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Know what AI really costs — real-time cost badges on AI agent tweets Every AI agent tweet is hiding a price tag. BurnRate shows it. BurnRate scans your X feed for posts about AI agents — bots, automations, custom pipelines — and injects a BR$ badge right on the tweet. Click the badge and AI reads the actual post to extract agent counts, models, activity levels, and specific services mentioned. You get a real cost breakdown, not a guess. No more hype without receipts. HOW IT WORKS BurnRate identifies AI agent mentions in your feed and adds a BR$ Assess badge. Click any badge to get an AI-powered cost assessment that includes LLM token costs by model, infrastructure detection (APIs, hosting, SMS, voice, compute), vendor ad detection — know when a post is selling something vs. showing a real setup, and a built-in calculator to adjust estimates or model your own agent costs. WHAT MAKES IT DIFFERENT Most cost estimates are generic. BurnRate actually reads the post. It found 3 agents in a Polymarket trading bot. It detected Google Maps API, Twilio SMS, and a voice calling service in a lead gen system. It flagged a managed hosting ad that looked like a user flex. Real analysis, not keyword matching. $19.99 ONE-TIME — LIFETIME ACCESS One purchase. Almost unlimited AI-powered assessments. No subscription, no recurring fees. Your license key works forever. PRIVACY FIRST All tweet scanning runs locally in your browser. The only external calls are AI analysis (via our secure proxy) and license activation. No data collection, no tracking, no analytics. Built by @DawnTepper_
Mar 13, 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.