LangChain ReAct agent implementation with tool binding for reasoning and action loops
Scanned 9/2/2026
Install to Claude Code
npx -y skills add a5c-ai/babysitter --skill langchain-react-agent --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: langchain-react-agent
description: LangChain ReAct agent implementation with tool binding for reasoning and action loops
allowed-tools:
- Read
- Write
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graph:
domains: [domain:software-engineering]
specializations: [specialization:ai-agents-conversational]
skillAreas: [skill-area:agentic-loops, skill-area:tool-use]
roles: [role:ml-engineer, role:backend-engineer]
workflows: [workflow:feature-development, workflow:ml-model-lifecycle]
topics: [topic:design-patterns]
---
# LangChain ReAct Agent Skill
## Capabilities
- Implement ReAct (Reasoning + Acting) agent patterns using LangChain
- Configure tool binding and function calling for agents
- Design thought-action-observation loops
- Integrate with various LLM providers (OpenAI, Anthropic, etc.)
- Handle agent memory and state persistence
- Implement error handling and retry logic for agent actions
## Target Processes
- react-agent-implementation
- function-calling-agent
## Implementation Details
### Core Components
1. **Agent Executor Setup**: Configure LangChain AgentExecutor with appropriate settings
2. **Tool Integration**: Bind tools with proper schemas and descriptions
3. **Prompt Engineering**: Design system prompts for ReAct reasoning patterns
4. **Output Parsing**: Parse agent outputs and handle structured responses
### Configuration Options
- LLM model selection and parameters
- Tool definitions and schemas
- Memory type (buffer, summary, vector)
- Max iterations and timeout settings
- Verbose/debug mode configuration
### Dependencies
- langchain
- langchain-openai / langchain-anthropic
- Python 3.9+
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