technical-change-tracker
Track code changes with structured JSON records, state machine enforcement, and AI session handoff for bot continuity
Best use case
technical-change-tracker is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Track code changes with structured JSON records, state machine enforcement, and AI session handoff for bot continuity
Teams using technical-change-tracker should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/technical-change-tracker/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How technical-change-tracker Compares
| Feature / Agent | technical-change-tracker | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Track code changes with structured JSON records, state machine enforcement, and AI session handoff for bot continuity
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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.Related Skills
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