/**
 * `monomind doc eval` — the Second Brain scoreboard.
 *
 * This harness is the arbiter of the retrieval work. Its job is to be HOSTILE
 * to its own result. Everything it does that could flatter the numbers is
 * either disabled or reported:
 *
 *  - Vacuous-eval assert: k must be a small fraction of the corpus. A retrieval
 *    window near corpus size makes recall 1.0 by construction. Hard failure.
 *  - Weak baselines: the same golden set is run through a seeded random picker
 *    and a plain BM25 scorer. The GAP is the signal; a high random score is the
 *    signature of a vacuous eval, and a high BM25 score means the set is too easy.
 *  - Anti-triviality: pairs whose query is near-verbatim in the target are
 *    dropped and counted, because those measure string matching.
 *  - Short-return instrumentation: a query that gets back fewer than k results
 *    cannot support an @k metric; those are counted and reported.
 *  - Network guard: the network is BLOCKED during the query phase, not assumed
 *    absent. Any attempt is recorded with its stack.
 *  - Live-doc pinning: the eval store is rebuilt from the corpus with exactly
 *    one ingest per document, so it holds no superseded versions.
 *
 * @module v1/cli/knowledge/eval/harness
 */
import { type EvalOptions, type EvalReport } from './harness-types.js';
export { renderReport } from './harness-render.js';
export * from './harness-screen.js';
export * from './harness-types.js';
export declare function runEval(opts: EvalOptions): Promise<EvalReport>;
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