis, propose specific updates to the user with priorities (high/medium/low).

Phase 3: Execute Updates

Update each file systematically based on change analysis.

Phase 4: Post-Update Validation

After making updates, always validate:

python scripts/validate_hub.py /path/to/project

Best Practices

• Always validate first - Fix structural issues before content updates
• Use git analysis - Let analyze_changes.py scope the update
• Present proposals - Show user what will change
• Update incrementally - One file at a time, validate between

See scripts/README.md for complete helper script documentation.