Grok Cli logo

Grok Cli

Community
scarletkc
grok-cli

Delegate bounded tasks to Grok Build from a supervising agent such as Codex. Use when the user asks Grok to investigate, review, implement, or provide another perspective, or when a distinct coding agent would materially help. Includes a background ACP client for progress, follow-up prompts, permissions, and cancellation.

Overview

Publisherscarletkc
Repositoryagents
Skill namegrok-cli
Stars
225
Forks
12
Bundled files
5
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by scarletkc on GitHub. Read the source before you install it.

Installation

Install the Grok Cli AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/scarletkc/agents/tree/main/skills/grok-cli
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/scarletkc/agents.git /tmp/agents
mkdir -p .claude/skills
cp -r /tmp/agents/skills/grok-cli .claude/skills/grok-cli
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Grok Cli in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Grok Cli on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Grok Cli is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Grok CLI

Use Grok Build as a separate coding agent on the same machine. The bundled client launches grok agent --no-leader stdio, keeps its ACP session open, and returns a task ID immediately. This is an external task: it does not appear in Codex's native spawn_agent tree or inherit its conversation.

Grok Build must already be installed and configured. Use the project's Python 3.12+ interpreter to run scripts/grok.py; the client uses only the standard library. If the project has no interpreter, uv run --python 3.12 <script> ... also works. Resolve the script relative to this installed skill, not the repository being investigated.

Delegate a task

Give Grok the goal, absolute working directory, relevant files and evidence, scope boundaries, and the check that proves completion. It cannot see the conversation that led to the assignment. Keep independent work with the supervising agent while Grok runs.

Use a UTF-8 prompt file for substantial instructions. In these examples, <script> is the absolute path to this skill's scripts/grok.py:

sh
python <script> start --cwd <absolute-project-path> --prompt-file <task-file>
python <script> wait <task_id> --timeout 30
python <script> status <task_id>
python <script> reply <task_id> --prompt-file <follow-up-file>
python <script> cancel <task_id>
python <script> close <task_id>

Retain the returned task_id. Use wait when there is no independent work left; its timeout returns the current state without cancelling the task. Use reply after the current turn finishes to continue the same Grok session. A running turn must finish or acknowledge cancellation before a follow-up is accepted. Close the task once no more follow-ups are needed.

The helper's --help is the command reference. For output fields, storage, timeouts, and troubleshooting, read references/client.md.

Configuration and permissions

Inherit Grok's model, authentication, and permission configuration unless the task requires a specific override. Subscription login, API keys, and configured providers are Grok's concern; do not change the user's configuration or choose another authentication route to get past a failure. The helper uses Grok's advertised noninteractive default authentication method when available. Interactive authentication is completed separately through Grok itself.

start --model, --effort, --permission-mode, and --sandbox are per-task overrides. Omit them when no override is needed. Do not use a permission bypass merely to avoid handling an approval request.

Choose --effort for the delegated task. Honor the user's explicit choice; otherwise weigh complexity, the cost of an incorrect result, and how easily the result can be checked. Make routine choices without asking the user:

  • Simple chat, rewriting, or mechanical work can use a lower effort level.
  • Ordinary implementation and analysis generally suit a middle level.
  • Difficult debugging and consequential code review may justify a higher level.

These are starting points, not fixed task-to-level rules. Use only levels known to be supported by the selected model. When support or the appropriate level is uncertain, omit --effort and inherit Grok's configured value.

Match permissions to the authorized work. Preserve read-only restrictions for read-only assignments; allow the necessary file edits and checks for an authorized implementation within its scope. Task complexity and reasoning effort do not expand that authorization.

When status is needs_approval, inspect pending_permissions and answer the relevant request with:

sh
python <script> permission <task_id> --request-id <request_id> --option-id <optionId>

Select an option Grok actually offered. Approve actions already covered by the user's assignment; prefer a single-use approval. Decisions beyond that scope stay with the user. Configured Grok allow rules can execute tools without producing an ACP approval request. A read-only task prompt or refusing an ACP request is not an OS sandbox; Codex's sandbox does not configure Grok's. Do not promise enforced isolation without verifying Grok's sandbox on the target platform.

Supervise the result

Avoid simultaneous edits to the same files. Use a separate worktree when both agents need to edit overlapping code, and pass its absolute path as --cwd; the helper does not create worktrees.

Read status, closed, stop_reason, and error together. A returned task ID means the worker started, not that Grok authenticated or finished. completed means Grok ended its turn, not that its claims were verified. Inspect the actual diff or cited evidence and run the relevant checks.

If Grok is unavailable or an installation, configuration, authentication, tool, or process failure blocks the task, explicitly tell the user what failed and which work remains incomplete. Inspect any partial result before retrying. Do not silently substitute your own work, another agent, or another provider for the requested Grok task. Report what Grok contributed and what the supervising agent verified. Committing, publishing, and other external actions keep the authorization boundaries of the original task.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Grok Cli AI skill do?

Delegate bounded tasks to Grok Build from a supervising agent such as Codex. Use when the user asks Grok to investigate, review, implement, or provide another perspective, or when a distinct coding agent would materially help. Includes a background ACP client for progress, follow-up prompts, permissions, and cancellation.

Why use Grok Cli on TypingMind?

Because you install it once and use it with any model. Grok Cli is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Grok Cli in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/scarletkc/agents/tree/main/skills/grok-cli. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Grok Cli?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Grok Cli?

As many as you like. As long as a model supports skills, you can use Grok Cli with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Grok Cli AI skill free?

Yes. It is published on GitHub by scarletkc under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