deep-agents-core

import { createDeepAgent } from "deepagents";
import { tool } from "@langchain/core/tools";
import { z } from "zod";
 
const getWeather = tool(
  async ({ city }) => `It is always sunny in ${city}`,
  { name: "get_weather", description: "Get weather for a city", schema: z.object({ city: z.string() }) }
);
 
const agent = await createDeepAgent({
  model: "claude-sonnet-4-5-20250929",
  tools: [getWeather],
  systemPrompt: "You are a helpful assistant"
});
 
const config = { configurable: { thread_id: "user-123" } };
const result = await agent.invoke({
  messages: [{ role: "user", content: "What's the weather in Tokyo?" }]
}, config);

from deepagents import create_deep_agent
from deepagents.backends import FilesystemBackend
from langgraph.checkpoint.memory import MemorySaver
from langgraph.store.memory import InMemoryStore
 
agent = create_deep_agent(
    name="my-assistant",
    model="claude-sonnet-4-5-20250929",
    tools=[custom_tool1, custom_tool2],
    system_prompt="Custom instructions",
    subagents=[research_agent, code_agent],
    backend=FilesystemBackend(root_dir=".", virtual_mode=True),
    interrupt_on={"write_file": True},
    skills=["./skills/"],
    checkpointer=MemorySaver(),
    store=InMemoryStore()
)

import { createDeepAgent, FilesystemBackend } from "deepagents";
import { MemorySaver, InMemoryStore } from "@langchain/langgraph";
 
const agent = await createDeepAgent({
  name: "my-assistant",
  model: "claude-sonnet-4-5-20250929",
  tools: [customTool1, customTool2],
  systemPrompt: "Custom instructions",
  subagents: [researchAgent, codeAgent],
  backend: new FilesystemBackend({ rootDir: ".", virtualMode: true }),
  interruptOn: { write_file: true },
  skills: ["./skills/"],
  checkpointer: new MemorySaver(),
  store: new InMemoryStore()
});

skills/
└── my-skill/
    ├── SKILL.md        # Required: main skill file
    ├── examples.py     # Optional: supporting files
    └── templates/      # Optional: templates

---
name: my-skill
description: Clear, specific description of what this skill does
---
 
# Skill Name
 
## Overview
Brief explanation of the skill's purpose.
 
## When to Use
Conditions when this skill applies.
 
## Instructions
Step-by-step guidance for the agent.

from deepagents import create_deep_agent
from deepagents.backends import FilesystemBackend
from langgraph.checkpoint.memory import MemorySaver
 
agent = create_deep_agent(
    backend=FilesystemBackend(root_dir=".", virtual_mode=True),
    skills=["./skills/"],
    checkpointer=MemorySaver()
)
 
result = agent.invoke({
    "messages": [{"role": "user", "content": "Use the python-testing skill"}]
}, config={"configurable": {"thread_id": "session-1"}})

import { createDeepAgent, FilesystemBackend } from "deepagents";
import { MemorySaver } from "@langchain/langgraph";
 
const agent = await createDeepAgent({
  backend: new FilesystemBackend({ rootDir: ".", virtualMode: true }),
  skills: ["./skills/"],
  checkpointer: new MemorySaver()
});
 
const result = await agent.invoke({
  messages: [{ role: "user", content: "Use the python-testing skill" }]
}, { configurable: { thread_id: "session-1" } });

from deepagents import create_deep_agent
from deepagents.backends import StoreBackend
from deepagents.backends.utils import create_file_data
from langgraph.store.memory import InMemoryStore
 
store = InMemoryStore()
 
# Load skill content into store
skill_content = """---
name: python-testing
description: Best practices for Python testing with pytest
---
# Python Testing Skill
..."""
 
store.put(
    namespace=("filesystem",),
    key="/skills/python-testing/SKILL.md",
    value=create_file_data(skill_content)
)
 
agent = create_deep_agent(
    backend=lambda rt: StoreBackend(rt),
    store=store,
    skills=["/skills/"]
)

# WRONG
agent = create_deep_agent(interrupt_on={"write_file": True})
 
# CORRECT
agent = create_deep_agent(interrupt_on={"write_file": True}, checkpointer=MemorySaver())

// WRONG
const agent = await createDeepAgent({ interruptOn: { write_file: true } });
 
// CORRECT
const agent = await createDeepAgent({ interruptOn: { write_file: true }, checkpointer: new MemorySaver() });

# WRONG
agent = create_deep_agent(backend=lambda rt: StoreBackend(rt))
 
# CORRECT
agent = create_deep_agent(backend=lambda rt: StoreBackend(rt), store=InMemoryStore())

// WRONG
const agent = await createDeepAgent({ backend: (config) => new StoreBackend(config) });
 
// CORRECT
const agent = await createDeepAgent({ backend: (config) => new StoreBackend(config), store: new InMemoryStore() });

# WRONG: Each invocation is isolated
agent.invoke({"messages": [{"role": "user", "content": "Hi"}]})
agent.invoke({"messages": [{"role": "user", "content": "What did I say?"}]})
 
# CORRECT
config = {"configurable": {"thread_id": "user-123"}}
agent.invoke({"messages": [...]}, config=config)
agent.invoke({"messages": [...]}, config=config)

// WRONG: Each invocation is isolated
await agent.invoke({ messages: [{ role: "user", content: "Hi" }] });
await agent.invoke({ messages: [{ role: "user", content: "What did I say?" }] });
 
// CORRECT
const config = { configurable: { thread_id: "user-123" } };
await agent.invoke({ messages: [...] }, config);
await agent.invoke({ messages: [...] }, config);

# WRONG: Missing frontmatter in SKILL.md
# My Skill
This is my skill...
 
# CORRECT: Include YAML frontmatter
---
name: my-skill
description: Python testing best practices with pytest fixtures and mocking
---
# My Skill
This is my skill...

# WRONG: Skills won't load without proper backend
agent = create_deep_agent(skills=["./skills/"])
 
# CORRECT: Use FilesystemBackend for local skills
agent = create_deep_agent(
    backend=FilesystemBackend(root_dir=".", virtual_mode=True),
    skills=["./skills/"]
)

# WRONG: Vague description
---
name: helper
description: Helpful skill
---
 
# CORRECT: Specific description
---
name: python-testing
description: Python testing best practices with pytest fixtures, mocking, and async patterns
---

# WRONG: Custom subagents don't inherit skills
agent = create_deep_agent(
    skills=["/main-skills/"],
    subagents=[{"name": "helper", ...}]  # No skills
)
 
# CORRECT: Provide skills explicitly
agent = create_deep_agent(
    skills=["/main-skills/"],
    subagents=[{"name": "helper", "skills": ["/helper-skills/"], ...}]
)