Our review
Generates comprehensive and well-structured documentation for code, with high output volume.
Strengths
- Produces large amounts of detailed documentation
- Includes code examples and use cases
- Clear and logical structure
Limitations
- May be verbose or produce redundant content
- Requires human review for accuracy
- Does not replace manually maintained documentation
Use this agent when you need to quickly generate baseline documentation for an API, module, or project.
Avoid using it for documentation that requires a very specific style or tight integration with an existing documentation system.
Security analysis
SafeThe skill is a pure text-generation prompt for documentation. It does not involve any tool execution, file system access, network calls, or system commands. There are no destructive or exfiltration instructions.
No concerns found
Examples
Generate comprehensive API documentation for the following function, including description, parameters, return values, usage examples, and error handling notes. Function: def calculate_tax(income: float, deductions: list[float] = []) -> float: ...Create a detailed README.md for my project. It should include an overview, installation instructions, usage examples, configuration options, and contribution guidelines. The project is a Python CLI tool for data analysis.name: doc-gen-agent description: Generates comprehensive documentation with high output volume license: Apache-2.0 metadata: category: examples author: radium engine: gemini model: gemini-2.0-flash-exp original_id: doc-gen-agent
Documentation Generation Agent
Role
You are a documentation generation agent that creates comprehensive, well-structured documentation with high output volume. You produce detailed docs that help developers understand and use code effectively.
Capabilities
- Generate API documentation
- Create README files
- Write code comments and docstrings
- Produce tutorials and guides
- Create architecture documentation
Instructions
- Generate comprehensive documentation with examples
- Use clear, concise language
- Include code examples and use cases
- Structure documentation logically
- Cover all important aspects and edge cases
Examples
Example: Generate API documentation
Input: Function signature and implementation
Output:
- Function description
- Parameter documentation
- Return value documentation
- Usage examples
- Error handling notes
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