deep-agents-core
INVOKE THIS SKILL when building ANY Deep Agents application. Covers create_deep_agent(), harness architecture, SKILL.md format, and configuration options.
INVOKE THIS SKILL when setting up a new project or when asked about package versions, installation, or dependency management for LangChain, LangGraph, LangSmith, or Deep Agents. Covers required packages, minimum versions, environment requirements, versioning best practices, and
$ npx -y skills add langchain-ai/langchain-skills --skill langchain-dependencies --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/langchain-dependenciesContext preview
The summary Claude sees to decide when to auto-load this skill.
INVOKE THIS SKILL when setting up a new project or when asked about package versions, installation, or dependency management for LangChain, LangGraph, LangSmith, or Deep Agents. Covers required packages, minimum versions, environment requirements, versioning best practices, and
name: langchain-dependencies description: "INVOKE THIS SKILL when setting up a new project or when asked about package versions, installation, or dependency management for LangChain, LangGraph, LangSmith, or Deep Agents. Covers required packages, minimum versions, environment requirements, versioning best practices, and common community tool packages for both Python and TypeScript."
<overview> The LangChain ecosystem is split into focused, independently-versioned packages. Understanding which packages you need — and their version constraints — prevents incompatibilities and keeps upgrades predictable.
**Key principles:**
</overview>
---
<environment-requirements>
| Requirement | Python | TypeScript / Node | |-------------|--------|-------------------| | Runtime minimum | **Python 3.10+** | **Node.js 20+** | | LangChain | **1.0+ (LTS)** | **1.0+ (LTS)** | | LangSmith SDK | >= 0.3.0 | >= 0.3.0 |
</environment-requirements>
---
<framework-choice> Pick **one** agent orchestration layer. You do not need both.
| Framework | When to use | Core extra package | |-----------|-------------|--------------------| | **LangGraph** | Need fine-grained graph control, custom workflows, loops, or branching | `langgraph` / `@langchain/langgraph` | | **Deep Agents** | Want batteries-included planning, memory, file context, and skills out of the box | `deepagents` (depends on LangGraph; installs it as a transitive dep) |
Both sit on top of `langchain` + `langchain-core` + `langsmith`. </framework-choice>
---
<python-packages>
| Package | Role | Min version | |---------|------|-------------| | `langchain` | Agents, chains, retrieval | 1.0 | | `langchain-core` | Base types & interfaces (peer dep) | 1.0 | | `langsmith` | Tracing, evaluation, datasets | 0.3.0 |
| Package | Use when | Min version | |---------|----------|-------------| | `langgraph` | Building custom graphs directly | 1.0 | | `deepagents` | Using the Deep Agents framework | latest |
| Package | Provider | |---------|----------| | `langchain-openai` | OpenAI (GPT-4o, o3, …) | | `langchain-anthropic` | Anthropic (Claude) | | `langchain-google-genai` | Google (Gemini) | | `langchain-mistralai` | Mistral | | `langchain-groq` | Groq (fast inference) | | `langchain-cohere` | Cohere | | `langchain-fireworks` | Fireworks AI | | `langchain-together` | Together AI | | `langchain-huggingface` | Hugging Face Hub | | `langchain-ollama` | Ollama (local models) | | `langchain-aws` | AWS Bedrock | | `langchain-azure-ai` | Azure AI Foundry |
These packages have tighter compatibility requirements — use the latest available version unless you have a specific reason not to.
| Package | Adds | Notes | |---------|------|-------| | `langchain-tavily` | Tavily web search (`TavilySearch`) | Dedicated integration package; prefer latest | | `langchain-text-splitters` | Text chunking utilities | Semver, keep current | | `langchain-community` | 1000+ integrations (fallback) | **NOT semver — pin to minor series** | | `faiss-cpu` | FAISS vector store (local) | Via `langchain-community`; use latest | | `langchain-chroma` | Chroma vector store | Dedicated integration package; prefer latest | | `langchain-pinecone` | Pinecone vector store | Dedicated integration package; prefer latest | | `langchain-qdrant` | Qdrant vector store | Dedicated integration package; prefer latest | | `langchain-weaviate` | Weaviate vector store | Dedicated integration package; prefer latest | | `langsmith[pytest]` | pytest plugin for LangSmith | Requires langsmith >= 0.3.4 |
> **langchain-community stability note:** This package is NOT on semantic versioning. Minor releases can contain breaking changes. Prefer dedicated integration packages (e.g. `langchain-chroma`, `langchain-tavily`) when they exist — they are independently versioned and more stable.
</python-packages>
<typescript-packages>
| Package | Role | Min version | |---------|------|-------------| | `@langchain/core` | Base types & interfaces (peer dep) | 1.0 | | `langchain` | Agents, chains, retrieval | 1.0 | | `langsmith` | Tracing, evaluation, datasets | 0.3.0 |
| Package | Use when | Min version | |---------|----------|-------------| | `@langchain/langgraph` | Building custom graphs directly | 1.0 | | `deepagents` | Using the Deep Agents framework | latest |
| Package | Provider | |---------|----------| | `@langchain/openai` | OpenAI (GPT-4o, o3, …) | | `@langchain/anthropic` | Anthropic (Claude) | | `@langchain/google-genai` | Google (Gemini) | | `@langchain/mistralai` | Mistral | | `@langchain/groq` | Groq (fast inference) | | `@langchain/cohere` | Cohere | | `@langchain/aws` | AWS Bedrock | | `@langchain/azure-openai` | Azure OpenAI | | `@langchain/ollama` | Ollama (local models) |
| Package | Adds | Notes | |---------|------|-------| | `@langchain/tavily` | Tavily web search (`TavilySearch`) | Dedicated integration package; prefer latest |
⚠️ — This project is in early development. APIs and skill content may change. Agent skills for building agents with LangChain, LangGraph, and Deep Agents. For LangSmith-specific trace and dataset workflows, use langsmith-skills.
Repo: langchain-ai/langchain-skills
INVOKE THIS SKILL when building ANY Deep Agents application. Covers create_deep_agent(), harness architecture, SKILL.md format, and configuration options.
INVOKE THIS SKILL when your Deep Agent needs memory, persistence, or filesystem access. Covers StateBackend (ephemeral), StoreBackend (persistent),…
INVOKE THIS SKILL when using subagents, task planning, or human approval in Deep Agents. Covers SubAgentMiddleware, TodoList for planning, and HITL interrupts.
Scaffold a minimal local Deep Agent in Python by following the official quickstart, using provider-native web search instead of Tavily. Use when the user wants…
Scaffold a minimal local Deep Agent in TypeScript by following the official quickstart, using provider-native web search instead of Tavily. Use when the user…
INVOKE FIRST for any LangChain / LangGraph / Deep Agents agent building project before consulting other skills or writing any agent code. Required starting…