Sprint1: pure-rule bucket classifier + scorer (taste before intelligence)

- athena/scoring.py: deterministic bucket taxonomy (SHIPPING, LOCAL AI,
  PROBLEM SOLVED, MODEL RELEASE, RESEARCH, BUSINESS, INFRASTRUCTURE,
  CULTURE, UNCATEGORIZED) + component scores (shipping/utility/
  replication/enthusiast/novelty) with hype_penalty. No embeddings/LLM.
- Idempotent schema migration: 12 new columns incl actionability_score (reserved).
- attach_scoring() wired into pipeline.py AFTER store_entries, BEFORE render.
- Backfilled all existing rows; verified at box: null->scored via live run.
- Review report exposes every fired rule (editorial proof, not accuracy metric).
- Human-review tally (Published/Rejected/Borderline) is manual only.

Decision: founder directive 2026-07-15 — discover taxonomy before adding
intelligence. Sprint 2 (Lens) blocked until manual review completes.

pipeline.py

@@ -27,6 +27,10 @@ sys.path.insert(0, os.path.dirname(__file__))
 from adapters import SourceAdapter
 from adapters._store import upsert_entries
 
+# Sprint 1 (2026-07-15): pure-rule bucket classifier + scorer.
+# Attaches immediately after ingest/dedup and before any rendering step.
+from athena import scoring as _scoring
+
 # Adapter registry — add new adapters here (one line each)
 ADAPTERS = {
     "github": lambda: __import__("adapters.github", fromlist=["GitHubAdapter"]).GitHubAdapter(),
@@ -273,6 +277,12 @@ def run_pipeline(sources: list[str] | None = None, limit: int = 20, dry_run: boo
             if src in source_stats:
                 source_stats[src]["stored"] += 1
 
+        # --- Sprint 1 attach point: score after ingest/dedup, before render ---
+        try:
+            _scoring.attach_scoring(db_path)
+        except Exception as e:
+            print(f"  ⚠ scoring attach failed: {e}")
+
         # Verification
         if verify:
             print(f"\n  [Verification]")