deep-agents-memory — Claude Code skill: memory backends
A skill that maps where a Deep Agent keeps its files: thread state, a persistent store, or the real disk. Useful once the agent starts dropping context.
npx skills add langchain-ai/langchain-skills --skill deep-agents-memory -a claude-codeWhat deep-agents-memory does
The skill covers the backends behind file operations in deepagents. StateBackend is the default: files sit in thread state and vanish when the thread ends. StoreBackend keeps them across threads and sessions.
FilesystemMiddleware exposes the model to a fixed tool set: ls, read_file, write_file, edit_file, glob, grep. Their names are not configurable. FilesystemBackend points at the real disk through root_dir and caps reach with virtual_mode. Keep it out of web servers, the skill says, and use StateBackend or a sandbox there instead.
CompositeBackend routes by path prefix, so /draft.txt can stay ephemeral while /memories/ lands in the store and shows up in the next thread. That routing is where setups break: StoreBackend needs a real store instance passed to create_deep_agent, InMemoryStore() in the sample. Snippets come in Python and TypeScript, with a separate recipe for reaching store from a custom @tool.
What it helps with
- carry user preferences across thread restarts
- route one path prefix to persistent storage
- let the agent edit disk files with write confirmation
- read saved memory from a custom tool
- stop losing scratch files when a thread ends
Example prompts for the agent
- Set up a `CompositeBackend` so `/memories/` survives a thread restart
- Switch to `FilesystemBackend` with `virtual_mode` and ask before every `write_file`
- Why can't thread 2 read what thread 1 saved to `/memories/style.txt`?
How to install deep-agents-memory
1Skills CLI (Vercel)
npx skills add langchain-ai/langchain-skills --skill deep-agents-memory -a claude-code2Manually: put the files in place
~/.claude/skills/deep-agents-memory/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/deep-agents-memory/
1Skills CLI (Vercel)
npx skills add langchain-ai/langchain-skills --skill deep-agents-memory -a codex2Manually: put the files in place
.agents/skills/deep-agents-memory/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add langchain-ai/langchain-skills --skill deep-agents-memory -a cursor2Manually: put the files in place
.cursor/skills/deep-agents-memory/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install langchain-ai/langchain-skills deep-agents-memory2Manually: put the files in place
.github/skills/deep-agents-memory/SKILL.md1Skills CLI (Vercel)
npx skills add langchain-ai/langchain-skills --skill deep-agents-memory -a gemini-cli2Platform CLI
gemini skills install https://github.com/langchain-ai/langchain-skills --path config/skills/deep-agents-memoryManually: put the files in place
.devin/skills/deep-agents-memory/SKILL.mdThe legacy .windsurf/skills/ path still works
Skills CLI (Vercel)
npx skills add langchain-ai/langchain-skills --skill deep-agents-memory -a opencodeClaude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
From the same set14
The whole set →Similar
Questions about deep-agents-memory
How do I install deep-agents-memory in Claude Code?
Run npx skills add langchain-ai/langchain-skills --skill deep-agents-memory -a claude-code. The skill file lands at ~/.claude/skills/deep-agents-memory/SKILL.md.
What does deep-agents-memory do?
It explains the file and memory backends in Deep Agents and which one fits which job. Python and TypeScript examples cover StateBackend, StoreBackend, CompositeBackend and FilesystemBackend.
Does StoreBackend work on its own?
No, it needs a store instance handed to create_deep_agent, such as InMemoryStore() from langgraph.store.memory. Switch the backend without it and persistence never kicks in.
Source text
SKILL.md · MIT
---
name: deep-agents-memory
description: "INVOKE THIS SKILL when your Deep Agent needs memory, persistence, or filesystem access. Covers StateBackend (ephemeral), StoreBackend (persistent), FilesystemMiddleware, and CompositeBackend for routing."
---
<overview>
Deep Agents use pluggable backends for file operations and memory:
**Short-term (StateBackend)**: Persists within a single thread, lost when thread ends
**Long-term (StoreBackend)**: Persists across threads and sessions
**Hybrid (CompositeBackend)**: Route different paths to different backends
FilesystemMiddleware provides tools: `ls`, `read_file`, `write_file`, `edit_file`, `glob`, `grep`
</overview>
<backend-selection>
| Use Case | Backend | Why |
|----------|---------|-----|
| Temporary working files | StateBackend | Default, no setup |
| Local development CLI | FilesystemBackend | Direct disk access |
| Cross-session memory | StoreBackend | Persists across threads |
| Hybrid storage | CompositeBackend | Mix ephemeral + persistent |
</backend-selection>
<ex-default-state-backend>
<python>
Default StateBackend stores files ephemerally within a thread.
