template-skill · git:20251125.ffb5b29 · 2025-11-25 · sha256 351040b43a3aeedb
template-skill git:20251125.ffb5b29A
Immutable. This exact content never changes and is served at /api/v1/blob/351040b43a3aeedb.
---
name: template-skill
description: Template for creating new skills in gptme-contrib. Use this as a starting point when creating your own skills.
---
# Template Skill
This is a minimal skill template demonstrating the basic structure of a gptme skill.
## Overview
Skills are enhanced lessons that bundle:
- Instructional content (like lessons)
- Executable scripts and utilities (optional)
- Dependencies and setup requirements (optional)
- Hook points for automation (optional)
## Basic Structure
Every skill needs:
1. **SKILL.md** - This file with YAML frontmatter + Markdown content
2. **Supporting files** (optional) - Scripts, templates, or resources
## YAML Frontmatter
Required fields:
- `type: skill` - Distinguishes from lessons
- `name: skill-name` - Skill identifier (must match directory name)
- `description: ...` - What the skill does and when to use it
- `status: active` - active, automated, deprecated, or archived
- `match: {keywords: [...]}` - Trigger keywords
Optional fields:
- `scripts: []` - List of bundled Python scripts
- `dependencies: []` - Required Python packages
- `hooks: []` - Execution hooks (future feature)
## Markdown Content
The markdown body can include:
- Detailed instructions for the LLM
- Step-by-step workflows
- Code examples and templates
- Best practices and principles
- References to supporting files
## Creating Your Own Skill
1. Copy this template-skill directory
2. Rename to your-skill-name
3. Update SKILL.md frontmatter (especially name and description)
4. Write your skill instructions in markdown
5. Add any supporting scripts or resources
6. Test with gptme
## Example: Minimal Skill
```yaml
---
type: skill
name: my-skill
description: Brief description of what the skill does
status: active
match:
keywords: [keyword1, keyword2]
scripts: []
dependencies: []
---
# My Skill
Instructions for using this skill...
```
## Example: Skill with Scripts
```yaml
---
type: skill
name: data-analysis
description: Data analysis workflows with pandas and visualization
status: active
match:
keywords: [data analysis, pandas, visualization]
scripts:
- helpers.py
- plot_utils.py
dependencies:
- pandas
- matplotlib
---
# Data Analysis Skill
Use this skill for data analysis tasks...
## Bundled Scripts
- `helpers.py`: Common data manipulation functions
- `plot_utils.py`: Visualization utilities
## Usage
```python
# Import bundled helpers
from helpers import load_data, clean_data
from plot_utils import plot_distribution
# Analyze data
df = load_data("data.csv")
df = clean_data(df)
plot_distribution(df["column"])
```
```
## Integration with Lessons
Skills complement lessons:
- **Lessons**: Behavioral patterns and best practices (auto-included)
- **Skills**: Executable workflows with bundled tools (explicitly loaded)
Example:
- Lesson teaches: "Use type hints in Python"
- Skill provides: Type checking utilities and templates
## Related
- [Skills README](../README.md) - Skills system overview