[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-langchain-deep-agents-core":3,"mdc--z8ma7g-key":34,"related-repo-langchain-deep-agents-core":4577,"related-org-langchain-deep-agents-core":4675},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":12,"stars":24,"repoUrl":25,"updatedAt":26,"license":27,"forks":28,"topics":29,"repo":30,"sourceUrl":32,"mdContent":33},"deep-agents-core","build applications with LangChain Deep Agents","INVOKE THIS SKILL when building ANY Deep Agents application. Covers create_deep_agent(), harness architecture, SKILL.md format, and configuration options.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},"langchain","LangChain","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Flangchain.png","langchain-ai",[13,17,20,21],{"name":14,"slug":15,"type":16},"LLM","llm","tag",{"name":18,"slug":19,"type":16},"Architecture","architecture",{"name":9,"slug":8,"type":16},{"name":22,"slug":23,"type":16},"Agents","agents",877,"https:\u002F\u002Fgithub.com\u002Flangchain-ai\u002Flangchain-skills","2026-04-06T18:26:24.822592",null,77,[],{"repoUrl":25,"stars":24,"forks":28,"topics":31,"description":27},[],"https:\u002F\u002Fgithub.com\u002Flangchain-ai\u002Flangchain-skills\u002Ftree\u002FHEAD\u002Fconfig\u002Fskills\u002Fdeep-agents-core","---\nname: deep-agents-core\ndescription: \"INVOKE THIS SKILL when building ANY Deep Agents application. Covers create_deep_agent(), harness architecture, SKILL.md format, and configuration options.\"\n---\n\n\u003Coverview>\nDeep Agents are an opinionated agent framework built on LangChain\u002FLangGraph with built-in middleware:\n\n- **Task Planning**: TodoListMiddleware for breaking down complex tasks\n- **Context Management**: Filesystem tools with pluggable backends\n- **Task Delegation**: SubAgent middleware for spawning specialized agents\n- **Long-term Memory**: Persistent storage across threads via Store\n- **Human-in-the-loop**: Approval workflows for sensitive operations\n- **Skills**: On-demand loading of specialized capabilities\n\nThe agent harness provides these capabilities automatically - you configure, not implement.\n\u003C\u002Foverview>\n\n\u003Cwhen-to-use>\n\n| Use Deep Agents When | Use LangChain's create_agent When |\n|---------------------|-----------------------------------|\n| Multi-step tasks requiring planning | Simple, single-purpose tasks |\n| Large context requiring file management | Context fits in a single prompt |\n| Need for specialized subagents | Single agent is sufficient |\n| Persistent memory across sessions | Ephemeral, single-session work |\n\n\u003C\u002Fwhen-to-use>\n\n\u003Cmiddleware-selection>\n\n| If you need to... | Middleware | Notes |\n|------------------|------------|-------|\n| Track complex tasks | TodoListMiddleware | Default enabled |\n| Manage file context | FilesystemMiddleware | Configure backend |\n| Delegate work | SubAgentMiddleware | Add custom subagents |\n| Add human approval | HumanInTheLoopMiddleware | Requires checkpointer |\n| Load skills | SkillsMiddleware | Provide skill directories |\n| Access memory | MemoryMiddleware | Requires Store instance |\n\n\u003C\u002Fmiddleware-selection>\n\n\u003Cex-basic-agent>\n\u003Cpython>\nCreate a basic deep agent with a custom tool and invoke it with a user message.\n\n```python\nfrom deepagents import create_deep_agent\nfrom langchain.tools import tool\n\n@tool\ndef get_weather(city: str) -> str:\n \"\"\"Get the weather for a given city.\"\"\"\n return f\"It is always sunny in {city}\"\n\nagent = create_deep_agent(\n model=\"claude-sonnet-4-5-20250929\",\n tools=[get_weather],\n system_prompt=\"You are a helpful assistant\"\n)\n\nconfig = {\"configurable\": {\"thread_id\": \"user-123\"}}\nresult = agent.invoke({\n \"messages\": [{\"role\": \"user\", \"content\": \"What's the weather in Tokyo?