rcc - RCC CLI workflows for robot automation environments
Create and run robots with isolated Python environments using RCC CLI and holotree caching
Tags
Updated: 2026-02-23Capabilities
Typical Inputs
Typical Outputs
What this skill does
- init robot from template
- pull robot from GitHub
- build holotree environment
- run robot tasks
- inspect task shell
- execute script commands
- bundle robot for distribution
- list holotree environments
- delete holotree space
- enable shared cache
- run diagnostics
- validate robot configuration
- configure robot.yaml
- configure conda.yaml
- check environment health
- manage Actions/MCP framework
- handle work items
Inputs
- robot.yaml configuration
- conda.yaml configuration
- GitHub repository URL
- robot template name
- task name
- directory path
- environment freeze files
- ROBOT_ROOT environment variable
- ROBOT_ARTIFACTS environment variable
- CLAUDE_PROJECT_DIR environment variable
- PyPI uv package version
Outputs
- isolated Python environment
- bundled robot .py file
- holotree environment listing
- diagnostic reports
- environment health check results
- robot validation reports
- task execution output
Requirements
- RCC CLI installed
- Python installed
- Conda package manager
- uv package manager
- PyYAML for validation
- network access for dependencies
- admin rights for shared cache