Auto Updater

Overview

auto-updater automatically applies improvements to skills and ecosystem components based on identified patterns and learnings.

Purpose

Automated application of validated improvements across ecosystem

The 5-Step Auto-Update Workflow

:

Identify Improvements

- Gather recommendations from reviews and learnings

Assess Safety

- Determine which can be safely automated

Apply Updates

- Implement improvements automatically

Validate Changes

- Ensure improvements effective, no regressions

Rollback if Needed

- Revert changes if validation fails

Safety

Always validates before finalizing, can rollback

When to Use

Applying systematic improvements across multiple skills

Implementing guideline updates ecosystem-wide

Automating common enhancement patterns

Bulk updates (e.g., add Quick Reference to all skills missing it)

Auto-Update Workflow

Step 1: Identify Improvements

Sources

:

system-reviewer recommendations

best-practices-learner documented patterns

review-multi common findings

Manual improvement requests

Output

List of potential improvements

Time

15-30 minutes

Step 2: Assess Safety

Safe to Automate

:

Structural additions (add Quick Reference section)

Content additions (add examples in standard locations)

Format standardization (consistent heading levels)

Documentation updates (README enhancements)

NOT Safe to Automate

:

Logic changes (requires understanding context)

Content rewrites (needs judgment)

Major refactoring (risk too high)

Custom implementations

Output

Classified improvements (auto-safe vs manual-only)

Time

20-40 minutes

Step 3: Apply Updates

Process

:

Backup affected skills (git commit or copy)

Apply improvement to each skill

Log changes made

Track success/failure per skill

Approach

One skill at a time, validate each before moving to next

Time

Varies by improvement and skill count

Step 4: Validate Changes

For Each Updated Skill

:

Run skill-validator (pass/fail)

Run review-multi structure check (score maintained?)

Visual inspection (looks correct?)

Mark as validated or flagged for review

Output

Validation results per skill

Time

10-15 minutes per skill

Step 5: Rollback if Needed

If Validation Fails

:

Identify which skill failed

Restore from backup (git revert or copy back)

Analyze why it failed

Mark improvement as manual-only for that skill

Output

Rolled back skill, failure analysis

Example Auto-Update

Auto-Update: Add Quick Reference to All Skills Missing It

Step 1: Identify

- Improvements: Add Quick Reference section

- Target Skills: planning-architect, task-development, todo-management

- Count: 3 skills to update

Step 2: Assess Safety

- ✅ Safe: Adding new section (doesn't modify existing content)

- ✅ Safe: Standard format (use template)

- ✅ Safe: Low risk (can validate easily)

- Decision: Auto-update approved

Step 3: Apply

- Backup: Git commit all 3 skills

- Apply to planning-architect: ✅ Success

- Apply to task-development: ✅ Success

- Apply to todo-management: ✅ Success

- Changes: 3/3 skills updated

Step 4: Validate

- planning-architect: 5/5 structure (maintained)

- task-development: 5/5 structure (maintained)

- todo-management: 5/5 structure (maintained)

- All validations: ✅ PASS

Step 5: Rollback

- Not needed (all validations passed)

Result: ✅ 3 skills successfully auto-updated

Time: 90 minutes (vs 3-4 hours manual)

Impact: 100% Quick Reference coverage achieved

Quality: All skills maintained 5/5 scores

Quick Reference

5-Step Auto-Update Workflow

Step

Focus

Time

Safety

Identify

Gather improvements

15-30m

N/A

Assess Safety

Classify auto-safe

20-40m

Critical

Apply

Implement changes

Varies

Backup first

Validate

Check quality maintained

10-15m/skill

Essential

Rollback

Revert if fails

5m/skill

Safety net

Safe vs Unsafe Automation

Safe to Automate

:

Adding standard sections

Format standardization

Documentation additions

Structural improvements (following patterns)

NOT Safe

:

Logic changes

Content rewrites

Major refactoring

Custom implementations

Rule

If requires judgment or understanding → Manual only auto-updater enables safe, validated, automated improvement application across multiple skills simultaneously.