\"}]\n}, config=config)\n```\n\u003C\u002Fpython>\n\u003Ctypescript>\nCreate a basic deep agent with a custom tool and invoke it with a user message.\n\n```typescript\nimport { createDeepAgent } from \"deepagents\";\nimport { tool } from \"@langchain\u002Fcore\u002Ftools\";\nimport { z } from \"zod\";\n\nconst getWeather = tool(\n async ({ city }) => `It is always sunny in ${city}`,\n { name: \"get_weather\", description: \"Get weather for a city\", schema: z.object({ city: z.string() }) }\n);\n\nconst agent = await createDeepAgent({\n model: \"claude-sonnet-4-5-20250929\",\n tools: [getWeather],\n systemPrompt: \"You are a helpful assistant\"\n});\n\nconst config = { configurable: { thread_id: \"user-123\" } };\nconst result = await agent.invoke({\n messages: [{ role: \"user\", content: \"What's the weather in Tokyo?\" }]\n}, config);\n```\n\u003C\u002Ftypescript>\n\u003C\u002Fex-basic-agent>\n\n\u003Cex-full-configuration>\n\u003Cpython>\nConfigure a deep agent with all available options including subagents, skills, and persistence.\n\n```python\nfrom deepagents import create_deep_agent\nfrom deepagents.backends import FilesystemBackend\nfrom langgraph.checkpoint.memory import MemorySaver\nfrom langgraph.store.memory import InMemoryStore\n\nagent = create_deep_agent(\n name=\"my-assistant\",\n model=\"claude-sonnet-4-5-20250929\",\n tools=[custom_tool1, custom_tool2],\n system_prompt=\"Custom instructions\",\n subagents=[research_agent, code_agent],\n backend=FilesystemBackend(root_dir=\".\", virtual_mode=True),\n interrupt_on={\"write_file\": True},\n skills=[\".\u002Fskills\u002F\"],\n checkpointer=MemorySaver(),\n store=InMemoryStore()\n)\n```\n\u003C\u002Fpython>\n\u003Ctypescript>\nConfigure a deep agent with all available options including subagents, skills, and persistence.\n\n```typescript\nimport { createDeepAgent, FilesystemBackend } from \"deepagents\";\nimport { MemorySaver, InMemoryStore } from \"@langchain\u002Flanggraph\";\n\nconst agent = await createDeepAgent({\n name: \"my-assistant\",\n model: \"claude-sonnet-4-5-20250929\",\n tools: [customTool1, customTool2],\n systemPrompt: \"Custom instructions\",\n subagents: [researchAgent, codeAgent],\n backend: new FilesystemBackend({ rootDir: \".\", virtualMode: true }),\n interruptOn: { write_file: true },\n skills: [\".\u002Fskills\u002F\"],\n checkpointer: new MemorySaver(),\n store: new InMemoryStore()\n});\n```\n\u003C\u002Ftypescript>\n\u003C\u002Fex-full-configuration>\n\n\u003Cbuilt-in-tools>\nEvery deep agent has access to:\n\n1. **Planning**: `write_todos` - Track multi-step tasks\n2. **Filesystem**: `ls`, `read_file`, `write_file`, `edit_file`, `glob`, `grep`\n3. **Delegation**: `task` - Spawn specialized subagents\n\u003C\u002Fbuilt-in-tools>\n\n---\n\n## SKILL.md Format\n\n\u003Cskill-md-format>\nSkills use **progressive disclosure** - agents only load content when relevant.\n\n### Directory Structure\n\n```\nskills\u002F\n└── my-skill\u002F\n ├── SKILL.md # Required: main skill file\n ├── examples.py # Optional: supporting files\n └── templates\u002F # Optional: templates\n```\n\n### SKILL.md Format\n\n```markdown\n---\nname: my-skill\ndescription: Clear, specific description of what this skill does\n---\n\n# Skill Name\n\n## Overview\nBrief explanation of the skill's purpose.\n\n## When to Use\nConditions when this skill applies.\n\n## Instructions\nStep-by-step guidance for the agent.\n```\n\u003C\u002Fskill-md-format>\n\n\u003Cskills-vs-memory>\n\n| Skills | Memory (AGENTS.md) |\n|--------|-------------------|\n| On-demand loading | Always loaded at startup |\n| Task-specific instructions | General preferences |\n| Large documentation | Compact context |\n| SKILL.md in directories | Single AGENTS.md file |\n\n\u003C\u002Fskills-vs-memory>\n\n\u003Cex-skills-with-filesystem-backend>\n\u003Cpython>\nSet up an agent with skills directory and filesystem backend for on-demand skill loading.