Evals
MCP golden set
services/harbor/eval/golden.jsonl holds 30 cases (G01–G30) run against a deployed MCP endpoint by eval/run.mjs.
| Category | Cases |
|---|---|
| Reads | 17 |
| Builds | 4 |
| Quotes | 3 |
| Executions | 3 |
| Approvals | 2 |
| Revoke | 1 |
- 15
searchcases check the returned operation names; 15executecases check the envelope (ok, keys, or an expected error such as the unlinked-account revoke guard). - 13 cases are required: live ledger reads, order-book depth, a simulated build,
tx.executeproducing a real pending owner approval, transaction status and the revoke guard. - The run fails below 27/30 or if any required case fails.
- It writes build and approval rows but never signs or submits. An optional
--livemode performs one delegated TestnetOfferCreatebehind several environment guards.
Example cases:
{"tool":"search","arguments":{"query":"ledger.fee"}}const result = await harbor.venues.list({});
if (!result.ok) return result;
return { ...result, data: result.data.map((venue) => venue.id) };Offline improvement eval
eval/offline-improvement/ compares a baseline and a candidate agent behavior on fixtures (pilot.offline-evaluation-fixture.v1): quality, evidence coverage, latency, and policy, scope or side-effect violations, plus output-hash determinism.
The evaluator rejects any regression in quality or coverage, or more than 1,000 ms of extra latency. It produces a review report, a promotion manifest left as pending_human_review and a rollback manifest left as prepared_not_applied. It has no write path: a human promotes changes.