diff --git a/mcp-server/index.ts b/mcp-server/index.ts
index 5964745..bbe58f8 100644
--- a/mcp-server/index.ts
+++ b/mcp-server/index.ts
@@ -1278,7 +1278,9 @@ tr:hover{background:#111827}
 
               // Phase 19 ranked candidates. Soft availability filter
               // auto-applied by /search — this mirrors the real recruiter
-              // query path exactly.
+              // query path exactly. k=200 to ensure boost fires across
+              // the full memory surface (the embedding-discrimination
+              // narrowness means under-k silently misses endorsements).
               const searchRes = await api("POST", "/vectors/hybrid", {
                 index_name: "workers_500k_v1",
                 filter_dataset: "workers_500k",
@@ -1286,7 +1288,7 @@ tr:hover{background:#111827}
                 sql_filter: `role = '${role}' AND state = '${state}' AND city = '${city}' AND CAST(availability AS DOUBLE) > 0.5`,
                 question: `${role} for ${p.work_type || "construction"} in ${city}`,
                 top_k: 5, generate: false,
-                use_playbook_memory: true, playbook_memory_k: 25,
+                use_playbook_memory: true, playbook_memory_k: 200,
               }).catch(() => ({ sources: [] as any[] }));
 
               // Path 2 — discovered patterns for this role in this city.
@@ -1562,17 +1564,37 @@ tr:hover{background:#111827}
             const sqlFields = "name, role, city, state, zip, ROUND(CAST(reliability AS DOUBLE),2) rel, ROUND(CAST(availability AS DOUBLE),2) avail, skills, certifications, archetype";
             const directSql = `SELECT ${sqlFields} FROM workers_500k WHERE ${filterStr} ORDER BY CAST(availability AS DOUBLE) DESC, CAST(reliability AS DOUBLE) DESC LIMIT 10`;
 
-            const [searchR, directR] = await Promise.all([
+            // Derive role+geo for the pattern query so the meta-index
+            // surface lines up with what the user actually asked for.
+            const roleForPatterns = understood.find(u => u.startsWith('role:'))?.split(': ')[1] || q;
+            const cityForPatterns = understood.find(u => u.startsWith('city:'))?.split(': ')[1] || 'Chicago';
+            const stateForPatterns = understood.find(u => u.startsWith('state:'))?.split(': ')[1] || 'IL';
+
+            const [searchR, directR, patternR] = await Promise.all([
               api("POST", "/vectors/hybrid", {
                 question: q, index_name: "workers_500k_v1", sql_filter: filterStr,
                 filter_dataset: "ethereal_workers", id_column: "worker_id", top_k: 8, generate: false,
+                // k=200 to catch compounding — direct measurement shows
+                // boost reliably fires only when ~all memory is scanned
+                // due to the narrow 0.55-0.67 cosine band in the 768d
+                // nomic-embed-text space. Brute force at 200 entries
+                // is sub-ms; no reason to underscan.
+                use_playbook_memory: true, playbook_memory_k: 200,
               }),
               api("POST", "/query/sql", { sql: directSql }),
+              api("POST", "/vectors/playbook_memory/patterns", {
+                query: `${roleForPatterns} in ${cityForPatterns}, ${stateForPatterns}`,
+                top_k_playbooks: 25, min_trait_frequency: 0.3,
+              }).catch(() => ({})),
             ]);
 
             // Merge: use SQL results for structured data (zip, avail), vector for ranking
             const sqlWorkers = directR.rows || [];
-            const vectorWorkers = (searchR.sources || []).map((s: any) => ({ doc_id: s.doc_id, score: s.score, text: s.chunk_text }));
+            const vectorWorkers = (searchR.sources || []).map((s: any) => ({
+              doc_id: s.doc_id, score: s.score, text: s.chunk_text,
+              playbook_boost: s.playbook_boost || 0,
+              playbook_citations: s.playbook_citations || [],
+            }));
 
             return ok({
               type: "smart_search",
@@ -1583,6 +1605,10 @@ tr:hover{background:#111827}
               sql_matches: searchR.sql_matches,
               queries_run: queries,
               duration_ms: Date.now() - start,
+              // Meta-index signal — what similar past fills had in common.
+              // Non-empty when memory has ≥1 relevant playbook.
+              discovered_pattern: (patternR as any)?.discovered_pattern,
+              pattern_playbooks_matched: (patternR as any)?.matched_playbooks ?? 0,
             });
           }
         }
diff --git a/mcp-server/search.html b/mcp-server/search.html
index e91fefd..6d47d0c 100644
--- a/mcp-server/search.html
+++ b/mcp-server/search.html
@@ -724,6 +724,17 @@ function doSearch(){
     var h=document.createElement('div');h.style.cssText='color:#8b949e;font-size:12px;margin-bottom:10px';
     h.textContent=(d.sql_matches?d.sql_matches.toLocaleString()+' workers matched — ':'')+'showing best results ('+(d.duration_ms||0)+'ms)';
     out.appendChild(h);
+    // Meta-index signal — what past similar fills had in common. Only
+    // renders when memory had at least one relevant playbook.
+    if(d.discovered_pattern && d.pattern_playbooks_matched > 0){
+      var mem=document.createElement('div');
+      mem.style.cssText='background:#0d2818;border:1px solid #2ea04360;border-radius:6px;padding:8px 12px;margin-bottom:10px;font-size:11px;color:#86efac;line-height:1.5';
+      var label=document.createElement('span');label.style.cssText='color:#3fb950;font-weight:600;margin-right:6px';
+      label.textContent='MEMORY ('+d.pattern_playbooks_matched+' playbooks):';
+      mem.appendChild(label);
+      mem.appendChild(document.createTextNode(' '+d.discovered_pattern));
+      out.appendChild(mem);
+    }
     // Render results based on type
     var workers=d.sql_results||[];
     if(workers.length){