deep-agent-cli

A command-line toolkit for running or building a Deep Agent in a terminal, with options for project files, shell commands, models, and custom prompts.

In plain words
What is it for?
Use it to start an interactive terminal agent, run tasks in a chosen directory, build a custom coding CLI, and connect file and shell access.
Why use it?
It provides a way to work with an AI coding agent directly from the command line instead of building the entire interface yourself.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/bdiasti/maestro-bundle-cli/deep-agent-cli
Any agent
npx skills add bdiasti/maestro-bundle-cli --skill deep-agent-cli
Clone the repo
git clone --depth 1 https://github.com/bdiasti/maestro-bundle-cli

Made for: Claude Code, Codex.

Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 984 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00039 $0.00984
Opus 5 $0.00019 $0.00492
Sonnet 5 $0.00008 $0.00197
Haiku 4.5 $0.00004 $0.00098

Measured 2d ago against content hash 2f0fa374b49a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

deep-agent-cli scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

templates/bundle-ai-agents-deep/skills/deep-agent-cli/SKILL.md · 159 lines

How it starts

The opening of the file, as written. The whole thing — 159 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Deep Agents CLI

Build a terminal-based coding agent similar to Claude Code using the Deep Agents CLI or by creating your own CLI interface.

When to Use

  • When you want a Claude Code-like experience in the terminal
  • When building a CLI tool for AI-assisted coding
  • When running Deep Agents interactively

Available Operations

  1. Install and use the official Deep Agents CLI
  2. Build a custom CLI with rich terminal UI
  3. Configure CLI with local file access + shell
  4. Add skills and AGENTS.md to CLI agent

Multi-Step Workflow

Step 1: Install Deep Agents CLI

pip install deepagents
# or
uv tool install deepagents

Step 2: Run the CLI

# Start interactive session
deepagents

# Start with a specific model
deepagents --model anthropic:claude-sonnet-4-6

# Start in a specific directory
deepagents --dir ./my-project

# Start with a prompt
deepagents "Fix the failing tests in src/auth/"

Step 3: Build Custom CLI

# cli.py
import asyncio
import sys
from deepagents import create_deep_agent
from deepagents.backends import LocalShellBackend
from langgraph.checkpoint.memory import MemorySaver

async def main():
    # Full coding agent with file + shell access
    agent = create_deep_agent(
        model="anthropic:claude-sonnet-4-6",
        backend=LocalShellBackend(root_dir="."),
        skills=["./skills/"],
        memory=["/AGENTS.md"],
        checkpointer=MemorySaver(),
        system_prompt="You are a coding assistant. Follow the project conventions."
    )

    config = {"configurable": {"thread_id": "cli-session"}}

    # One-shot mode
    if len(sys.argv) > 1:
        prompt = " ".join(sys.argv[1:])
        async for event in agent.astream_events(
            {"messages": [{"role": "user", "content": prompt}]},
            config=config, version="v2"
        ):
            if event["event"] == "on_chat_model_stream":
                print(event["data"]["chunk"].content, end="", flush=True)
        print()
        return

    # Interactive mode
    print("Coding Agent (type 'exit' to quit)\n")
    while True:
        try:
            user_input = input("> ")
        except (EOFError, KeyboardInterrupt):
            break

        if user_input.lower() in ("exit", "quit"):
            break

        async for event in agent.astream_events(
            {"messages": [{"role": "user", "content": user_input}]},
            config=config, version="v2"
        ):
            if event["event"] == "on_chat_model_stream":
                print(event["data"]["chunk"].content, end="", flush=True)
        print("\n")

asyncio.run(main())

Read the full file on GitHub · 159 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 159 lines · 39 tokens per session scan A 2f0fa374b49a

Subscribe to this mod's changes

deep-agent-cli is a skill published in the GitHub repository bdiasti/maestro-bundle-cli (21 stars, last pushed 5mo ago), licensed MIT. It adds 39 tokens to every session and 984 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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