How it works: every fact is pinned with a sha256 hash and timestamp, and the report cites pins, not pages. The ship gate has no model inside: it re-fetches and re-hashes each cited fact. A refusal writes a receipt (what moved, old and new hash, why). The agent then finds which conclusions broke, re-fetches only the drifted pages, recomputes, discloses the old values, and re-gates.
Nimble: our agent calls Nimble's MCP server directly, with nimble_extract on five live Amazon pages in parallel and nimble_search to replace a lost page.
Liquid AI (on-device): LFM2-1.2B-Extract must agree with our parser before a fact is pinned; LFM2.5-1.2B-Instruct writes the analysis as cite-checked claims.
Tinybird: every pin, refusal and run streams live; pipes serve the evidence counts, gate p95 and which facts move most.
Result: 0 shipped contradictions. An injected 15% price drop is caught every run, real Amazon drift is caught with nothing injected, and 30 adversarial red proofs pass. We count false refusals too: refusing everything would also ship zero contradictions.
