feat(curation): data quality pipeline — Phases 1-3

Add comprehensive data curation system to clean up the 197K skill
dataset and show only quality browse-ready skills to users.

Phase 1 — Database exploration:
- Explore scripts (explore.ts, explore.mjs, explore.sql) for analysis
- Discovered: 69% duplicates, 77% aggregator/fork noise

Phase 2 — Data cleanup and classification:
- Schema: 6 new curation columns + 4 indexes
- curate.mjs: 8-step pipeline (classify, dedup, fork detection, etc.)
- Result: 197K → 60K unique → 16K browse-ready skills
- Bug fix: securityStatus was computed but never stored during crawl

Phase 3 — UI browse-ready filters:
- browseReadyFilter applied to 17+ query functions
- Homepage stats show accurate browse-ready counts
- Stats API filtered (previously had no WHERE clause)
- Category counts recalculated (e.g. 45K → 3.1K)
- Featured skills exclude duplicates and aggregators

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

apps/web/app/api/stats/route.ts

@@ -34,14 +34,18 @@ export async function GET(request: NextRequest) {
       });
     }
 
-    // Consolidate all skill stats into a single query for better performance
+    // Browse-ready filter: exclude duplicates and aggregators
+    const browseReady = sql`${skills.isDuplicate} = false AND (${skills.skillType} IS NULL OR ${skills.skillType} != 'aggregator')`;
+
+    // Consolidate all skill stats into a single query (browse-ready only)
     const statsResult = await db
       .select({
         totalSkills: sql<number>`count(*)::int`,
         totalDownloads: sql<number>`coalesce(sum(${skills.downloadCount}), 0)::int`,
         totalContributors: sql<number>`count(distinct ${skills.githubOwner})::int`,
       })
-      .from(skills);
+      .from(skills)
+      .where(browseReady);
 
     // Get category count in separate query (different table)
     const categoryResult = await db