Create Skill Wizard

This skill helps you create new Agent Zero skills that follow the SKILL.md standard.

Quick Start

To create a new skill, I'll guide you through these steps:

•Name & Purpose - What should this skill do?
•Trigger Patterns - When should this skill activate?
•Content Structure - What instructions should the agent follow?
•Supporting Files - Any scripts or templates needed?

SKILL.md Format

Every skill needs a SKILL.md file with YAML frontmatter:

yaml

---
name: "skill-name"
description: "Clear description of what this skill does and when to use it"
version: "1.0.0"
author: "Your Name"
tags: ["category1", "category2"]
trigger_patterns:
  - "keyword1"
  - "phrase that triggers this"
---

# Skill Title

Your skill instructions go here...

Required Fields

Field	Description	Example
`name`	Unique identifier (lowercase, hyphens)	`"code-review"`
`description`	When/why to use this skill	`"Review code for quality and security issues"`

Optional Fields

Field	Description	Example
`version`	Semantic version	`"1.0.0"`
`author`	Creator name	`"Jane Developer"`
`tags`	Categorization keywords	`["review", "quality"]`
`trigger_patterns`	Words/phrases that activate skill	`["review", "check code"]`
`allowed_tools`	Tools this skill can use	`["code_execution", "web_search"]`

Skill Directory Structure

code

/a0/usr/skills/
└── my-skill/
   ├── SKILL.md           # Required: Main skill file
   ├── scripts/           # Optional: Helper scripts
   │   ├── helper.py
   │   └── process.sh
   ├── templates/         # Optional: Templates
   │   └── output.md
   └── docs/              # Optional: Additional docs
      └── examples.md

Writing Good Skill Instructions

Be Specific and Actionable

markdown

# Good
When reviewing code:
1. Check for security vulnerabilities
2. Verify error handling
3. Assess test coverage

# Bad
Review the code and make it better.

Include Examples

markdown

## Example Usage

**User**: "Review my Python function for issues"

**Agent Response**:
> I'll review your function using the code review checklist:
>
> 1. **Security**: No user input validation detected
> 2. **Error Handling**: Missing try-catch for file operations
> 3. **Testing**: Function is testable but no tests found

Provide Checklists

markdown

## Review Checklist
- [ ] Input validation present
- [ ] Error handling complete
- [ ] Tests included
- [ ] Documentation updated

Creating Your Skill: Step by Step

Step 1: Define Purpose

Answer these questions:

•What problem does this skill solve?
•When should the agent use it?
•What's the expected output?

Step 2: Choose a Name

•Use lowercase letters and hyphens
•Be descriptive but concise
•Examples: code-review, data-analysis, deploy-helper

Step 3: Write Trigger Patterns

List words/phrases that should activate this skill:

yaml

trigger_patterns:
  - "review"
  - "check code"
  - "code quality"
  - "pull request"

Step 4: Structure Your Content

Organize with clear sections:

markdown

# Skill Title

## When to Use
Describe the trigger conditions

## The Process
Step-by-step instructions

## Examples
Show sample interactions

## Tips
Additional guidance

Step 5: Add Supporting Files (Optional)

If your skill needs scripts or templates:

bash

# Create directory structure
mkdir -p /a0/usr/skills/my-skill/{scripts,templates,docs}

Example: Complete Skill

yaml

---
name: "python-optimizer"
description: "Optimize Python code for performance and readability. Use when asked to improve or optimize Python code."
version: "1.0.0"
author: "Agent Zero Team"
tags: ["python", "optimization", "performance"]
trigger_patterns:
  - "optimize python"
  - "improve performance"
  - "make faster"
  - "python optimization"
---

# Python Optimizer

## When to Use
Activate when user asks to optimize, improve, or speed up Python code.

## Optimization Process

### Step 1: Profile First
Before optimizing, understand where time is spent:
```python
import cProfile
cProfile.run('your_function()')

Step 2: Common Optimizations

•

Use List Comprehensions

python

# Slow
result = []
for x in data:
    result.append(x * 2)

# Fast
result = [x * 2 for x in data]

•

Use Sets for Lookups

python

# Slow: O(n)
if item in large_list:

# Fast: O(1)
if item in large_set:

•

Use Generators for Large Data

python

# Memory-heavy
data = [process(x) for x in huge_list]

# Memory-efficient
data = (process(x) for x in huge_list)

Step 3: Verify Improvement

Always measure before and after:

python

import time
start = time.perf_counter()
# code to measure
elapsed = time.perf_counter() - start
print(f"Took {elapsed:.4f} seconds")

Anti-Patterns to Avoid

•Premature optimization
•Optimizing without profiling
•Sacrificing readability for tiny gains

code


## Skill Installation

### Local Installation

1. Create skill directory:
   ```bash
   mkdir -p /a0/usr/skills/my-skill

•
Create SKILL.md:
bash
```
touch /a0/usr/skills/my-skill/SKILL.md
```
•
Add content and save
•
Skills are automatically loaded on next agent initialization

Sharing Skills

To share skills with others:

•Create a GitHub repository
•Include the skill directory structure
•Add a README with installation instructions
•Users can copy to their /a0/usr/skills/ directory

Testing Your Skill

After creating a skill:

•Start a new conversation
•Use one of your trigger patterns
•Verify the agent follows your instructions
•Iterate and improve based on results