deepagents-cli

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Using the Deep Agents CLI - terminal interface, persistent memory with AGENTS.md, project conventions, skills directories, and CLI commands.

christian-bromann By christian-bromann schedule Updated 2/14/2026

name: deepagents-cli description: Using the Deep Agents CLI - terminal interface, persistent memory with AGENTS.md, project conventions, skills directories, and CLI commands. language: js

deepagents-cli (JavaScript/TypeScript)

Overview

Open-source coding assistant for terminal with persistent memory. Capabilities: file operations, shell execution, web search, HTTP requests, task planning, memory, HITL, and skills.

Installation

npm install -g deepagents-cli

# Start CLI
deepagents

CLI Commands

Command Description
deepagents Start the CLI
deepagents list List agents
deepagents skills Manage skills
deepagents help Show help
deepagents reset --agent NAME Clear memory
deepagents threads list List sessions
deepagents threads delete ID Delete session

Memory (AGENTS.md)

Global Memory

~/.deepagents/<agent_name>/AGENTS.md

Store: personality, coding preferences, communication style

Project Memory

.deepagents/AGENTS.md (requires .git folder)

Store: project architecture, conventions, team guidelines

Skills

# Create skill
deepagents skills create test-skill

# Project skill
cd /path/to/project
deepagents skills create test-skill --project

Locations:

  • Global: ~/.deepagents/<agent_name>/skills/
  • Project: .deepagents/skills/

Code Examples

Programmatic CLI Usage

import { createDeepAgent, FilesystemBackend } from "deepagents";
import { MemorySaver } from "@langchain/langgraph";

// Create an agent with the same capabilities as the CLI
const agent = await createDeepAgent({
  name: "my-assistant",
  backend: new FilesystemBackend({ rootDir: ".", virtualMode: true }),
  checkpointer: new MemorySaver(),
  skills: ["./.deepagents/skills/"],
});

// Invoke like the CLI would
const result = await agent.invoke(
  {
    messages: [{ role: "user", content: "Refactor the auth module" }],
  },
  { configurable: { thread_id: "session-1" } }
);

Managing Skills via CLI

# Create a new global skill
deepagents skills create my-skill

# Create a project-scoped skill
cd /path/to/project
deepagents skills create my-skill --project

# List available skills
deepagents skills list

Managing Memory via CLI

# Reset agent memory
deepagents reset --agent my-assistant

# List conversation threads
deepagents threads list

# Delete a specific thread
deepagents threads delete session-1

Decision Table: Memory vs Skills

Content Location Why
Coding style AGENTS.md (global) Always relevant
Project arch AGENTS.md (project) Project context
Testing workflow Skill Task-specific
Large docs Skill On-demand loading

Boundaries

What CAN Configure

✅ Agent name and personality via AGENTS.md ✅ Project-specific conventions via project AGENTS.md ✅ Custom skills (global or project-scoped) ✅ Model selection via environment variables ✅ Thread management (list, delete) ✅ API keys for web search and model providers

What CANNOT Configure

❌ Core CLI commands (fixed set) ❌ Built-in tool names (ls, read_file, write_file, etc.) ❌ Middleware order in CLI mode ❌ AGENTS.md file format (must be markdown) ❌ Skills protocol format (must follow SKILL.md spec)

Gotchas

1. Project Root Needs .git

# ❌ No project memory
cd /project  # No .git
deepagents

# ✅ Init git
git init
deepagents

2. Skills Location

# ❌ Wrong
/project/skills/SKILL.md

# ✅ Correct
/project/.deepagents/skills/skill-name/SKILL.md

3. Web Search Needs API Key

export TAVILY_API_KEY="your-key"
deepagents

Full Documentation

Install via CLI
npx skills add https://github.com/christian-bromann/langchain-skills --skill deepagents-cli
Repository Details
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article Path SKILL.md
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