\n\n```python\nfrom deepagents import create_deep_agent\nfrom deepagents.backends import FilesystemBackend\nfrom langgraph.checkpoint.memory import MemorySaver\n\nagent = create_deep_agent(\n backend=FilesystemBackend(root_dir=\".\", virtual_mode=True),\n skills=[\".\u002Fskills\u002F\"],\n checkpointer=MemorySaver()\n)\n\nresult = agent.invoke({\n \"messages\": [{\"role\": \"user\", \"content\": \"Use the python-testing skill\"}]\n}, config={\"configurable\": {\"thread_id\": \"session-1\"}})\n```\n\u003C\u002Fpython>\n\u003Ctypescript>\nSet up an agent with skills directory and filesystem backend for on-demand skill loading.\n\n```typescript\nimport { createDeepAgent, FilesystemBackend } from \"deepagents\";\nimport { MemorySaver } from \"@langchain\u002Flanggraph\";\n\nconst agent = await createDeepAgent({\n backend: new FilesystemBackend({ rootDir: \".\", virtualMode: true }),\n skills: [\".\u002Fskills\u002F\"],\n checkpointer: new MemorySaver()\n});\n\nconst result = await agent.invoke({\n messages: [{ role: \"user\", content: \"Use the python-testing skill\" }]\n}, { configurable: { thread_id: \"session-1\" } });\n```\n\u003C\u002Ftypescript>\n\u003C\u002Fex-skills-with-filesystem-backend>\n\n\u003Cex-skills-with-store-backend>\n\u003Cpython>\nLoad skill content into a Store backend for environments without filesystem access.\n\n```python\nfrom deepagents import create_deep_agent\nfrom deepagents.backends import StoreBackend\nfrom deepagents.backends.utils import create_file_data\nfrom langgraph.store.memory import InMemoryStore\n\nstore = InMemoryStore()\n\n# Load skill content into store\nskill_content = \"\"\"---\nname: python-testing\ndescription: Best practices for Python testing with pytest\n---\n# Python Testing Skill\n...\"\"\"\n\nstore.put(\n namespace=(\"filesystem\",),\n key=\"\u002Fskills\u002Fpython-testing\u002FSKILL.md\",\n value=create_file_data(skill_content)\n)\n\nagent = create_deep_agent(\n backend=lambda rt: StoreBackend(rt),\n store=store,\n skills=[\"\u002Fskills\u002F\"]\n)\n```\n\u003C\u002Fpython>\n\u003C\u002Fex-skills-with-store-backend>\n\n\u003Cboundaries>\n\n### What Agents CAN Configure\n\n- Model selection and parameters\n- Additional custom tools\n- System prompt customization\n- Backend storage strategy\n- Which tools require approval\n- Custom subagents with specialized tools\n\n### What Agents CANNOT Configure\n\n- Core middleware removal (TodoList, Filesystem, SubAgent always present)\n- The write_todos, task, or filesystem tool names\n- The SKILL.md frontmatter format\n\u003C\u002Fboundaries>\n\n\u003Cfix-checkpointer-for-interrupts>\n\u003Cpython>\nInterrupts require a checkpointer.\n\n```python\n# WRONG\nagent = create_deep_agent(interrupt_on={\"write_file\": True})\n\n# CORRECT\nagent = create_deep_agent(interrupt_on={\"write_file\": True}, checkpointer=MemorySaver())\n```\n\u003C\u002Fpython>\n\u003Ctypescript>\nInterrupts require a checkpointer.\n\n```typescript\n\u002F\u002F WRONG\nconst agent = await createDeepAgent({ interruptOn: { write_file: true } });\n\n\u002F\u002F CORRECT\nconst agent = await createDeepAgent({ interruptOn: { write_file: true }, checkpointer: new MemorySaver() });\n```\n\u003C\u002Ftypescript>\n\u003C\u002Ffix-checkpointer-for-interrupts>\n\n\u003Cfix-store-for-memory>\n\u003Cpython>\nStoreBackend requires a Store instance for persistent memory across threads.\n\n```python\n# WRONG\nagent = create_deep_agent(backend=lambda rt: StoreBackend(rt))\n\n# CORRECT\nagent = create_deep_agent(backend=lambda rt: StoreBackend(rt), store=InMemoryStore())\n```\n\u003C\u002Fpython>\n\u003Ctypescript>\nStoreBackend requires a Store instance for persistent memory across threads.