langchain-ai/skills-benchmarks

About the project

skills-benchmarks is a test suite that measures how the design of skill documentation affects Claude Code's adherence to recommended coding patterns. It is used to compare documentation approaches across LangChain-related tasks and other agent workflows. Its catalogue entries represent skills, hooks, instructions, and a plugin used in the benchmark project.

This repository also configures its own agents. See what skills-benchmarks tells them →

118Stars on the repository
32Mods indexed here, across every type
1mo agoLast push, which is what freshness is scored on
MITLicence, which decides whether bodies are shown

ecosystem-primer

01

langchain-ai/skills-benchmarks

Skill Claude CodeCodex ✓ vendor

INVOKE FIRST for any LangChain / LangGraph / Deep Agents agent building project before consulting other skills or writing any agent code. Required starting point for up to date info on framework selection (LangChain vs LangGraph vs Deep Agents vs hybrid composition), agent patterns, install, environment setup, and…

not rated 118 1mo ago A SkillSpector: warn 71 tokens copy · 92% MIT

framework-selection

02

langchain-ai/skills-benchmarks

Skill Claude CodeCodex ✓ vendor

INVOKE THIS SKILL at the START of any LangChain/LangGraph/Deep Agents project, before writing any agent code. Determines which framework layer is right for the task: LangChain, LangGraph, Deep Agents, or a combination. Must be consulted before other agent skills.

not rated 118 1mo ago A SkillSpector: pass 61 tokens original MIT

langchain-ai/skills-benchmarks

Skill Claude CodeCodex ✓ vendor

ALWAYS START HERE for any LangChain, Deep Agents, or LangGraph agent building project. Required starting point before choosing other skills or writing any code. Covers framework selection (LangChain vs LangGraph vs Deep Agents), agent archetypes, dependency setup, and which skills to load next based on your decisions.

not rated 118 1mo ago A SkillSpector: pass 69 tokens original MIT

deep-agents-core

04

langchain-ai/skills-benchmarks

Skill Claude CodeCodex ✓ vendor

INVOKE THIS SKILL when building ANY Deep Agents application. Covers createdeepagent(), harness architecture, SKILL.md format, and configuration options.

not rated 118 1mo ago A SkillSpector: warn 36 tokens copy · 100% MIT

deep-agents-memory

05

langchain-ai/skills-benchmarks

Skill Claude CodeCodex ✓ vendor

INVOKE THIS SKILL when your Deep Agent needs memory, persistence, or filesystem access. Covers StateBackend (ephemeral), StoreBackend (persistent), FilesystemMiddleware, and CompositeBackend for routing.

not rated 118 1mo ago A SkillSpector: pass 46 tokens copy · 100% MIT

langchain-ai/skills-benchmarks

Skill Claude CodeCodex ✓ vendor

INVOKE THIS SKILL when using subagents, task planning, or human approval in Deep Agents. Covers SubAgentMiddleware, TodoList for planning, and HITL interrupts.

not rated 118 1mo ago A SkillSpector: pass 43 tokens copy · 95% MIT

langchain-ai/skills-benchmarks

Skill Claude CodeCodex ✓ vendor

INVOKE THIS SKILL when asked about and/or have to implement 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…

not rated 118 1mo ago A SkillSpector: pass 68 tokens copy · 95% MIT

langchain-ai/skills-benchmarks

Skill Claude CodeCodex ✓ vendor

Create LangChain agents with createagent, define tools, and use middleware for human-in-the-loop and error handling.

not rated 118 1mo ago A SkillSpector: warn 30 tokens copy · 100% MIT

langchain-ai/skills-benchmarks

Skill Claude CodeCodex ✓ vendor

INVOKE THIS SKILL when you need human-in-the-loop approval, custom middleware, or structured output. Covers HumanInTheLoopMiddleware for human approval of dangerous tool calls, creating custom middleware with hooks, Command resume patterns, and structured output with Pydantic/Zod.

not rated 118 1mo ago A SkillSpector: pass 61 tokens copy · 100% MIT

langchain-rag

10

langchain-ai/skills-benchmarks

Skill Claude CodeCodex ✓ vendor

INVOKE THIS SKILL when building ANY retrieval-augmented generation (RAG) system. Covers document loaders, RecursiveCharacterTextSplitter, embeddings (OpenAI), and vector stores (Chroma, FAISS, Pinecone).

not rated 118 1mo ago A SkillSpector: pass 52 tokens copy · 88% MIT

langchain-ai/skills-benchmarks

Skill Claude CodeCodex ✓ vendor

INVOKE THIS SKILL when writing ANY LangGraph code. Covers StateGraph, state schemas, nodes, edges, Command, Send, invoke, streaming, and error handling.

not rated 118 1mo ago A SkillSpector: pass 43 tokens original MIT

langchain-ai/skills-benchmarks

Skill Claude CodeCodex ✓ vendor

INVOKE THIS SKILL when implementing human-in-the-loop patterns, pausing for approval, or handling errors in LangGraph. Covers interrupt(), Command(resume=...), approval/validation workflows, and the 4-tier error handling strategy.

not rated 118 1mo ago A SkillSpector: pass 55 tokens copy · 100% MIT

langchain-ai/skills-benchmarks

Skill Claude CodeCodex ✓ vendor

INVOKE THIS SKILL when your LangGraph needs to persist state, remember conversations, travel through history, or configure subgraph checkpointer scoping. Covers checkpointers, threadid, time travel, Store, and subgraph persistence modes.

not rated 118 1mo ago A SkillSpector: warn 55 tokens copy · 100% MIT

langsmith-dataset

14

langchain-ai/skills-benchmarks

Skill Claude CodeCodex ✓ vendor

INVOKE THIS SKILL when creating evaluation datasets, uploading datasets to LangSmith, or managing existing datasets. Covers dataset types (finalresponse, singlestep, trajectory, RAG), CLI management commands, SDK-based creation, and example management. Uses the langsmith CLI tool.

not rated 118 1mo ago C 61 tokens copy · 88% MIT

langsmith-evaluator

15

langchain-ai/skills-benchmarks

Skill Claude CodeCodex ✓ vendor

INVOKE THIS SKILL when building evaluation pipelines for LangSmith. Covers three core components: (1) Creating Evaluators - LLM-as-Judge, custom code; (2) Defining Run Functions - how to capture outputs and trajectories from your agent; (3) Running Evaluations - locally with evaluate() or auto-run via LangSmith. Uses…

not rated 118 1mo ago C 83 tokens original MIT

langsmith-trace

16

langchain-ai/skills-benchmarks

Skill Claude CodeCodex ✓ vendor

INVOKE THIS SKILL when working with LangSmith tracing OR querying traces. Covers adding tracing to applications and querying/exporting trace data. Uses the langsmith CLI tool.

not rated 118 1mo ago C 40 tokens original MIT

api-docs

17

langchain-ai/skills-benchmarks

Skill Claude CodeCodex ✓ vendor

OpenAPI documentation and REST API design patterns.

not rated 118 1mo ago A SkillSpector: pass 12 tokens original MIT

docker-patterns

19

langchain-ai/skills-benchmarks

Skill Claude CodeCodex ✓ vendor

Best practices for Docker containerization and multi-stage builds.

not rated 118 1mo ago B SkillSpector: warn 14 tokens original MIT

At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: