docs: Tool docs improvements

[tonykipkemboi]

Added all the documentation changes, including:

• Updates to existing tool documentation files (like seleniumscrapingtool.mdx, codeinterpretertool.mdx, etc.)
• Addition of new tool documentation files
• Updates to the mint.json file

[joaomdmoura]

Disclaimer: This review was made by a crew of AI Agents.

Code Review Comment for PR #2259

Overview

PR #2259 introduces critical documentation enhancements and tool implementations aimed at improving both usability and clarity across various CrewAI tools. This is a positive step towards better onboarding for users and maintaining consistent project standards.

Key Highlights

Documentation Improvements:

1. Installation Documentation (installation.mdx)

   • The migration to the UV package manager has been executed well, and clear, step-by-step instructions have been highlighted.
   • Recommendation: Include a version compatibility matrix to enhance user understanding of compatibility:

   | CrewAI Version | Python Version | UV Version |
   |----------------|----------------|------------|
   | 1.x            | >=3.9, <3.12  | >=0.1.0    |
   | 2.x            | >=3.10        | >=0.1.0    |

2. Structured Tool Documentation

   • The organization of tool documentation is consistent and well-structured, incorporating sections like Description, Installation, and Examples. This structure promotes accessibility for new users.
   • Recommendation: Implement a standardized metadata header across all tool docs for clarity:

   ---
   title: 'Tool Name'
   description: 'Brief description'
   version: '1.0'
   lastUpdated: '2024-02-20'
   maintainer: 'CrewAI Team'
   ---

3. Code Examples

   • Most code examples are comprehensive, though there is room for improvement in ensuring a uniform format across examples.
   • Suggestion: Adopt a standardized example structure to enhance clarity and consistency:

   from crewai import Agent
   from crewai_tools import ToolName
   
   tool = ToolName(param1: str = "value", param2: int = 42, param3: Optional[dict] = None)
   
   @agent("tool_expert")
   def tool_expert(self) -> Agent:
       """Tool expert agent with clear docstring."""
       return Agent(role="Tool Expert", goal="Specific goal description", tools=[tool], verbose=True)

Implementation Recommendations:

1. Error Handling Improvement

   • The error handling in tools like QdrantVectorSearchTool requires enhancement to provide clearer feedback to users.
   • Suggested implementation:

   class QdrantVectorSearchTool(BaseTool):
       def _run(self, **kwargs) -> str:
           try:
               results = self.client.search(...)
               return self._format_results(results)
           except QdrantClientError as e:
               logger.error(f"Qdrant search error: {e}")
               return f"Error performing vector search: {str(e)}"

2. Configuration Management

   • Utilizing Pydantic models for tool configurations will enhance data validation significantly.
   • Suggested approach:

   from pydantic import BaseModel
   
   class ToolConfig(BaseModel):
       api_key: str
       endpoint: str

3. Performance Enhancements

   • Consider adding caching for frequently accessed data to optimize performance.
   • Suggested mechanism:

   from functools import lru_cache
   
   class CachedTool(BaseTool):
       @lru_cache(maxsize=100)
       def fetch_data(self, query: str) -> Dict[str, Any]:
           # Function implementation...

General Recommendations:

• Add example test coverage information in documentation for better understanding.
• Include a Security Considerations section to highlight best practices regarding API keys and data privacy.
• Ensure error messages follow a standardized format for consistency across the application.

Conclusion

This PR significantly bolsters documentation quality and tool usability. Emphasizing structured documentation, consistent error handling patterns, and configuration validation will lead to a more developer-friendly environment. The suggested improvements, particularly around documentation and error management, will directly enhance user experience. Moving forward, maintaining backward compatibility while evolving tool capabilities should remain a priority.

Great job on this initiative to improve CrewAI! I encourage you to consider the detailed recommendations shared above that can further refine the documentation and implementation for users.