Model Truth Desk Agent Tracks AI Model Specs with Dated, Source-Cited Evidence

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Developer Abhinav Tiwari has built Model Truth Desk, an AI evidence agent submitted to the Sanity Challenge that stores structured, primary-source claims about AI model specifications and pricing. Each claim is tagged with a provider, subject, normalized value, effective date range, source URL, and confidence level, rather than being stored as undated text snippets. The agent converts user queries into structured evidence plans, grouping claims by model and filtering by active date intervals to distinguish current facts from expired ones. For example, it correctly separates Claude Sonnet 4.5's former 1-million-token beta context window from its current 200K limit, preserving the expired claim as history without treating it as a live contradiction. The live application and public repository are available online, with the agent connecting server-side to a Sanity-hosted knowledge base so that read tokens are never exposed to the browser.

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