```python
from deepagents import create_deep_agent
agent = create_deep_agent() # Default: StateBackend
result = agent.invoke({
"messages": [{"role": "user", "content": "Write notes to /draft.txt"}]
}, config={"configurable": {"thread_id": "thread-1"}})
# /draft.txt is lost when thread ends
```
</python>
<typescript>
Default StateBackend stores files ephemerally within a thread.
```typescript
import { createDeepAgent } from "deepagents";
const agent = await createDeepAgent(); // Default: StateBackend
const result = await agent.invoke({
messages: [{ role: "user", content: "Write notes to /draft.txt" }]
}, { configurable: { thread_id: "thread-1" } });
// /draft.txt is lost when thread ends
```
</typescript>
</ex-default-state-backend>
<ex-composite-backend-for-hybrid>
<python>
Configure CompositeBackend to route paths to different storage backends.
```python
from deepagents import create_deep_agent
from deepagents.backends import CompositeBackend, StateBackend, StoreBackend
from langgraph.store.memory import InMemoryStore
store = InMemoryStore()
composite_backend = lambda rt: CompositeBackend(
default=StateBackend(rt),
routes={"/memories/": StoreBackend(rt)}
)
agent = create_deep_agent(backend=composite_backend, store=store)
# /draft.txt -> ephemeral (StateBackend)
# /memories/user-prefs.txt -> persistent (StoreBackend)
```
</python>
<typescript>
Configure CompositeBackend to route paths to different storage backends.
```typescript
import { createDeepAgent, CompositeBackend, StateBackend, StoreBackend } from "deepagents";
import { InMemoryStore } from "@langchain/langgraph";
const store = new InMemoryStore();
const agent = await createDeepAgent({
backend: (config) => new CompositeBackend(
new StateBackend(config),
{ "/memories/": new StoreBackend(config) }
),
store
});
// /draft.txt -> ephemeral (StateBackend)
// /memories/user-prefs.txt -> persistent (StoreBackend)
```
</typescript>
</ex-composite-backend-for-hybrid>
<ex-cross-session-memory>
<python>
Files in /memories/ persist across threads via StoreBackend routing.
```python
# Using CompositeBackend from previous example
config1 = {"configurable": {"thread_id": "thread-1"}}
agent.invoke({"messages": [{"role": "user", "content": "Save to /memories/style.txt"}]}, config=config1)
config2 = {"configurable": {"thread_id": "thread-2"}}
agent.invoke({"messages": [{"role": "user", "content": "Read /memories/style.txt"}]}, config=config2)
# Thread 2 can read file saved by Thread 1
```
</python>
<typescript>
Files in /memories/ persist across threads via StoreBackend routing.
```typescript
// Using CompositeBackend from previous example
const config1 = { configurable: { thread_id: "thread-1" } };
await agent.invoke({ messages: [{ role: "user", content: "Save to /memories/style.txt" }] }, config1);
const config2 = { configurable: { thread_id: "thread-2" } };
await agent.invoke({ messages: [{ role: "user", content: "Read /memories/style.txt" }] }, config2);
// Thread 2 can read file saved by Thread 1
```
</typescript>
</ex-cross-session-memory>
<ex-filesystem-backend-local-dev>
<python>
Use FilesystemBackend for local development with real disk access and human-in-the-loop.
```python
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), # Restrict access
interrupt_on={"write_file": True, "edit_file": True},
checkpointer=MemorySaver()
)
# Agent can read/write actual files on disk
```
</python>
<typescript>
Use FilesystemBackend for local development with real disk access and human-in-the-loop.
```typescript
import { createDeepAgent, FilesystemBackend } from "deepagents";
import { MemorySaver } from "@langchain/langgraph";
const agent = await createDeepAgent({
backend: new FilesystemBackend({ rootDir: ".", virtualMode: true }),
interruptOn: { write_file: true, edit_file: true },
checkpointer: new MemorySaver()
});
```
</typescript>
**Security: Never use FilesystemBackend in web servers - use StateBackend or sandbox instead.**
</ex-filesystem-backend-local-dev>
<ex-store-in-custom-tools>
<python>
Access the store directly in custom tools for long-term memory operations.
