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langchain-tools

Build custom tools for LangChain agents and connect existing tools or APIs. Define structured inputs, descriptions, return types, and error handling so an LLM can understand how to call each tool; the skill also covers tool chains and pipelines.

OriginalShow the original description

LangChain tool creation and integration utilities for agent systems

a5c-ai/babysitter1,872 stars(GitHub 1,872 + cccskills 0)

Run score Not tested

See how to install

Good for

  • Creating a custom tool for a LangChain agent
  • Connecting an agent to an existing API
  • Defining structured inputs for tool calls
  • Handling tool errors and fallback behavior

Files included (2)

  • SKILL.md1.5 KB
  • README.md593 B

SKILL.md (original)

Review the instructions the agent will receive before you install.

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

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