\n\n```typescript\n\u002F\u002F WRONG\nconst agent = await createDeepAgent({ backend: (config) => new StoreBackend(config) });\n\n\u002F\u002F CORRECT\nconst agent = await createDeepAgent({ backend: (config) => new StoreBackend(config), store: new InMemoryStore() });\n```\n\u003C\u002Ftypescript>\n\u003C\u002Ffix-store-for-memory>\n\n\u003Cfix-thread-id-for-conversations>\n\u003Cpython>\nUse consistent thread_id to maintain conversation context across invocations.\n\n```python\n# WRONG: Each invocation is isolated\nagent.invoke({\"messages\": [{\"role\": \"user\", \"content\": \"Hi\"}]})\nagent.invoke({\"messages\": [{\"role\": \"user\", \"content\": \"What did I say?\"}]})\n\n# CORRECT\nconfig = {\"configurable\": {\"thread_id\": \"user-123\"}}\nagent.invoke({\"messages\": [...]}, config=config)\nagent.invoke({\"messages\": [...]}, config=config)\n```\n\u003C\u002Fpython>\n\u003Ctypescript>\nUse consistent thread_id to maintain conversation context across invocations.\n\n```typescript\n\u002F\u002F WRONG: Each invocation is isolated\nawait agent.invoke({ messages: [{ role: \"user\", content: \"Hi\" }] });\nawait agent.invoke({ messages: [{ role: \"user\", content: \"What did I say?\" }] });\n\n\u002F\u002F CORRECT\nconst config = { configurable: { thread_id: \"user-123\" } };\nawait agent.invoke({ messages: [...] }, config);\nawait agent.invoke({ messages: [...] }, config);\n```\n\u003C\u002Ftypescript>\n\u003C\u002Ffix-thread-id-for-conversations>\n\n\u003Cfix-frontmatter-required>\n\n```markdown\n# WRONG: Missing frontmatter in SKILL.md\n# My Skill\nThis is my skill...\n\n# CORRECT: Include YAML frontmatter\n---\nname: my-skill\ndescription: Python testing best practices with pytest fixtures and mocking\n---\n# My Skill\nThis is my skill...\n```\n\u003C\u002Ffix-frontmatter-required>\n\n\u003Cfix-backend-for-skills>\n\u003Cpython>\nSkills require a proper backend to load from the filesystem.\n\n```python\n# WRONG: Skills won't load without proper backend\nagent = create_deep_agent(skills=[\".\u002Fskills\u002F\"])\n\n# CORRECT: Use FilesystemBackend for local skills\nagent = create_deep_agent(\n backend=FilesystemBackend(root_dir=\".\", virtual_mode=True),\n skills=[\".\u002Fskills\u002F\"]\n)\n```\n\u003C\u002Fpython>\n\u003C\u002Ffix-backend-for-skills>\n\n\u003Cfix-specific-skill-descriptions>\nUse specific descriptions to help agents decide when to use a skill.\n\n```markdown\n# WRONG: Vague description\n---\nname: helper\ndescription: Helpful skill\n---\n\n# CORRECT: Specific description\n---\nname: python-testing\ndescription: Python testing best practices with pytest fixtures, mocking, and async patterns\n---\n```\n\u003C\u002Ffix-specific-skill-descriptions>\n\n\u003Cfix-subagent-skills>\n\u003Cpython>\nSkills are not inherited by subagents - provide them explicitly.\n\n```python\n# WRONG: Custom subagents don't inherit skills\nagent = create_deep_agent(\n skills=[\"\u002Fmain-skills\u002F\"],\n subagents=[{\"name\": \"helper\", ...}] # No skills\n)\n\n# CORRECT: Provide skills explicitly\nagent = create_deep_agent(\n skills=[\"\u002Fmain-skills\u002F\"],\n subagents=[{\"name\": \"helper\", \"skills\": [\"\u002Fhelper-skills\u002F\"], ...}]\n)\n```\n\u003C\u002Fpython>\n\u003C\u002Ffix-subagent-skills>\n",{"data":35,"body":36},{"name":4,"description":6},{"type":37,"children":38},"root",[39,4571],{"type":40,"tag":41,"props":42,"children":43},"element","overview",{},[44,47,113,119,203,342,1258,1917],{"type":45,"value":46},"text","\nDeep Agents are an opinionated agent framework built on LangChain\u002FLangGraph with built-in 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...