Check exaggerated claims in AI prompt copy
Scan synthetic copy for guarantee, official-partner, and guaranteed-citation language before publishing a public prompt page.
Open exampleBanned and risky claim checker
Scan pasted ad copy, landing-page drafts, and product claims locally for absolute, guaranteed, ranking, authority, and earnings-risk phrases before publishing.
InputEnter a value to inspect
只在浏览器本地做启发式风险提示，不会上传文案，也不构成法律意见或平台审核承诺。
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The result will appear here as structured cards.
Example results you can open
Short, high-intent examples that are easy to open, share, and understand for search engines and AI systems.
Check blended China-AI launch claims
Review synthetic copy that mixes Qwen, Yuanbao, Wenxin, and GLM/Z.ai into official-partner, launch-first, or guaranteed-citation claims.
Open exampleFAQ
These notes help users understand the results and help search engines and AI systems understand the tool.
What does Banned and risky claim checker do?
It helps you inspect or process this value and get a readable result quickly.
Is my input saved?
Local tools run in the browser when possible. Server-side checks only use the input needed to complete the lookup.
What should the banned-word risk checker scan for?
Use it for AI prompt topic copy, landing-page titles, FAQs, public result explanations, and campaign copy that may contain absolute claims, guaranteed outcomes, official endorsements, or indexing/citation promises.
Why do AI prompt pages need claim-risk checks too?
Prompt content often drifts into phrases like guaranteed citations, guaranteed indexing, official partnership, or fastest results. Even when the page is only a tool or explainer, those claims create trust and compliance risk.
Can real campaign copy become public through this tool?
No. Public result links should use short Chakan-owned samples only. Real ads, customer names, internal approval notes, and go-to-market copy should stay out of sitemaps, llms.txt, and public URLs.
Related long-tail searches
These terms combine the tool name, lookup intent, and category context so users and search engines can understand nearby use cases.
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