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documentation-standards
Universal documentation standards and best practices for software projects
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
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Universal documentation standards and best practices for software projects
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Python import style guidelines for absolute and relative imports
Python naming conventions for variables, constants, files, and directories
Python pathlib usage guidelines for file and directory operations
Python refactoring triggers and guidelines for code size limits
UV command-line usage patterns for Python project management
UV command automation and project lifecycle management patterns powered by the uv-mcp server
| name | documentation-standards |
| description | Universal documentation standards and best practices for software projects |
| license | MIT |
| compatibility | opencode |
| metadata | {"related_coding_principles":"For overall development standards, use skill `coding-principles`","related_python_guidelines":"For Python-specific documentation, use skill `python-guidelines`"} |
Provide universal documentation standards and best practices that apply across different projects and domains.
# Universal documentation structure
docs/
├── README.md # Project overview
├── architecture/ # System architecture
│ ├── overview.md # High-level architecture
│ └── components/ # Component details
├── development/ # Development guidelines
│ ├── setup.md # Development environment
│ ├── workflow.md # Development workflow
│ └── standards.md # Coding standards
├── api/ # API documentation
│ ├── reference.md # API reference
│ └── examples.md # Usage examples
└── user/ # User documentation
├── getting-started.md # Quick start guide
├── tutorials/ # Step-by-step tutorials
└── reference/ # Detailed reference
Universal Documentation Standards:
.md files)# Universal Markdown Standards
## Headings
- Use ATX-style headings (#, ##, ###)
- Maintain consistent heading hierarchy
- Limit to 3-4 heading levels
## Code Blocks
```python
# Always specify language for syntax highlighting
def example_function():
"""Example with proper formatting"""
return "formatted code"
```
## Lists
- Use consistent list formatting
- Prefer hyphens for bullet points
- Use numbered lists for sequential steps
## Links
- Use relative links for internal references
- Use absolute links for external references
- Include link descriptions
Use this skill when:
# Universal API Documentation Template
## Endpoint: `/api/v1/resource`
**Method:** `GET`
**Description:** Retrieve resource information
**Parameters:**
- `id` (string, required): Resource identifier
- `format` (string, optional): Response format (json, xml)
**Response:**
```json
{
"id": "string",
"name": "string",
"created_at": "datetime",
"status": "string"
}
```
**Examples:**
```bash
# Request example
curl -X GET "https://api.example.com/v1/resource?id=123&format=json"
# Response example
{
"id": "123",
"name": "Sample Resource",
"created_at": "2023-01-01T00:00:00Z",
"status": "active"
}
### Code Documentation
```python
# Universal Python docstring template
class DataProcessor:
"""Process and transform data for analysis.
This class provides methods for cleaning, normalizing, and
transforming raw data into analysis-ready formats.
Attributes:
config (dict): Configuration parameters for processing
logger (Logger): Logger instance for tracking operations
"""
def __init__(self, config=None):
"""Initialize DataProcessor with configuration.
Args:
config (dict, optional): Processing configuration.
Defaults to default configuration.
Raises:
ValueError: If configuration is invalid
"""
self.config = config or self._get_default_config()
self.logger = self._setup_logger()
self._validate_config()
# Universal Tutorial Template
## Tutorial: Getting Started with [Feature]
### Prerequisites
- Basic understanding of [related concept]
- [Software] version [version] installed
- Access to [required resources]
### Step 1: Setup
1. Install required dependencies
```bash
pip install required-package
```
2. Configure your environment
```bash
export ENV_VAR=value
```
### Step 2: Basic Usage
1. Import the module
```python
from package import Module
```
2. Create an instance
```python
processor = Module(config)
```
### Step 3: Advanced Features
1. Configure advanced options
```python
processor.configure_advanced(option=value)
```
2. Process data
```python
result = processor.process(data)
```
### Troubleshooting
- **Issue**: Common problem description
**Solution**: Step-by-step resolution
- **Issue**: Another common problem
**Solution**: Alternative approach
Applies to: