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setup-intention

v1.1.5

Published

Intent tracking for Cursor and Claude Code

Readme

Intention - Simple Intent Tracking for Collaborative Vibe Coding

Track why code was written and how it evolved when using Cursor or Claude Code.

Installation

Run in the repository root:

npx setup-intention

The script will:

  1. Detect which AI assistants you use
  2. Add intent tracking instructions to their config files
  3. Create a .intents folder for tracking

How it Works

After setup, whenever a coding agent creates or modifies files, it will also create a corresponding file in .intents/ documenting:

  • What was requested (the prompt)
  • When it happened (timestamp)
  • Why it was done (summary)
  • Who requested it (if available)

Example

When you ask: "Create an Express server in app.js"

The coding agent creates:

  • app.js - Your Express server
  • .intents/app.js.json - Documentation of why it was created
{
  "intents": [{
    "id": "550e8400-e29b-41d4-a716-446655440000",
    "timestamp": "2024-11-05T10:30:00Z",
    "action": "create",
    "prompt": "Create an Express server in app.js",
    "summary": "Created Express server with basic routing and middleware setup"
  }]
}

Supported AI Assistants

  • Cursor - .cursorrules
  • Claude Code - .claude/instructions.md (Desktop IDE)

Viewing Intent History

# See all tracked files
find .intents -name "*.json"

# View specific file history
cat .intents/src/app.js.json | python -m json.tool

# Count changes per file
for f in .intents/**/*.json; do
  echo "$f: $(grep -c '"id"' $f) changes"
done

Version Control

Important: The .intents folder should be committed to your repository. This allows your team to:

  • Understand why code was written
  • See the evolution of AI-assisted changes
  • Review AI decisions
  • Maintain accountability

Don't add .intents to .gitignore - it's meant for collaboration.

Why Intent Tracking?

  • Understand decisions - Know why code was written a certain way
  • Team collaboration - Share context about AI-assisted changes
  • Code archaeology - Understand historical decisions
  • Quality assurance - Review AI-generated code more effectively
  • Knowledge transfer - New team members understand the codebase faster