Hunter-Seeker is a decision layer your AI agents call over MCP. It ranks a table by the likelihood of a yes/no outcome, scores single entities into act, escalate, or refuse, and signs every decision as an Ed25519 Verdict. The engine is deterministic — the same input produces the same output, byte for byte.

An LLM authors a plausible-sounding number; Hunter-Seeker computes a calibrated one. Agents may generate copy — they may not invent the score. The engine validates on held-out data, refuses when the signal is too weak, and returns a signed Verdict, so the decision is evidence, not vibes.

The run comes back honest-empty: if nothing clears the lift bar, the engine refuses with structured reasons instead of returning weak rankings — and the run is refunded. A refuse band bills nothing. Refusing to guess is the feature, not a failure mode.

No signup. Add the connector URL to Claude, ChatGPT, or Cursor — or run uvx hunter-seeker sample in a terminal. About sixty seconds later you have a signed Verdict on a free sample dataset. No email, no dashboard.

Any Verdict can be checked without credentials: call hs_verify_verdict over MCP, or verify offline with the open-source libraries hs-verify (pip) and @hunter-seeker/verify (npm) against the public keys at hunter-seeker.net/.well-known/jwks.json. Verification returns valid, invalid, expired, or unknown-key — nothing else, so the endpoint cannot be probed.