adaptationio/skill-evolution-tracker
.claude/skills/skill-evolution-tracker/SKILL.md
Track skill changes, improvements, and evolution over time. Task-based operations for version tracking, change documentation, impact measurement, and evolution analysis. Use when tracking skill versions, documenting changes over time, measuring improvement impact, or analyzing how skills evolved.
$ install --global
skillsauthnpx skillsauth add adaptationio/skrillz skill-evolution-trackerInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Last scanned: Mar 31, 2026, 1:42 AM60.3s2 files scanned
SKILL.md
- name:
- skill-evolution-tracker
- description:
- Track skill changes, improvements, and evolution over time. Task-based operations for version tracking, change documentation, impact measurement, and evolution analysis. Use when tracking skill versions, documenting changes over time, measuring improvement impact, or analyzing how skills evolved.
- allowed-tools:
- Read, Write, Edit, Glob, Grep, Bash, WebSearch, WebFetch
Skill Evolution Tracker
Overview
skill-evolution-tracker documents and analyzes how skills change and improve over time, providing visibility into evolution patterns and improvement effectiveness.
Purpose: Track and understand skill evolution for continuous improvement insights
The 4 Tracking Operations:
- Version Tracking - Document skill versions and changes
- Change Documentation - Record what changed and why
- Impact Measurement - Quantify improvement effects
- Evolution Analysis - Identify patterns in how skills evolve
When to Use
- After skill updates (document changes)
- Version releases (track versions)
- Analyzing improvement effectiveness
- Understanding skill maturity
- Identifying evolution patterns
Operations
Operation 1: Version Tracking
Purpose: Maintain version history for skills
Process:
- Assign version numbers (semver: v1.0, v1.1, v2.0)
- Document version in YAML frontmatter
- Track major changes per version
- Maintain changelog
Format:
## Version History
### v1.1 (2025-11-07)
- Added Quick Reference section
- Enhanced examples in Operations
- Fixed validation criteria
### v1.0 (2025-10-15)
- Initial release
Operation 2: Change Documentation
Purpose: Record what changed, why, and impact
Process:
- List all changes made
- Explain rationale for each
- Note expected impact
- Document validation results
Format:
### Change: Added Quick Reference
**Rationale**: User experience improvement, easier memory refresh
**Changes**: Added Quick Reference section (96 lines)
**Impact**: Improved usability, 100% Quick Ref coverage
**Validation**: Passed structure validation, Quick Ref detected
Operation 3: Impact Measurement
Purpose: Quantify effectiveness of improvements
Metrics:
- Quality score changes (before/after review-multi scores)
- Usage frequency changes
- User satisfaction changes
- Efficiency improvements
Example:
Impact Measurement: Quick Reference Addition
Before:
- Quick Reference: 4 of 7 skills (57%)
- User feedback: "Hard to refresh memory"
After:
- Quick Reference: 7 of 7 skills (100%)
- Validation: All pass Quick Ref check
- Impact: Improved UX, consistency
Quantified:
- Coverage: 57% → 100% (+43%)
- Time to refresh: ~30min → ~5min (-83%)
Operation 4: Evolution Analysis
Purpose: Identify patterns in skill evolution
Process:
- Review version histories
- Identify common evolution patterns
- Understand what drives changes
- Extract meta-learnings
Example Patterns:
- Skills often add Quick Reference in v1.1
- Examples get refined/made concrete
- Validation criteria become more specific over time
Quick Reference
| Operation | Focus | Output | |-----------|-------|--------| | Version Tracking | Version numbers, changelog | Version history | | Change Documentation | What/why/impact of changes | Change log | | Impact Measurement | Quantify improvements | Metrics, evidence | | Evolution Analysis | Patterns across skills | Meta-learnings |
Integration: best-practices-learner (uses evolution insights for learnings)
skill-evolution-tracker provides visibility into how skills improve over time, enabling data-driven understanding of what makes skills better.
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