fix: align 4 more intelligence routes to ethereal_workers_v1
Same index↔dataset misalignment swept across the intelligence handler — four more /vectors/hybrid calls that paired workers_500k_v1 with filter_dataset ethereal_workers: - similar-workers route (~2418) - semantic role-discovery route (~2459) - smart_search route (~2869) - scenario worker-find (~3531) Verified: no workers_500k_v1 index remains paired with the ethereal_workers dataset; the 9 remaining refs are correctly aligned (workers_500k dataset) or pure RAG. Server boots clean. Takes effect on next mcp-server restart. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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@ -2415,7 +2415,7 @@ async function main() {
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queries.push(`Vector: Semantic similarity on ${worker.name}'s full profile → ${stateFilter}`);
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queries.push(`Vector: Semantic similarity on ${worker.name}'s full profile → ${stateFilter}`);
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const searchR = await api("POST", "/vectors/hybrid", {
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const searchR = await api("POST", "/vectors/hybrid", {
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question: worker.resume_text || `${worker.role} in ${worker.city} with skills ${worker.skills}`,
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question: worker.resume_text || `${worker.role} in ${worker.city} with skills ${worker.skills}`,
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index_name: "workers_500k_v1",
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index_name: "ethereal_workers_v1", // align with ethereal_workers dataset
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sql_filter: stateFilter + ` AND CAST(reliability AS DOUBLE) >= 0.7`,
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sql_filter: stateFilter + ` AND CAST(reliability AS DOUBLE) >= 0.7`,
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filter_dataset: "ethereal_workers", id_column: "worker_id", top_k: 5, generate: false,
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filter_dataset: "ethereal_workers", id_column: "worker_id", top_k: 5, generate: false,
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});
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});
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@ -2456,7 +2456,7 @@ async function main() {
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queries.push(`Vector: Semantic search for "${roleDesc}" — no exact role match needed`);
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queries.push(`Vector: Semantic search for "${roleDesc}" — no exact role match needed`);
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const searchR = await api("POST", "/vectors/hybrid", {
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const searchR = await api("POST", "/vectors/hybrid", {
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question: `Worker experienced in ${roleDesc}, relevant skills and certifications`,
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question: `Worker experienced in ${roleDesc}, relevant skills and certifications`,
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index_name: "workers_500k_v1", sql_filter: "CAST(reliability AS DOUBLE) >= 0.75",
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index_name: "ethereal_workers_v1", sql_filter: "CAST(reliability AS DOUBLE) >= 0.75", // align w/ dataset
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filter_dataset: "ethereal_workers", id_column: "worker_id", top_k: 8, generate: false,
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filter_dataset: "ethereal_workers", id_column: "worker_id", top_k: 8, generate: false,
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});
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});
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return ok({ type: "discovery", summary: `${(searchR.sources||[]).length} workers found through semantic skill matching for: "${roleDesc}"`,
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return ok({ type: "discovery", summary: `${(searchR.sources||[]).length} workers found through semantic skill matching for: "${roleDesc}"`,
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@ -2866,7 +2866,7 @@ async function main() {
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const [searchR, directR, patternR] = await Promise.all([
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const [searchR, directR, patternR] = await Promise.all([
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api("POST", "/vectors/hybrid", {
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api("POST", "/vectors/hybrid", {
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question: q, index_name: "workers_500k_v1", sql_filter: filterStr,
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question: q, index_name: "ethereal_workers_v1", sql_filter: filterStr, // align w/ dataset
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filter_dataset: "ethereal_workers", id_column: "worker_id",
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filter_dataset: "ethereal_workers", id_column: "worker_id",
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// Honor the parsed headcount (capped at 25 to keep the
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// Honor the parsed headcount (capped at 25 to keep the
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// vector rerank from re-scoring more rows than render).
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// vector rerank from re-scoring more rows than render).
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@ -3528,7 +3528,7 @@ async function runWeekSimulation() {
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const filt = `role = '${role}' AND state = '${state}' AND reliability >= ${minRel}`;
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const filt = `role = '${role}' AND state = '${state}' AND reliability >= ${minRel}`;
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const r = await api("POST", "/vectors/hybrid", {
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const r = await api("POST", "/vectors/hybrid", {
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question: `Find ${role} workers in ${city}, ${state} for ${scenario.situation}`,
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question: `Find ${role} workers in ${city}, ${state} for ${scenario.situation}`,
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index_name: "workers_500k_v1",
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index_name: "ethereal_workers_v1", // align with ethereal_workers dataset
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sql_filter: filt,
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sql_filter: filt,
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filter_dataset: "ethereal_workers",
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filter_dataset: "ethereal_workers",
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id_column: "worker_id",
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id_column: "worker_id",
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