#!/usr/bin/env node
/**
 * `distill` — run a teacher→student GEPA distillation against a gold JSONL.
 *
 * The TEACHER is an expensive workflow whose verdicts are frozen as gold; the
 * STUDENT is a cheap single-shot analyst whose system prompt GEPA optimizes
 * toward reproducing those gold verdicts. This is the LIVE, token-spending
 * entry — invoked by hand, never in CI.
 *
 * Usage:
 *   distill \
 *     --gold   <path/to/gold.jsonl> \
 *     --baseline <path/to/baseline-prompt.txt> \
 *     --model  <cheap-student-model> \
 *     [--optimizer-model <reflection-model>] \
 *     [--generations N] [--population K] [--reps R] \
 *     [--test-every-nth 4] [--delta 0] \
 *     [--categorical f1,f2] [--array a1,a2] \
 *     [--run-dir <dir>]
 *
 * Auth: set LLM_API_KEY (+ optional LLM_BASE_URL) or TANGLE_API_KEY for the
 * Tangle router. The same creds drive the student calls AND the GEPA
 * reflection.
 *
 * Example (against the private skills-internal gold set, 53 records):
 *   TANGLE_API_KEY=$(cat /tmp/.tk) pnpm tsx src/campaign/distillation/cli.ts \
 *     --gold ~/code/skills-internal/audits/gold/skill-verdicts.gold.jsonl \
 *     --baseline ./baseline-skill-analyst.txt \
 *     --model gpt-4o-mini --optimizer-model gpt-4o \
 *     --generations 3 --population 4 \
 *     --categorical value_verdict,quality_score,generalization_rating,public_leak_risk,write_target_rating,subagent_recommended \
 *     --array top_actions
 */
export {};
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