Configuration
Skills

Skills

Agent Mode includes a powerful skills system that allows you to extend the AI’s capabilities with custom instructions, reference materials, scripts, and assets. Skills are organized collections of knowledge and tools that help the AI perform specific tasks more effectively.

Skill Directory Structure

Skills follow a standardized directory structure:

skill-name/
├── SKILL.md              # Main skill definition with YAML frontmatter and instructions
├── references/           # Reference materials (markdown files)
│   └── example-api.md           # API documentation
│   └── example-guide.md         # Usage guide
├── scripts/             # Executable scripts
│   └── example-setup.sh         # Setup script
│   └── example-deploy.py        # Deployment script
├── assets/              # Binary assets (images, config files, etc.)
│   └── example-diagram.png      # Architecture diagram
│   └── example-config.json      # Configuration file
└── evals/
    └── evals.json        # Evaluation tests

SKILL.md Format

The SKILL.md file contains YAML frontmatter followed by markdown instructions:

---
name: python-refactoring
description: Tools and techniques for Python code refactoring
license: MIT
metadata:
  version: 1.0.0
  author: AI Team
  tags: [python, refactoring, code-quality]
---

# Python Refactoring Skill

This skill provides tools and techniques for refactoring Python code...

## Common Refactoring Patterns

1. **Extract Method** - Break down large functions...
2. **Rename Variable** - Improve code readability...
3. **Simplify Conditionals** - Reduce complexity...

## Usage Examples

```python
# Before refactoring
def process_data(data):
    # Complex logic here
    pass

# After refactoring  
def process_data(data):
    validate_input(data)
    cleaned = clean_data(data)
    result = analyze_data(cleaned)
    return result

Skill Configuration

Skills are configured through the agent-config parameter in the YAML configuration file. The following options are available:

skills_paths: Array of directory paths to search for skills
skills_includelist: Array of skill names to include (whitelist)
skills_excludelist: Array of skill names to exclude (blacklist)

Complete configuration example in YAML configuration file (.cecli.conf.yml or ~/.cecli.conf.yml):

# Enable Agent Mode
agent: true

# Agent Mode configuration
agent-config: |
  {
    # Skills configuration
    "skills_paths": ["~/my-skills", "./project-skills"],  # Directories to search for skills
    "skills_includelist": ["python-refactoring", "react-components"],  # Optional: Whitelist of skills to include
    "skills_excludelist": ["legacy-tools"],  # Optional: Blacklist of skills to exclude
    
    # Other Agent Mode settings
    ...
  }

Creating Custom Skills

To create a custom skill:

Create a skill directory with the skill name
Add SKILL.md with YAML frontmatter and instructions
Add reference materials in references/ directory
Add executable scripts in scripts/ directory
Add binary assets in assets/ directory
Add evaluation tests in evals/ directory to test skill performance
Test the skill by adding it to your configuration file:

Best Practices for Skills

Keep skills focused: Each skill should address a specific domain or task
Provide clear instructions: Write comprehensive, well-structured documentation
Include examples: Show practical usage examples
Test scripts: Ensure scripts work correctly and handle errors
Version skills: Use metadata to track skill versions
License appropriately: Specify licenses for reusable skills
Organize references: Structure reference materials logically

Skills in Action

With skills enabled, the LLM can:

Reference specific techniques from skill instructions
Use provided scripts to automate tasks
Consult reference materials for API details
Follow established patterns and best practices
Combine multiple skills for complex tasks

Skills transform Agent Mode from a general-purpose coding assistant into a domain-specific expert with access to curated knowledge and tools.

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