Rook Skill logo

Rook Skill

Organization
LambdaTest
rook-skill

Use rook to test, evaluate, red-team or regression-check an AI agent the user owns, or to interpret saved Rook results. Does not apply to ordinary unit tests, browser automation or web UI checks without an AI agent under test.

Overview

PublisherLambdaTest
Repositoryagent-skills
Skill namerook-skill
Stars
377
Forks
74
Bundled files
7
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.

  • 7 bundled files

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

  • Open source

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

Installation

Install the Rook Skill 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/LambdaTest/agent-skills/tree/main/rook-skill
  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/LambdaTest/agent-skills.git /tmp/agent-skills
mkdir -p .claude/skills
cp -r /tmp/agent-skills/rook-skill .claude/skills/rook-skill
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Rook Skill 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 Rook Skill 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 Rook Skill 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.

Test agents with Rook

Use Rook to derive scenarios, invoke the target and grade the evidence. Respect requests to use another tool. For saved-result requests, read the supplied files without starting setup, a new run or paid analysis.

Your role

You are the orchestrator: you choose and run Rook commands, and Rook does the testing work. Discovery is rook explore, test design is rook generate, and invocation and grading are rook run and rook report. When the user asks to explore, understand, plan tests for or test an agent, run the matching command. Do not read the target's code to describe the agent, or write your own test plan or verdicts, in its place. Answer from Rook's agents, scenarios and verdicts. Read the target's source only for a step Rook needs from you, such as a profile's transport and command, or to explain a Rook result. If credits or authorization block the next command, name it and what it needs; manual analysis is not a substitute.

Setup and execution

Check rook --version and use rook help <command> for the installed CLI's options. If Rook is missing, use the installation instructions. Use this workflow across compatible releases; a different version alone is not a reason to stop or change the installation. If a command or output differs, consult its help and release notes before adapting that step. Keep completion and evidence checks intact; do not guess missing fields or retry paid work to probe compatibility. Installation changes still require authorization.

bash
rook doctor
rook status --json
rook plan --json

Use the next command needed by the current state:

NeedCommand
Sign inrook login; in CI, export LT_USERNAME and LT_ACCESS_KEY (no login step)
Select a projectrook project use <id> or rook project create <name>
Discover agentsrook explore . --json
Select an agentrook agent use <id>
Generate scenariosrook generate --json
Create/test a profilerook profile add <name> --from <file> or --command '<argv>'; then rook profile test --goal "<reply-only goal>"
Runrook sync --yes before rook run --json, or rook run --test --json for a local result
Read resultsrook report <run-id> --json

Choose the profile's transport and command from the target's source or the user's invocation details; ask when unknown. See profiles. Use rook help <command> for flags and scenarios to scope a run with --only, classes, categories or tags. When an agent has more than one profile, check the active profile with rook profile or pass rook run --profile <id> to select the intended target.

Authorization and credits

Before profile add, profile fix, profile test or run, inspect the target's agent.yaml for calls[] entries with write: true. Those commands can reach the real agent. Use staging and obtain any missing authorization for its effects; Rook cannot undo them; do not rely on a per-target headless confirmation. Verify effects through read-only interfaces; inspect available read tools before concluding that an effect is unverifiable. Keep secrets as ${VAR} references through rook env set, outside profiles and transcripts.

Announce spending before explore, generate, run, profile add|fix, ask and run|report --rca. profile test invokes the target without Rook model credits. Use paid RCA only with user authorization. Track the user's budget across commands; do not assume the CLI enforces an aggregate task cap. Check its help for available limits. A null balance means unknown. Prefer scoped --allow grants; use --yes only within the authorized scope. See headless contracts for output, grants and credit accounting.

Report the evidence

Check the exit status and discarded/halted fields before claiming completion. A finished run exits 0 even when scenarios fail; ok: true can also describe a refused run. Parse JSON only when a document exists, otherwise use stderr. Read the report by this invocation's run ID, not an old default report.

Follow verdicts: show Pass, Fail and Unable to Verify separately, quote criterion evidence, identify gaps and compare prior runs only when their evidence is available. Preserve incomplete results and unknown metadata; do not invent evidence or replace Rook's verdict with your own reading of the agent reply.

References

  • CI: complete pipeline and verdict gating.
  • MCP: server discovery, approval and configuration.
  • Troubleshooting: setup failures and version-specific verification limitations.
  • Headless contracts: JSON shapes and saved-file locations.

Project evidence lives under .testmuai/rook/. Credentials and session state live under ~/.testmuai/rook/; do not commit that home directory.

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 Rook Skill AI skill do?

Use rook to test, evaluate, red-team or regression-check an AI agent the user owns, or to interpret saved Rook results. Does not apply to ordinary unit tests, browser automation or web UI checks without an AI agent under test.

Why use Rook Skill on TypingMind?

Because you install it once and use it with any model. Rook Skill 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 Rook Skill in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/LambdaTest/agent-skills/tree/main/rook-skill. 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 Rook Skill?

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 Rook Skill?

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

Is the Rook Skill AI skill free?

Yes. It is published on GitHub by LambdaTest 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.

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