Technical Change Tracker
Overview
Track every code change with structured JSON records and accessible HTML output. Ensures AI bot sessions can resume seamlessly when previous sessions expire or are abandoned.
When to Use This Skill
- Use when you need structured change tracking across AI coding sessions
- Use when a bot session expires mid-task and the next session needs full context to resume
- Use when onboarding a project with undocumented change history
How It Works
State Machine
planned -> in_progress -> implemented -> tested -> deployed
|
+-> blocked
Commands
/tc init | /tc create | /tc update | /tc status | /tc resume | /tc close | /tc export | /tc dashboard | /tc retro
Session Handoff
Each TC stores: progress summary, next steps, blockers, key context, and files in progress — so the next bot session picks up exactly where the last left off.
Non-Blocking
TC bookkeeping runs via background subagents. Never interrupts coding work.
Features
- Structured JSON records with append-only revision history
- Test cases with log snippet evidence
- WCAG AA+ accessible HTML output (dark theme, rem-based fonts)
- CSS-only dashboard with status filters
- Python stdlib only — zero external dependencies
- Retroactive bulk creation from git history via
/tc retro
Full Repository
https://github.com/Elkidogz/technical-change-skill — MIT License
Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.