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Separate evidence from marketing: analyze the claims in a product listing with your own LLM key or a local model. Hype Detector helps you think critically about online product listings. Instead of telling you what to buy, it analyzes the claims the seller makes — flagging vague marketing language, unsupported or scientific claims, and missing evidence — and explains its reasoning so you can decide for yourself. Its goal is to answer one question: how trustworthy are the claims in this listing? • Bring your own LLM — OpenAI, Anthropic, Google Gemini, or OpenRouter with your own API key, or a local Ollama server. No subscription, no middleman. • Private by design — no accounts, no analytics, no tracking, no telemetry. Your API key is stored only on your device, and your data goes directly to the provider you choose (and never leaves your device with a local Ollama model). • Balanced, evidence-oriented — it distinguishes facts from marketing, highlights missing evidence, summarizes what reviewers say (pros and cons of the product and seller), and never claims a product is "fake" — only whether evidence is present. How to use: 1. Open the Options page and enter an API key (or choose a local model). 2. Visit an Amazon product page. 3. Click the toolbar icon → Analyze this page. 4. Read the credibility breakdown in the side panel. Analysis only runs when you click Analyze — never automatically. Currently supports Amazon; more sites planned. Open source (MIT): https://github.com/tilanukwatta/hype-detector
Aug 4, 2026
rating_count is the Chrome Web Store ratings count, not a written-review count.
Media assets
Screenshots and videos on the listing.
Has promo video
Whether the listing includes at least one video.
Languages
Declared language locales.
Developer website
Listing exposes a developer website URL.
Contact email
Listing exposes a contact email.
Keyword in name
Case-insensitive substring match in the name.
Keyword in description
Case-insensitive substring match in the description.
Keyword occurrences in description
Count of case-insensitive occurrences in the description.
Category user-count percentile
Share of same-category extensions with fewer users (null if unknown).
These are transparent listing completeness / keyword signals, not a prediction of Chrome Web Store search ranking.