How to test a no-code or AI-website-builder chatbot for policy, privacy, and safety failures without writing code or setting up an eval stack.
Last updated 2026-06-20. For the full evidence standard, read the testing methodology.
Use it to move from vague chatbot review to evidence-backed launch testing: customer pressure, expected safer behavior, transcript proof, severity, fixes, and a retest path.
Building a bot without code is fast, but the failures are the same: invented refunds, wrong policy, leaked details, unsafe advice, and dead-end conversations. Speed of building does not reduce customer risk.
Developer eval frameworks expect code, SDKs, and a CI pipeline. If you built with no-code, that is the wrong tool. Pointing a tester at the live bot and reading a plain-English report fits how you actually work.
Test the same risk families as any customer-facing bot: policy pressure, privacy, unsafe claims, prompt injection, escalation, and conversion. No-code platforms can also inherit prompt-injection and content risks from third-party widgets.
Setup: A no-code site embeds a third-party chat widget that was never tested against adversarial customer input.
Expected evidence: The report should show whether the widget leaks instructions, ignores policy, or mishandles private data.
Setup: A customer asks about a policy the no-code builder never added to the bot's knowledge base.
Expected evidence: The finding should show whether the bot admitted the gap and escalated, or invented an answer.
Yes. You point the tester at the live website widget or a public API endpoint and read a report. There is no framework, SDK, or pipeline to set up.
Yes. No-code and AI-website-builder bots can inherit prompt-injection and content-integrity risks from the underlying model and any third-party widget, even when no custom code was written.
Any bot reachable as a public website widget or API endpoint can be tested. Login-protected, WhatsApp, Instagram, and voice bots are not supported by the website runner today.
This resource is for no-code builders, AI-website-builder users, and small teams shipping chatbots without engineers.
Run the live crash test and get a transcript-backed report preview.
See the free preview, one-time report unlock, and account credit model.
Use Bot Roast reports for client QA, handoff, and fix conversations.
Inspect the report format: evidence, severity, fixes, and retest guidance.
Use the launch checklist for policy, privacy, escalation, and prompt pressure.
Map chatbot QA to real customer pressure, transcript evidence, and fixes.
Compare model-level evals with customer-facing launch-readiness testing.
See how prompt-injection risk is tested without publishing exploit recipes.
Decide if a bot — even one someone else built for you — is safe to put in front of customers.
What an AI chatbot audit covers and the transcript-backed report you should get from one.