}]\n)\n",[4486],{"type":40,"tag":360,"props":4487,"children":4488},{"__ignoreMap":357},[4489,4497,4504,4512,4520,4527,4534,4542,4549,4556,4564],{"type":40,"tag":364,"props":4490,"children":4491},{"class":366,"line":367},[4492],{"type":40,"tag":364,"props":4493,"children":4494},{},[4495],{"type":45,"value":4496},"# WRONG: Custom subagents don't inherit skills\n",{"type":40,"tag":364,"props":4498,"children":4499},{"class":366,"line":376},[4500],{"type":40,"tag":364,"props":4501,"children":4502},{},[4503],{"type":45,"value":445},{"type":40,"tag":364,"props":4505,"children":4506},{"class":366,"line":385},[4507],{"type":40,"tag":364,"props":4508,"children":4509},{},[4510],{"type":45,"value":4511}," skills=[\"\u002Fmain-skills\u002F\"],\n",{"type":40,"tag":364,"props":4513,"children":4514},{"class":366,"line":395},[4515],{"type":40,"tag":364,"props":4516,"children":4517},{},[4518],{"type":45,"value":4519}," subagents=[{\"name\": \"helper\", ...}] # No skills\n",{"type":40,"tag":364,"props":4521,"children":4522},{"class":366,"line":404},[4523],{"type":40,"tag":364,"props":4524,"children":4525},{},[4526],{"type":45,"value":481},{"type":40,"tag":364,"props":4528,"children":4529},{"class":366,"line":413},[4530],{"type":40,"tag":364,"props":4531,"children":4532},{"emptyLinePlaceholder":389},[4533],{"type":45,"value":392},{"type":40,"tag":364,"props":4535,"children":4536},{"class":366,"line":422},[4537],{"type":40,"tag":364,"props":4538,"children":4539},{},[4540],{"type":45,"value":4541},"# CORRECT: Provide skills explicitly\n",{"type":40,"tag":364,"props":4543,"children":4544},{"class":366,"line":431},[4545],{"type":40,"tag":364,"props":4546,"children":4547},{},[4548],{"type":45,"value":445},{"type":40,"tag":364,"props":4550,"children":4551},{"class":366,"line":439},[4552],{"type":40,"tag":364,"props":4553,"children":4554},{},[4555],{"type":45,"value":4511},{"type":40,"tag":364,"props":4557,"children":4558},{"class":366,"line":448},[4559],{"type":40,"tag":364,"props":4560,"children":4561},{},[4562],{"type":45,"value":4563}," subagents=[{\"name\": \"helper\", \"skills\": [\"\u002Fhelper-skills\u002F\"], ...}]\n",{"type":40,"tag":364,"props":4565,"children":4566},{"class":366,"line":457},[4567],{"type":40,"tag":364,"props":4568,"children":4569},{},[4570],{"type":45,"value":481},{"type":40,"tag":4572,"props":4573,"children":4574},"style",{},[4575],{"type":45,"value":4576},"html .light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html.light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html .default .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}html.dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}",{"items":4578,"total":3041},[4579,4586,4601,4619,4630,4641,4657],{"slug":4,"name":4,"fn":5,"description":6,"org":4580,"tags":4581,"stars":24,"repoUrl":25,"updatedAt":26},{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4582,4583,4584,4585],{"name":22,"slug":23,"type":16},{"name":18,"slug":19,"type":16},{"name":9,"slug":8,"type":16},{"name":14,"slug":15,"type":16},{"slug":4587,"name":4587,"fn":4588,"description":4589,"org":4590,"tags":4591,"stars":24,"repoUrl":25,"updatedAt":4600},"deep-agents-memory","implement memory and persistence for Deep Agents","INVOKE THIS SKILL when your Deep Agent needs memory, persistence, or filesystem access. Covers StateBackend (ephemeral), StoreBackend (persistent), FilesystemMiddleware, and CompositeBackend for routing.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4592,4593,4594,4597],{"name":22,"slug":23,"type":16},{"name":9,"slug":8,"type":16},{"name":4595,"slug":4596,"type":16},"Memory","memory",{"name":4598,"slug":4599,"type":16},"Storage","storage","2026-04-06T18:26:26.065654",{"slug":4602,"name":4602,"fn":4603,"description":4604,"org":4605,"tags":4606,"stars":24,"repoUrl":25,"updatedAt":4618},"deep-agents-orchestration","orchestrate subagents and tasks in Deep Agents","INVOKE THIS SKILL when using subagents, task planning, or human approval in Deep Agents. Covers SubAgentMiddleware, TodoList for planning, and HITL interrupts.