```python
from langchain.tools import tool, ToolRuntime
from langchain.agents import create_agent
from langgraph.store.memory import InMemoryStore
@tool
def get_user_preference(key: str, runtime: ToolRuntime) -> str:
"""Get a user preference from long-term storage."""
store = runtime.store
result = store.get(("user_prefs",), key)
return str(result.value) if result else "Not found"
@tool
def save_user_preference(key: str, value: str, runtime: ToolRuntime) -> str:
"""Save a user preference to long-term storage."""
store = runtime.store
store.put(("user_prefs",), key, {"value": value})
return f"Saved {key}={value}"
store = InMemoryStore()
agent = create_agent(
model="gpt-4.1",
tools=[get_user_preference, save_user_preference],
store=store
)
```
</python>
</ex-store-in-custom-tools>
<boundaries>
### What Agents CAN Configure
- Backend type and configuration
- Routing rules for CompositeBackend
- Root directory for FilesystemBackend
- Human-in-the-loop for file operations
### What Agents CANNOT Configure
- Tool names (ls, read_file, write_file, edit_file, glob, grep)
- Access files outside virtual_mode restrictions
- Cross-thread file access without proper backend setup
</boundaries>
<fix-storebackend-requires-store>
<python>
StoreBackend requires a store instance.
```python
# WRONG
agent = create_deep_agent(backend=lambda rt: StoreBackend(rt))
# CORRECT
agent = create_deep_agent(backend=lambda rt: StoreBackend(rt), store=InMemoryStore())
```
</python>
<typescript>
StoreBackend requires a store instance.
```typescript
// WRONG
const agent = await createDeepAgent({ backend: (c) => new StoreBackend(c) });
// CORRECT
const agent = await createDeepAgent({ backend: (c) => new StoreBackend(c), store: new InMemoryStore() });
```
</typescript>
</fix-storebackend-requires-store>
<fix-statebackend-files-dont-persist>
<python>
StateBackend files are thread-scoped - use same thread_id or StoreBackend for cross-thread access.
```python
# WRONG: thread-2 can't read file from thread-1
agent.invoke({"messages": [...]}, config={"configurable": {"thread_id": "thread-1"}}) # Write
agent.invoke({"messages": [...]}, config={"configurable": {"thread_id": "thread-2"}}) # File not found!
```
</python>
<typescript>
StateBackend files are thread-scoped - use same thread_id or StoreBackend for cross-thread access.
```typescript
// WRONG: thread-2 can't read file from thread-1
await agent.invoke({ messages: [...] }, { configurable: { thread_id: "thread-1" } }); // Write
await agent.invoke({ messages: [...] }, { configurable: { thread_id: "thread-2" } }); // File not found!
```
</typescript>
</fix-statebackend-files-dont-persist>
<fix-path-prefix-for-persistence>
<python>
Path must match CompositeBackend route prefix for persistence.
```python
# With routes={"/memories/": StoreBackend(rt)}:
agent.invoke(...) # /prefs.txt -> ephemeral (no match)
agent.invoke(...) # /memories/prefs.txt -> persistent (matches route)
```
</python>
<typescript>
Path must match CompositeBackend route prefix for persistence.
```typescript
// With routes: { "/memories/": StoreBackend }:
await agent.invoke(...); // /prefs.txt -> ephemeral (no match)
await agent.invoke(...); // /memories/prefs.txt -> persistent (matches route)
```
</typescript>
</fix-path-prefix-for-persistence>
<fix-production-store>
<python>
Use PostgresStore for production (InMemoryStore lost on restart).
```python
# WRONG # CORRECT
store = InMemoryStore() store = PostgresStore(connection_string="postgresql://...")
```
</python>
<typescript>
Use PostgresStore for production (InMemoryStore lost on restart).
```typescript
// WRONG // CORRECT
const store = new InMemoryStore(); const store = new PostgresStore({ connectionString: "..." });
```
</typescript>
</fix-production-store>
<fix-filesystem-backend-needs-virtual-mode>
<python>
Enable virtual_mode=True to restrict path access (prevents ../ and ~/ escapes).
```python
backend = FilesystemBackend(root_dir="/project", virtual_mode=True) # Secure
```
</python>
</fix-filesystem-backend-needs-virtual-mode>
<fix-longest-prefix-match>
<python>
CompositeBackend matches longest prefix first.
```python
routes = {"/mem/": StoreBackend(rt), "/mem/temp/": StateBackend(rt)}
# /mem/file.txt -> StoreBackend, /mem/temp/file.txt -> StateBackend (longer match)
```
</python>
</fix-longest-prefix-match>
© langchain-ai · MIT · langchain-ai/langchain-skills