vt

Track project version history and file paths in a centralized JSON metadata file.

9|Updated Jul 3, 2026
One-click install
npx skills add https://github.com/TonyQ-AI/agents-workflow --skill vt-tonyq-ai
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: vt
Source: https://github.com/TonyQ-AI/agents-workflow/tree/main/skills/vt
Command: npx skills add https://github.com/TonyQ-AI/agents-workflow --skill vt-tonyq-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill solves the fragmentation of project tracking when working across multiple AI tools, ensuring you always know which directory contains the latest version, its status, and its history.

Core Features & Use Cases

  • Unified Version Tracking: Maintains a single source of truth via .vt.json that all your AI tools can read and update.
  • History Management: Automatically logs updates, feature additions, and timestamps for every project path.
  • Use Case: When switching between Cursor, Claude Code, and other agents, use this to instantly verify if your current working directory is the most recent version or if you need to pull changes from a different path.

Quick Start

Ask the AI to record the current project as the latest version with a description of the features you just implemented.

Frequently Asked Questions about vt

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I sync project versions across multiple AI development tools?

To sync project versions across multiple AI development tools, you use a centralized JSON metadata file that records path updates, feature logs, and chronological history, serving as a single source of truth for all environments.

What is the best way to track project history when switching between AI agents?

The best way to track project history when switching between AI agents is to maintain a standardized JSON metadata file that automatically logs updates, feature additions, and timestamps for every project path.

How do I record the current project state as the latest version?

You record the current project state as the latest version by asking your AI tool to log the current working directory path and a description of the features you just implemented into the JSON metadata file.

Can I use a JSON file to manage context switching between different AI development environments?

Yes, you can use a JSON file to manage context switching between different AI development environments by providing a standardized interface for querying and pruning project versions to verify your current working directory status.

How does centralized version tracking prevent fragmentation across AI tools?

Centralized version tracking prevents fragmentation across AI tools by ensuring you always know which directory contains the latest version, its current status, and its complete chronological history.

When do I need to prune project versions in a multi-agent workflow?

You need to prune project versions in a multi-agent workflow when your centralized JSON metadata file accumulates outdated path records and historical logs that no longer reflect active development tasks.