fsq-agent 0.2.1

Describe what to test. Let AI help to test the user flow.

Describe the goal and let AI operate the real app. FSQ records evidence and turns the exploration into a test you can review and replay.

An open-source project from FSQ Lab.

Quick start · 中文 · Guide · Contribute

See FSQ in action

https://github.com/user-attachments/assets/aa9d0a12-2f93-4894-8349-52a013424939

Watch the full demo on YouTube.

How it works

1. Describe: You define the platform and target, goal, success criteria, and allowed and forbidden actions.
2. Observe as AI tests the real UI flow and FSQ captures screenshots, interface state, events, and may produce a reviewable test.
3. Control what happens next: inspect the evidence and, if FSQ returns a test, inspect it unchanged before separately requesting any deterministic replay.

You get an evidence-backed result and, when FSQ returns one, a portable, reusable test you can review, keep, and replay without surrendering control.

Quick start

Start with the real outcome you want to test. You need Python 3.11+ and the prerequisites for your platform and target. Choose one of the two paths below. Enter Provider credentials only in the FSQ UI—not in Coding Agent chat. Review the result first and, if FSQ returns a Case, review it unchanged before separately requesting any replay.

1. Coding Agent

Initial setup. Open your project in a Coding Agent and paste:

The official FSQ project is https://github.com/FSQ-lab/FSQ. Establish the exact opened project root. Batch the read-only Python, fsq, and Skill-presence checks with their exact working directories, commands, purpose, and effects. Then request one approval for the listed changes, covering only installation or upgrade of fsq-agent and one fsq init --agent skill in this project; disclose the exact commands and Python-environment and project-file effects before asking. Perform only the approved operations, verify fsq, and report the exact installed Skill path. This one-time setup does not initialize a Workspace, configure a Provider, or run a test. Tell me to reload or start a new Coding Agent session, then stop.

Complete that reload before continuing.

First test. Copy this prompt into your Coding Agent:

Use FSQ to test this user goal: launch Microsoft Edge Stable, use Bing to search for FSQ GitHub, then inspect the organic search results and report the current position/ranking of the FSQ GitHub repository. Select the Web platform and Microsoft Edge Stable. Follow the installed FSQ Skill and ask only for decisions it cannot establish.

Treat the platform and exact target as facts or user-owned decisions: provide them when asked rather than letting the agent guess a target ID or path, and do not substitute a different Edge channel.

Review the result first. If FSQ returns a Case, review it unchanged before deciding whether to request replay separately.

2. FSQ UI

Initial setup.

python -m pip install --upgrade fsq-agent
fsq ui

In Settings, configure the FSQ LLM Provider and explicitly select a model.

First test.

1. Create or select a Workspace, and configure its platform and target as needed.
2. In Test Runner, select the exact target.
3. Describe a verifiable result, review the test setup, and start the test. Review the result first and, if FSQ returns a Case, review it unchanged before separately requesting any replay.

Detailed first-test guide

Platforms

FSQ supports Web, Android, Windows, and macOS targets; see platform prerequisites, and help broaden support through contributions.

Documentation

• Getting started
• 中文快速开始
• CLI reference
• FSQ Case format
• Advanced Codex compatibility
• Platform prerequisites
• Support and stability

Built by FSQ Lab and the community

Built by FSQ Lab with thanks to all contributors. Want to help? Read CONTRIBUTING.md and join us.

License

MIT — Copyright (c) Microsoft Corporation.