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/langchain-tools

LangChain tool creation and integration utilities for agent systems

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babysitter
1.8k200 skills3 agents21 commands1 MCP
Install
$ npx -y skills add a5c-ai/babysitter --skill langchain-tools --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/langchain-tools

Context preview

The summary Claude sees to decide when to auto-load this skill.

LangChain tool creation and integration utilities for agent systems

SKILL.md

langchain-tools.SKILL.md
name: langchain-tools
description: LangChain tool creation and integration utilities for agent systems
allowed-tools:
  - Read
  - Write
  - Edit
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  - 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
Read more
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