Testdriver:Agent

Organization

testdriverai

testdriver:agent

How the TestDriver agent behaves on GitHub issues, pull requests, and @mentions

Overview

Publisher	testdriverai
Repository	`testdriverai`
Skill name	`testdriver:agent`
Stars	465
Forks	39
Bundled files	Instructions only
Links	Skill source Repository Homepage

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.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by testdriverai on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/testdriverai/testdriverai/tree/main/ai/skills/testdriver-agent
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.

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/testdriverai/testdriverai.git /tmp/testdriverai
mkdir -p .claude/skills
cp -r /tmp/testdriverai/ai/skills/testdriver-agent .claude/skills/testdriverai-testdriver-agent

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Testdriver:Agent 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 Testdriver:Agent 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 Testdriver:Agent 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.

The TestDriver agent is an AI teammate in your GitHub repository. It is code review that runs your app. It does not only read a diff and guess what can break. It starts a real sandbox, controls the real app, and reports what really happens.

Scope: it only builds and maintains tests

The agent has one purpose. It does one thing: it writes, debugs, fixes, and keeps automated tests with TestDriver. It reviews pull requests. It writes and runs a test against the change. It does not do work that is not in scope. It does not edit your application code, fix product bugs, answer other programming questions, or act as a general coding assistant.

How it behaves depends on the surface

The agent reacts to three different GitHub surfaces. Its behavior is different on each one.

Surface	Trigger	What it does
Pull request opened	Automatic (no mention)	Silent, evidence-based code review
Issue opened	Automatic (no mention)	Onboarding / test-building
@mention (issue or PR)	You mention the bot	Interactive, chatty conversation

Pull requests — automatic code review

When a pull request is opened, the agent reviews it automatically. Nobody has to ask.

The review is the deliverable, not chatter. No person asks for an automatic review. Thus the agent stays quiet while it works. It posts a single review comment at the end. It does not put many inline threads across the diff. It does not tell each step.
It runs the change when it can. Its default first move is to start a session, work out what the PR changes from a user's point of view, and write and run a TestDriver test that exercises exactly that. A bug it watched happen is far more valuable than one it inferred.
Findings are labeled by how they were found. Each finding is marked observed (proven by actually running the change) or suspected (reasoned out from reading the diff). If the installation isn't signed in to TestDriver, the agent can't run anything, so it reviews by reading and marks every finding suspected.
It focuses on real bugs. Logic errors, regressions, broken edge cases, mishandled errors — not style, naming, or "consider extracting this."
Zero findings is a good review. If the change looks correct, it says so in a sentence. If there's nothing worth reviewing (only lockfiles, generated files, or formatting), it posts nothing at all.
It comments, it never blocks. The review is always a COMMENT — it never approves and never requests changes, so it can't gate a merge.

It also fires a native GitHub Check Run for the PR's TestDriver suite, and re-runs that check on every push (not a full re-review — push more commits and @mention the agent if you want it to review again).

Issues — onboarding and test building

When an issue is opened, the agent treats it as a cue to help you build a test.

If the issue describes a task, it acts on the request — writing or debugging the test you asked for.
If the issue is empty, it introduces itself, explains that it writes and debugs computer-use tests, and walks you through signing in to TestDriver and creating your first test.
It finishes by opening a pull request with the test it wrote.

@mentions — interactive conversation

Mentioning the bot (on either an issue or a PR) starts a solicited, interactive turn. Because you asked directly, the agent is chatty: it posts progress updates, shows you screenshots of what's happening in the sandbox, and answers follow-ups in the thread.

On a PR, an @mention overrides the silent auto-review behavior — you'll see the full play-by-play instead of just the final review comment.

You can also manage the agent from a comment:

@bot logout (or "sign out") revokes the installation's shared TestDriver sign-in and tears down the live sandbox, so the next mention will prompt whoever responds to sign in again.

Signing in

Reading a diff needs nothing, but running the app needs a TestDriver session, which requires the installation to be signed in. Sign-in state doesn't decide whether the agent reviews — it decides how good the review gets. A signed-out install still gets its bugs caught from reading the code; signing in upgrades findings from suspected to observed.

Frequently asked questions

What does the Testdriver:Agent AI skill do?

How the TestDriver agent behaves on GitHub issues, pull requests, and @mentions

Why use Testdriver:Agent on TypingMind?

Because you install it once and use it with any model. Testdriver:Agent 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 Testdriver:Agent in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/testdriverai/testdriverai/tree/main/ai/skills/testdriver-agent. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Testdriver:Agent?

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 Testdriver:Agent?

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

Is the Testdriver:Agent AI skill free?

It is published on GitHub by testdriverai. Check the repository for licensing terms. 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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Deslop

openclaw

OrganizationPopular

Diff-scoped AI-slop cleanup pass: strip comment slop, defensive-check slop, type-laundering, and style drift from the current branch diff before autoreview.

Discord Clawd

Use to talk to the Discord-backed OpenClaw agent/session; not for archive search.

Discrawl

Discord archive: search, sync freshness, DMs, summaries, TUI, repo/release work.

Gitcrawl

GitHub archive: issue/PR search, sync freshness, duplicate clusters, current GitHub handoff, and Gitcrawl repo work.

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Scope: it only builds and maintains tests

How it behaves depends on the surface

Pull requests — automatic code review

Issues — onboarding and test building

@mentions — interactive conversation

Signing in

Frequently asked questions

Related AI Skills

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