Transform workflows into Claude Skills automatically
Project description
Pack to Claude Skill Pipeline
A comprehensive system for capturing workflows and automatically generating Claude Skills from recorded user interactions.
Overview
This pipeline transforms real-world workflows into Claude Skills through four progressive phases:
- Phase 1 (MVP): Recording & Basic Skill Generation
- Phase 2: Improving Skill Quality (confidence, descriptions, robustness)
- Phase 3: Collaboration & Deployment (team features)
- Phase 4: Ecosystem Integration and Marketplace
Features
- Workflow Recording: Capture screen video and user interaction events
- Vision-Language Analysis: Extract meaningful steps from video frames
- Automated Skill Generation: Create Claude Skills with proper structure and metadata
- Confidence Scoring: Rate the reliability of each generated step
- Team Collaboration: Version control, sharing, and deployment features
- Ecosystem Integration: Connect with Claude's skill marketplace and MCP plugins
Quick Start
# Install dependencies
pip install -r requirements.txt
# Record a workflow
python -m pack2skill record --output my_workflow.json
# Generate a skill
python -m pack2skill generate my_workflow.json --output ./skills/
# Install the skill
python -m pack2skill install ./skills/my-skill/
Project Structure
pack2skill/
├── core/ # Core functionality
│ ├── recorder/ # Workflow recording (screen + events)
│ ├── analyzer/ # Video frame analysis and captioning
│ ├── generator/ # Skill generation logic
│ └── utils/ # Shared utilities
├── quality/ # Phase 2: Quality improvements
│ ├── confidence.py # Confidence scoring
│ ├── description.py # Description optimization
│ └── robustness.py # Edge case handling
├── team/ # Phase 3: Team features
│ ├── versioning.py # Version control integration
│ ├── deployment.py # Skill deployment
│ └── testing.py # Testing framework
├── ecosystem/ # Phase 4: Ecosystem integration
│ ├── marketplace.py # Marketplace features
│ └── integrations.py # MCP and plugin support
├── cli/ # Command-line interface
└── tests/ # Test suite
Requirements
- Python 3.9+
- FFmpeg (for screen recording)
- CUDA-capable GPU (recommended for vision models)
Documentation
See the docs/ directory for detailed documentation:
Contributing
We welcome contributions! See CONTRIBUTING.md for guidelines.
License
MIT License - see LICENSE for details.
Acknowledgments
Built for the Claude Skills ecosystem by Anthropic.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file pack2skill-0.1.0.tar.gz.
File metadata
- Download URL: pack2skill-0.1.0.tar.gz
- Upload date:
- Size: 57.7 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.10.14
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
a0800543588828a10abd248f2ab955e05a9e94a30eabe02d0a3d7b84de3bdd75
|
|
| MD5 |
662cfdbde3d204c90a5e38df9c8d223d
|
|
| BLAKE2b-256 |
010724a26eee52670f8aa151f7bc1dbf3cbda8d33aef35025a4c95ae2d23b3b1
|
File details
Details for the file pack2skill-0.1.0-py3-none-any.whl.
File metadata
- Download URL: pack2skill-0.1.0-py3-none-any.whl
- Upload date:
- Size: 40.1 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.10.14
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
43113cf23b74711be87ab74c3a9da5cbeb3b24d100ddee3db055ab080e7879dc
|
|
| MD5 |
b504a95dfdc6cc0d618997aa89a54c94
|
|
| BLAKE2b-256 |
bab8a6f684c7a006c6dde43ce388ded38e606afb611f52a18829c707fd768e04
|