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4607,4608,4611,4612,4615],{"name":22,"slug":23,"type":16},{"name":4609,"slug":4610,"type":16},"Approvals","approvals",{"name":9,"slug":8,"type":16},{"name":4613,"slug":4614,"type":16},"Multi-Agent","multi-agent",{"name":4616,"slug":4617,"type":16},"Workflow Automation","workflow-automation","2026-04-06T18:26:32.280463",{"slug":4620,"name":4620,"fn":4621,"description":4622,"org":4623,"tags":4624,"stars":24,"repoUrl":25,"updatedAt":4629},"deepagents-python-quickstart","scaffold local Deep Agents","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 to quickly build or try a Deep Agent locally.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4625,4626,4627],{"name":22,"slug":23,"type":16},{"name":9,"slug":8,"type":16},{"name":4628,"slug":347,"type":16},"Python","2026-07-24T06:09:00.291108",{"slug":4631,"name":4631,"fn":4632,"description":4633,"org":4634,"tags":4635,"stars":24,"repoUrl":25,"updatedAt":4640},"deepagents-typescript-quickstart","build Deep Agents in TypeScript","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 wants to quickly build or try a Deep Agent locally.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4636,4637,4638],{"name":22,"slug":23,"type":16},{"name":9,"slug":8,"type":16},{"name":4639,"slug":527,"type":16},"TypeScript","2026-07-24T06:09:00.673714",{"slug":4642,"name":4642,"fn":4643,"description":4644,"org":4645,"tags":4646,"stars":24,"repoUrl":25,"updatedAt":4656},"ecosystem-primer","select frameworks for LangChain and LangGraph agents","INVOKE FIRST for any LangChain \u002F LangGraph \u002F 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 which skill to load next.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4647,4648,4651,4652,4653],{"name":22,"slug":23,"type":16},{"name":4649,"slug":4650,"type":16},"AI Infrastructure","ai-infrastructure",{"name":18,"slug":19,"type":16},{"name":9,"slug":8,"type":16},{"name":4654,"slug":4655,"type":16},"LangGraph","langgraph","2026-07-24T05:42:48.348966",{"slug":4658,"name":4658,"fn":4659,"description":4660,"org":4661,"tags":4662,"stars":24,"repoUrl":25,"updatedAt":4674},"eval-engineering","create and audit Harbor agent evals","Iteratively inspect an agent repository and optional user-provided traces, interview the user, and create, run, and audit Harbor evals one at a time. Use for agent evals, Harbor tasks, benchmark cases, verifier design, or controlled agent environments.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4663,4664,4667,4670,4671],{"name":22,"slug":23,"type":16},{"name":4665,"slug":4666,"type":16},"Code Analysis","code-analysis",{"name":4668,"slug":4669,"type":16},"Evals","evals",{"name":9,"slug":8,"type":16},{"name":4672,"slug":4673,"type":16},"Testing","testing","2026-07-31T05:53:29.552458",{"items":4676,"total":4846},[4677,4698,4709,4726,4739,4754,4767,4780,4794,4804,4815,4833],{"slug":4678,"name":4678,"fn":4679,"description":4680,"org":4681,"tags":4682,"stars":4695,"repoUrl":4696,"updatedAt":4697},"analyze-market","perform market analysis and size estimation","Perform a market analysis for a product category or segment. Trigger on: market analysis, market size, TAM SAM SOM, market opportunity, industry analysis.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4683,4686,4689,4692],{"name":4684,"slug":4685,"type":16},"Marketing","marketing",{"name":4687,"slug":4688,"type":16},"Research","research",{"name":4690,"slug":4691,"type":16},"Sales","sales",{"name":4693,"slug":4694,"type":16},"Strategy","strategy",26592,"https:\u002F\u002Fgithub.com\u002Flangchain-ai\u002Fdeepagents","2026-04-18T04:46:54.557115",{"slug":4699,"name":4699,"fn":4700,"description":4701,"org":4702,"tags":4703,"stars":4695,"repoUrl":4696,"updatedAt":4708},"arxiv-search","search arXiv for academic research papers","Searches arXiv for preprints and academic papers, retrieves abstracts, and filters by topic. Use when the user asks to find research papers, search arXiv, look up preprints, find academic articles in physics, math, CS, biology, statistics, or related fields.