LangChainCLAUDE.mdopenwiki
langchain-ai/openwiki/CLAUDE.md
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CLAUDE.md examples from real projects
How real projects brief Claude Code: the commands, conventions and warnings they put in CLAUDE.md.
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LangChainCLAUDE.mdLangChainCLAUDE.mdagents-from-scratch
langchain-ai/agents-from-scratch/CLAUDE.md
This repository demonstrates building agents using LangGraph, focusing on an email assistant that can: - Triage incoming emails - Draft appropriate responses - Execute actions (calendar scheduling, etc.) - Incorporate human feedback - Learn from past interactions Recommended: Using uv (faster and more reliable) Alternative: Using pip The package is installed as interruptworkshop with import name emailassistant, allowing you to import from anywhere with from email_assistant import ... The repository contains several implementations with increasing complexity in src/email_assistant: Each aspect…
LangChainCLAUDE.mddeep_research_from_scratch
langchain-ai/deep_research_from_scratch/CLAUDE.md
This repository builds a comprehensive deep research system from scratch using LangGraph, progressing through 5 tutorial notebooks that demonstrate different components and patterns. The notebooks in notebooks/ are the source of truth and should be the ONLY files modified. The source code in src/deepresearchfrom_scratch/ is automatically generated from the notebooks using %%writefile magic commands. Here's how it works: The system implements a three-phase deep research workflow: This approach ensures that the interactive tutorials remain the authoritative source while automatically maintaining…
LangChainCLAUDE.mdlangchain-google
langchain-ai/langchain-google/CLAUDE.md
This document provides context to understand the LangChain Python project and assist with development. This is a Python monorepo with multiple independently versioned packages that use uv. This monorepo uses uv for dependency management. Local development uses editable installs: [tool.uv.sources] Each package in libs/ has its own pyproject.toml and uv.lock. Suggest PR titles that follow Conventional Commits format. Refer to .github/workflows/pr_lint for allowed types and scopes. CRITICAL: Always attempt to preserve function signatures, argument positions, and names for exported/public methods.…
LangChainCLAUDE.mdlangchain-aws
langchain-ai/langchain-aws/CLAUDE.md
This document provides context to understand the LangChain Python project and assist with development. This is a monorepo containing LangChain and LangGraph integrations for AWS services. The repository contains two main packages: The package is organized by AWS service integration type: Amazon Bedrock AgentCore Code Interpreter sandbox backend for Deep Agents. Lives in libs/agentcore-codeinterpreter/. This monorepo uses uv for dependency management. Local development uses editable installs: [tool.uv.sources] Each package in libs/ has its own pyproject.toml and uv.lock. Suggest PR titles…
LangChainCLAUDE.mdpaid-media-agent
langchain-ai/paid-media-agent/CLAUDE.md
Read AGENTS.md first and follow it as the binding repository contract. Then read the files it routes to for the change at hand. Do not duplicate their content here. .claude/skills links to .agents/skills, which contains local coding-agent workflows. The paid-media agent's runtime skills live separately in workspace/skills. Desktop app only: when a user asks to set up or onboard, start the setup configuration from .claude/launch.json so the console opens in the Browser pane (preview_start with name setup). The terminal CLI…
LangChainCLAUDE.mdskills-benchmarks
langchain-ai/skills-benchmarks/CLAUDE.md
CRITICAL: LangSmith skills have both Python and TypeScript implementations. These MUST stay in sync: - Same CLI commands, flags, and options - Same output format for identical inputs - Same error handling behavior When modifying any script, always update both Python and TypeScript versions together. Parity tests in tests/scripts/langsmith/parity/ verify this. The TypeScript scaffold (scaffold/typescript/) mirrors Python: - Both scaffolds are copied into Docker so test scripts in either language work from either runner - TestRunner class available in both…
LangChainCLAUDE.mdskills-benchmarks / skills
langchain-ai/skills-benchmarks/skills/CLAUDE.md
This project uses skills that contain up-to-date patterns and CLI tools. ALWAYS invoke the relevant skill first - skills have the correct imports, patterns, and scripts that prevent common mistakes. When stuck or debugging, use this powerful workflow: 1. Build agent using LangChain, DeepAgents, or LangGraph patterns 2. Run agent to generate traces in LangSmith 3. Query traces using langsmith-trace to find interesting examples 4. Create dataset using langsmith-dataset from those traces 5. Build evaluator using langsmith-evaluator to measure quality
LangChainCLAUDE.mdclaude-code-evals
langchain-ai/claude-code-evals/CLAUDE.md
If you are coding with LangGraph, follow these principles and patterns. If any LangGraph files exist: Follow the existing structure exactly. Do not create new agent.py files. Only create agent.py…
LangChainCLAUDE.mdsmithtune
langchain-ai/smithtune/CLAUDE.md
No summary in the file. Open it to read it.
152 projects use a version of this
LangChainCLAUDE.mdmacaw-design-system
langchain-ai/macaw-design-system/CLAUDE.md
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About CLAUDE.md
What is CLAUDE.md?
A file Claude Code reads at the start of every session. It holds the commands, conventions and warnings the agent needs for this project.
Where does it go?
At the repository root. Claude Code also reads CLAUDE.md files in subdirectories when it works there.
What should it contain?
Build and test commands, the project's layout, conventions that aren't obvious from the code, and mistakes to avoid. Short files tend to work better than long ones.
CLAUDE.md or AGENTS.md?
Claude Code reads CLAUDE.md; most other agents read AGENTS.md. Many projects keep one and point the other at it.