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 drafts a report with steps to reproduce and device context for you to review. Reports export as markdown for AI coding tools like Claude Code and Cursor, or to paste into any tracker. Jira, Linear, Slack, GitHub Issues and Notion integrations are coming soon. No SDK required in the app you test.

What is Vibe QA — and why does it matter?

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 built for Vibe QA.

Does clip.qa work with OpenClaw projects?

Yes. clip.qa produces a structured report your agent, including OpenClaw, can read through MCP or a pasted prompt.

How is clip.qa different from Jam?

Jam has a Chrome extension, a Mac app and an iOS app, plus AI summaries and an MCP server. No Android app is documented. clip.qa records on iOS, Android and in Chrome (beta, request access), with no SDK in the app you test. clip.qa's MCP also records each fix attempt (pending, succeeded, failed) with its commit or PR, and can diff reports.

Do I need to install an SDK or add code to my app?

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 (subject to OS limits such as FLAG_SECURE).

How much does clip.qa cost?

Free: 30 bug reports and 30 AI-assisted reports a month. Team ($12.99/mo or $129/yr, billed per creator seat, viewers free): unlimited bug reports, 200 AI-assisted reports and 50 share links a month. Enterprise pricing is custom; confirm current quotas and features with sales. Audit logs and priority support are listed; SAML/SSO is coming soon.

What platforms does clip.qa support?

The clip.qa web dashboard is available now; the iOS app, Android app and Chrome extension are in beta (request access at hello@clip.qa). Bug reports can be copied as markdown into any tracker (Jira, Linear, GitHub Issues; native integrations coming soon) or used directly as prompts for Claude, Cursor, and other AI coding tools.

clip.qa / Use cases / AI Code QA

AI ships code fast. QA has to keep up.

One vendor study found AI co-authored PRs had about 1.7x more issues per PR. clip.qa is the QA layer for apps built with Claude Code, Cursor and other AI coding tools.

Record bugs on your phone. Review the AI draft. Send it to your coding agent.

Request beta access

The problem

AI code ships fast. Bugs ship faster.

One vendor study is worth knowing about.

1.7x

more issues per PR in AI co-authored PRs (10.83 vs 6.45; 470 open-source PRs)

CodeRabbit analysis, December 2025 (vendor study, authorship inferred)

The mismatch

Why traditional QA fails for AI code

AI ships in hours. Traditional QA takes days. The gap keeps widening.

Traditional QA

Vibe QA (clip.qa)

Feature ship speed

Days to weeks

Hours (AI-coded)

Bug report creation

Manual writing

AI draft, then your review

Report format

Human-readable only

LLM-ready markdown

Fix implementation

Human reads report, writes code

Your agent reads the report; you review the fix

Full loop time

Ticket, triage, sprint

Record, review the AI draft, send it to your agent

The Solution

The Vibe QA loop for AI code

Four steps from bug found to bug fixed.

1. Record the bug

Open clip.qa on your phone. Screen-record the bug in your AI-built app. clip.qa captures device context automatically.

2. AI writes the report

clip.qa's AI drafts a structured, LLM-ready bug report with steps to reproduce, expected vs actual when the recording shows a defect, and device context.

3. Paste into your AI tool

Review the draft. Paste it into Claude Code, Cursor or another AI coding tool, or let the agent read it over MCP.

4. Bug fixed

The agent reads the report and proposes a fix; you review and ship.

Learn more about Vibe QA

AI Tool Integrations

Built for your AI workflow

clip.qa's LLM-ready output is formatted for the exact tools you're already using to build.

Claude Code

Paste the clip.qa report as context. Claude Code reads the structured steps, device info, and expected behavior to write a targeted fix.

Cursor

Drop the bug report into Cursor's chat. The structured markdown gives Cursor all the context it needs to locate and fix the issue.

OpenClaw

Your OpenClaw agent can read the report through MCP or a pasted prompt.

Coming soon

Other MCP clients

Any MCP client can connect to https://mcp.clip.qa/mcp, or paste the markdown report.

Coming Soon

The Autonomous QA Loop

MCP integration will let clip.qa send bug reports directly to your AI coding agent. No copy-paste. No human in the loop. Record a bug and the AI fixes it automatically.

You record bug

clip.qa's AI generates report

MCP sends to agent

Agent commits fix

Learn about the agent loop

AI code QA FAQ

What types of bugs does AI-generated code produce?

AI-generated code tends to produce subtle logic errors, edge-case failures, and security vulnerabilities that pass basic tests but fail in real-world usage. Common issues include incorrect state management, missing error handling, race conditions, and UI bugs that only appear on specific devices or orientations. These are exactly the kinds of bugs that visual QA catches and automated tests miss.

Does clip.qa work with any AI coding tool?

Yes. clip.qa's AI generates structured LLM-ready markdown that any AI coding tool can consume. Setup guides exist for Claude Code, Cursor and Windsurf, and any other tool that accepts text context can use the markdown. The report format is standard structured markdown — universally readable by language models.

Is this different from automated testing?

Yes. Automated testing (unit tests, E2E tests) validates known, expected behavior. clip.qa and Vibe QA handle the unknown — visual bugs, UX regressions, and edge cases that no one wrote an assertion for. AI-generated code is especially prone to these "unknown unknown" bugs because the developer didn't write the code manually and may not anticipate all its failure modes. clip.qa complements automated testing; it doesn't replace it.

What is "vibe coding" and why does it need special QA?

Vibe coding is building apps by describing what you want to an AI assistant and letting it write the code. It dramatically accelerates development but creates a QA gap: the developer may not fully understand every line of generated code, making it harder to predict where bugs will appear. Vibe QA is the practice of using AI-native tools to close that gap — catching bugs visually and generating reports that AI tools can act on.

AI builds it. clip.qa catches what slips through.

Free to start. No SDK. Works with every AI coding tool.

Get clip.qa free clip.qa for vibe coders