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4704,4705],{"name":4687,"slug":4688,"type":16},{"name":4706,"slug":4707,"type":16},"Search","search","2026-05-13T06:11:01.203061",{"slug":4710,"name":4710,"fn":4711,"description":4712,"org":4713,"tags":4714,"stars":4695,"repoUrl":4696,"updatedAt":4725},"blog-post","write SEO-optimized blog posts","Write long-form blog posts with SEO optimization and clear structure.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4715,4718,4719,4722],{"name":4716,"slug":4717,"type":16},"Content Creation","content-creation",{"name":4684,"slug":4685,"type":16},{"name":4720,"slug":4721,"type":16},"SEO","seo",{"name":4723,"slug":4724,"type":16},"Writing","writing","2026-04-15T05:00:54.149813",{"slug":4727,"name":4727,"fn":4728,"description":4729,"org":4730,"tags":4731,"stars":4695,"repoUrl":4696,"updatedAt":4738},"competitor-analysis","analyze competitors and market positioning","Analyze competitors in a given market segment. Trigger on: competitive landscape, competitor analysis, market comparison, competitive positioning.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4732,4735,4736,4737],{"name":4733,"slug":4734,"type":16},"Competitive Intelligence","competitive-intelligence",{"name":4684,"slug":4685,"type":16},{"name":4687,"slug":4688,"type":16},{"name":4693,"slug":4694,"type":16},"2026-04-18T04:46:55.79306",{"slug":4740,"name":4740,"fn":4741,"description":4742,"org":4743,"tags":4744,"stars":4695,"repoUrl":4696,"updatedAt":4753},"deepagents-thread-inspector","inspect local Deep Agents conversation threads","Inspect and explain conversations in the local Deep Agents Code SQLite session store. Use as a fallback when LangSmith trace tooling is unavailable, for offline or untraced sessions, or when asked to identify or summarize a local dcode thread, inspect checkpoint metadata, list recent local threads, or parse ~\u002F.deepagents\u002F.state\u002Fsessions.db and a thread UUID or prefix.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4745,4746,4749,4750],{"name":22,"slug":23,"type":16},{"name":4747,"slug":4748,"type":16},"Debugging","debugging",{"name":9,"slug":8,"type":16},{"name":4751,"slug":4752,"type":16},"SQLite","sqlite","2026-07-24T06:08:57.102689",{"slug":4755,"name":4755,"fn":4756,"description":4757,"org":4758,"tags":4759,"stars":4695,"repoUrl":4696,"updatedAt":4766},"langgraph-docs","build stateful agents with LangGraph","Fetches and references LangGraph Python documentation to build stateful agents, create multi-agent workflows, and implement human-in-the-loop patterns. Use when the user asks about LangGraph, graph agents, state machines, agent orchestration, LangGraph API, or needs LangGraph implementation guidance.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4760,4761,4764,4765],{"name":22,"slug":23,"type":16},{"name":4762,"slug":4763,"type":16},"Documentation","documentation",{"name":4654,"slug":4655,"type":16},{"name":4613,"slug":4614,"type":16},"2026-05-13T06:11:03.650877",{"slug":4768,"name":4768,"fn":4769,"description":4770,"org":4771,"tags":4772,"stars":4695,"repoUrl":4696,"updatedAt":4779},"remember","capture knowledge into persistent memory","Review the current conversation and capture valuable knowledge — best practices, coding conventions, architecture decisions, workflows, and user feedback — into persistent memory (AGENTS.md) or reusable skills. Use when the user says: (1) remember this, (2) save what we learned, (3) update memory, (4) capture learnings.