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
Copy

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.