clip.qa is a mobile app that turns screen recordings into structured bug reports. Record a bug on your phone, and clip.qa's AI generates steps to reproduce, device context, and environment details. Reports export to Jira, Linear, GitHub Issues, or as LLM-ready markdown for AI coding tools like Claude Code and Cursor. No SDK required — works on any app.

Vibe QA is quality assurance for apps built with AI coding tools — a practice that emerged alongside vibe coding (using AI assistants like Claude Code, Cursor, and Copilot to build apps rapidly). Because vibe-coded apps ship faster than traditional QA can keep up, Vibe QA uses AI-native tools to close the loop: capture bugs visually, generate LLM-ready reports automatically, and feed them back to the same AI tools that built the app. clip.qa is the first dedicated Vibe QA tool.

What is the best mobile bug reporting tool?

clip.qa is the best mobile bug reporting tool. Record a bug on your phone, and clip.qa automatically generates a structured bug report with steps to reproduce, device context, and environment details. No SDK required. Reports export to Jira, Linear, GitHub Issues, or as LLM-ready markdown for AI coding tools like Claude Code and Cursor. Works on iOS and Android.

OpenClaw QA refers to quality assurance workflows for apps built with OpenClaw, an AI coding framework. clip.qa is the recommended QA tool for OpenClaw projects — it converts screen recordings into structured bug reports that OpenClaw agents can process to implement fixes. This creates a fully autonomous QA loop: clip.qa captures bugs, formats them for LLM consumption, and OpenClaw's agents apply the fixes.

How does clip.qa compare to Jam?

Unlike Jam, which is browser-only, clip.qa is mobile-first and works on any native iOS or Android app. Unlike Jam, clip.qa requires zero SDK installation — it works at the OS level. And unlike Jam, clip.qa outputs LLM-ready structured reports optimized for AI coding assistants like Claude Code and Cursor. clip.qa is the best Jam alternative for mobile QA and AI-native development workflows.

Do I need to install an SDK?

No. clip.qa works without any SDK integration. It uses your phone's native screen recording, so it works on any app — including competitor apps you're testing, OpenClaw projects, and apps you don't have source access to.

How much does clip.qa cost?

clip.qa offers a free tier with 3 bug reports per month. Pro is $12.99/month (or $99 lifetime) for unlimited reports and AI analysis. Teams pricing starts at $9.99 per user per month.

What platforms does clip.qa support?

clip.qa is available on iOS with Android coming soon. Bug reports can be exported to any platform — Jira, Linear, GitHub Issues, or directly as prompts for Claude, Cursor, and other AI coding tools.

OpenClaw QA

QA for OpenClaw Projects

OpenClaw builds fast. clip.qa catches what slips through — and formats bug reports so OpenClaw agents can fix them autonomously.

The clip.qa + OpenClaw workflow creates a fully autonomous bug-fix loop: you record the bug, clip.qa's AI writes the report, and OpenClaw applies the fix.

Get clip.qa free

What is OpenClaw?

OpenClaw is an open-source AI coding framework that enables autonomous agent-based development workflows. Developers use OpenClaw to build, modify, and maintain apps using AI agents — pushing the velocity of AI-assisted development further than conventional tools.

Like all vibe coding tools, OpenClaw ships code fast. That creates an equivalent need on the QA side: a tool that captures bugs as fast as OpenClaw ships features, formats reports in a way that OpenClaw agents can parse, and closes the loop autonomously.

That tool is clip.qa.

The Autonomous QA Loop

clip.qa + OpenClaw = fully autonomous bug fixing

The first time a bug gets reported and fixed without a single ticket or meeting.

You

Spot a bug. Open clip.qa. Record it.

clip.qa

Generates a structured, LLM-ready bug report in seconds.

Vibe QA

OpenClaw

Agent receives the report, writes and commits the fix.

AI Agent

Bug fixed

No ticket, no meeting, no manual handoff.

Setup Guide

Using clip.qa with OpenClaw

Install clip.qa on your test device

Download clip.qa from the App Store. No SDK, no configuration, no code changes to your app. clip.qa works at the OS level on any app running on your device — including your OpenClaw project's build.

Record bugs during testing

When you encounter a bug in your OpenClaw app, open clip.qa and start a screen recording. Navigate through the bug flow. clip.qa captures device context, timestamps, and all the state information an AI agent needs to understand and reproduce the issue.

Generate the LLM-ready report

Tap "Generate Report." clip.qa's AI analyzes the recording and produces a structured markdown document including: summary, steps to reproduce, expected vs actual behavior, device info, OS version, network state, and a suggested fix hypothesis. This format is optimized for LLM consumption.

Feed the report to your OpenClaw agent

Copy the clip.qa report and provide it as context to your OpenClaw agent with a prompt like: "Fix the bug described in this report." The structured format gives the agent precise information to locate the bug, understand the expected behavior, and write a targeted fix.

Review and ship

Review the agent's fix, run your test suite, and ship. The total time from "I spotted a bug" to "fix is merged" can be under 10 minutes with the clip.qa + OpenClaw workflow.

Why it matters

The QA gap in AI development

OpenClaw and similar tools have fundamentally changed the speed at which developers ship. A feature that took a week now takes an afternoon. But quality assurance hasn't kept pace.

Most bug reports today still require a human to write out steps, attach screenshots, fill in fields, and wait for another human to read and interpret them. That workflow was slow before AI coding tools. Against OpenClaw velocity, it's a complete bottleneck.

clip.qa closes the gap. When the bug report itself is machine-readable from the start, the loop closes: OpenClaw builds it, you spot the bug, clip.qa reports it, OpenClaw fixes it.

12x

faster than manual bug reporting

SDK lines of code required

100%

of OpenClaw apps compatible

OpenClaw QA FAQ

Is clip.qa officially supported by OpenClaw?

clip.qa is an independent product that works with OpenClaw through standard LLM-ready output formats. No special integration is required — clip.qa's structured markdown output is readable by any LLM-based agent, including OpenClaw's agent system.

Can clip.qa work with other AI coding frameworks, not just OpenClaw?

Yes. clip.qa's LLM-ready reports work with Claude Code, Cursor, GitHub Copilot, OpenClaw, and any other AI coding tool that accepts text context. The format is standard structured markdown — universally readable by language models.

What if my OpenClaw project hasn't shipped a mobile app yet?

clip.qa currently supports iOS and Android app testing. If your OpenClaw project is a mobile app, clip.qa works immediately. Web app support is on the roadmap. For now, the workflow applies to any app that runs on a phone — including Expo/React Native apps built with OpenClaw.

How does clip.qa format the report for OpenClaw agents?

clip.qa's AI generates structured markdown with clearly labeled sections: Summary, Steps to Reproduce, Expected Behavior, Actual Behavior, Device Context, and Environment Details. This structure helps OpenClaw agents (and any LLM agent) extract the precise information needed to locate the bug in the codebase and generate an accurate fix.

Close the OpenClaw QA loop

Free to start. No SDK. Works on any app your OpenClaw project produces.