langchain-tools

name	langchain-tools
description	LangChain tool creation and integration utilities for agent systems
allowed-tools	["Read","Write","Edit","Bash","Glob","Grep"]
graph	{"domains":["domain:software-engineering"],"specializations":["specialization:ai-agents-conversational"],"skillAreas":["skill-area:tool-use","skill-area:tool-service-integration-agents"],"roles":["role:ml-engineer","role:backend-engineer"],"workflows":["workflow:feature-development","workflow:ml-model-lifecycle"],"topics":["topic:api-design"]}

LangChain Tools Skill

Capabilities

• Create custom LangChain tools with proper schemas
• Integrate existing tools and APIs
• Design tool descriptions for optimal LLM understanding
• Implement structured tool inputs with Pydantic
• Handle tool errors and fallbacks
• Create tool chains and pipelines

Target Processes

• custom-tool-development
• function-calling-agent

Implementation Details

Tool Creation Patterns

1. @tool decorator: Simple function-based tools
2. StructuredTool: Tools with complex input schemas
3. BaseTool subclass: Full control over tool behavior
4. Tool from functions: Dynamic tool creation

Configuration Options

• Tool name and description
• Input schema (args_schema)
• Return type specification
• Error handling strategy
• Async/sync execution modes

Best Practices

• Clear, action-oriented descriptions
• Explicit input parameter documentation
• Proper error messages for LLM understanding
• Idempotent operations where possible

Dependencies

• langchain-core
• pydantic