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basic-skill-template skill

/.agent-skills/templates/basic-skill-template

This skill guides you to implement Python-based automation workflows by outlining steps, prerequisites, and best practices for reliable execution.

npx playbooks add skill supercent-io/skills-template --skill basic-skill-template

Review the files below or copy the command above to add this skill to your agents.

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SKILL.md
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---
name: basic-skill-template
description: Brief description of what this Skill does and when to use it. Include key technologies and scenarios.
tags: [template, example-tags]
platforms: [Claude, ChatGPT, Gemini]
---

# Your Skill Name

## When to use this skill
- Scenario 1: Describe when to use
- Scenario 2: Another use case
- Scenario 3: Additional context

## Instructions

### Step 1: [Action Name]
Provide clear, detailed instructions for this step.

Include any prerequisites or context needed:
- Prerequisite 1
- Prerequisite 2

```language
# Code example if applicable
example_code()
```

### Step 2: [Action Name]
Continue with the next logical step.

Explain the reasoning behind this step and what the expected outcome should be.

### Step 3: [Action Name]
Final steps or additional considerations.

## Examples

### Example 1: [Scenario Name]
Describe a specific use case.

```language
# Complete, working code example
def example_function():
    """Docstring explaining the function."""
    result = process_data()
    return result
```

**Expected output**:
```
Example output here
```

### Example 2: [Another Scenario]
Show a different use case or variation.

```language
# Another complete example
class ExampleClass:
    def __init__(self):
        self.value = 0

    def method(self):
        return self.value
```

## Best practices

1. **Practice 1**: Explain why this is important
   - Sub-point about implementation
   - Common mistake to avoid

2. **Practice 2**: Another key principle
   - How to implement correctly
   - When to apply this principle

3. **Practice 3**: Additional guidance
   - Real-world considerations
   - Performance/security implications

4. **Practice 4**: Final recommendations

## Common pitfalls

- **Pitfall 1**: What to avoid and why
- **Pitfall 2**: Another common mistake
- **Pitfall 3**: Edge case to consider

## Troubleshooting

### Issue 1: [Problem Description]
**Symptoms**: What you might observe
**Cause**: Why this happens
**Solution**: How to fix it

### Issue 2: [Another Problem]
**Symptoms**: Observable behavior
**Cause**: Root cause
**Solution**: Resolution steps

## References

- [Official Documentation](https://example.com/docs)
- [Related Tutorial](https://example.com/tutorial)
- [Best Practices Guide](https://example.com/guide)
- [Community Resources](https://example.com/community)

## Additional Resources

- [Internal Reference](REFERENCE.md) (if exists)
- [More Examples](EXAMPLES.md) (if exists)
- [Advanced Usage](ADVANCED.md) (if exists)

Overview

This skill provides a compact, reusable Python template for building simple command-line or library components. It outlines when to apply the template, step-by-step actions to implement features, and minimal working examples to accelerate development. Use it to standardize small utilities, prototypes, or learning projects.

How this skill works

The skill inspects common project needs and delivers a three-step workflow: scaffold, implement, and validate. It includes code snippets for core functions and a class example, plus troubleshooting notes for typical runtime issues. The templates emphasize clear prerequisites, expected outcomes, and minimal, runnable examples.

When to use it

  • Starting a small Python utility or prototype
  • Creating a consistent project skeleton for demos or learning
  • Standardizing simple CLI tools or library modules
  • Teaching or documenting basic Python patterns
  • Rapidly scaffolding examples for tutorials or PRs

Best practices

  • Keep functions focused: each function should do one thing and return predictable values
  • Document inputs and outputs with short docstrings and expected types
  • Include simple unit-like checks or assertions to validate behavior during development
  • Handle edge cases explicitly and log helpful error messages for troubleshooting
  • Keep dependencies minimal and pin versions when sharing code

Example use cases

  • Build a small data-processing script that reads, transforms, and outputs data
  • Prototype a new utility function and include a class wrapper for future extension
  • Create a reproducible example for a bug report or educational tutorial
  • Scaffold a minimal CLI that exposes a single processing entry point
  • Provide a reference implementation to compare against optimized versions

FAQ

What prerequisites are required to use the template?

A working Python environment (3.7+ recommended), a basic editor, and any domain-specific libraries listed in the template prerequisites. No framework is required.

How do I validate the template works in my environment?

Run the provided code examples as-is. Use the example function or class in an interactive session and compare the output to the expected output noted in the examples. Add simple assertions to automate checks.