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4773,4774,4775,4778],{"name":22,"slug":23,"type":16},{"name":4762,"slug":4763,"type":16},{"name":4776,"slug":4777,"type":16},"Knowledge Management","knowledge-management",{"name":4595,"slug":4596,"type":16},"2026-05-13T06:10:58.510037",{"slug":4781,"name":4781,"fn":4782,"description":4783,"org":4784,"tags":4785,"stars":4695,"repoUrl":4696,"updatedAt":4793},"skill-creator","create agent skills and tool integrations","Guide for creating effective skills that extend agent capabilities with specialized knowledge, workflows, or tool integrations. Use this skill when the user asks to: (1) create a new skill, (2) make a skill, (3) build a skill, (4) set up a skill, (5) initialize a skill, (6) scaffold a skill, (7) update or modify an existing skill, (8) validate a skill, (9) learn about skill structure, (10) understand how skills work, or (11) get guidance on skill design patterns. Trigger on phrases like \"create a skill\", \"new skill\", \"make a skill\", \"skill for X\", \"how do I create a skill\", or \"help me build a skill\".",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4786,4787,4790],{"name":22,"slug":23,"type":16},{"name":4788,"slug":4789,"type":16},"Engineering","engineering",{"name":4791,"slug":4792,"type":16},"Plugin Development","plugin-development","2026-05-13T06:10:59.88449",{"slug":4795,"name":4795,"fn":4796,"description":4797,"org":4798,"tags":4799,"stars":4695,"repoUrl":4696,"updatedAt":4803},"social-media","create optimized social media posts","Create social media posts optimized for engagement across platforms.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4800,4801,4802],{"name":4716,"slug":4717,"type":16},{"name":4684,"slug":4685,"type":16},{"name":4723,"slug":4724,"type":16},"2026-04-15T05:00:55.37452",{"slug":4805,"name":4805,"fn":4806,"description":4807,"org":4808,"tags":4809,"stars":4695,"repoUrl":4696,"updatedAt":4814},"web-research","conduct and synthesize web research","Searches multiple web sources, synthesizes findings, and produces cited research reports using delegated subagents. Use when the user asks to research a topic online, search the web, look something up, find current information, compare options, or produce a research report.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4810,4811,4812,4813],{"name":22,"slug":23,"type":16},{"name":4613,"slug":4614,"type":16},{"name":4687,"slug":4688,"type":16},{"name":4706,"slug":4707,"type":16},"2026-05-13T06:11:04.930044",{"slug":4816,"name":4816,"fn":4817,"description":4818,"org":4819,"tags":4820,"stars":4830,"repoUrl":4831,"updatedAt":4832},"mermaid-diagrams","embed Mermaid diagrams in documentation","Embed Mermaid diagrams in generated wiki pages. Use whenever documenting a runtime or request flow, a call sequence, a state machine or lifecycle, a data model or entity relationships, or non-trivial control flow, since these are clearer as a diagram than as prose. Also use when an update run touches a page that already contains a mermaid fence, or a page that contains a text fence a previous run degraded.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4821,4824,4825,4827],{"name":4822,"slug":4823,"type":16},"Diagrams","diagrams",{"name":4762,"slug":4763,"type":16},{"name":4826,"slug":2056,"type":16},"Markdown",{"name":4828,"slug":4829,"type":16},"Technical Writing","technical-writing",12181,"https:\u002F\u002Fgithub.com\u002Flangchain-ai\u002Fopenwiki","2026-07-24T06:09:01.089597",{"slug":4834,"name":4834,"fn":4835,"description":4836,"org":4837,"tags":4838,"stars":4830,"repoUrl":4831,"updatedAt":4845},"write-connector","implement OpenWiki source connectors","Add a new built-in OpenWiki source connector. Use when a user asks to create or implement an OpenWiki connector.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[4839,4842],{"name":4840,"slug":4841,"type":16},"API Development","api-development",{"name":4843,"slug":4844,"type":16},"Integrations","integrations","2026-07-18T05:48:23.961804",41]