Phase B1: multi-tag groupings model (backend)

Three-layer organization: primary topic (one per article, for ranking and
brief balance) + grouping tags (1-4 per article from a controlled vocabulary,
the organic "wandering" axis) + tonal flavor.

- taxonomy: add technology + learning topics; 4 calm tag families
  (Discovery & Wonder, People & Kindness, Solutions & Progress, Mind & Craft)
  defined in code, not the DB; ALLOWED_TAGS union + coerce_tags validation.
- db: article_tags(article_id, tag) join table + tag index.
- llm: tags added to the classifier json_schema (enum-constrained, maxItems 4)
  and system prompt; normalize_scores coerces tags; upsert_article_score
  replaces a row's tags atomically on every (re)classification.
- queries: feed gains a tag filter and exposes tags via group_concat; tag_counts.
- api: Article.tags, feed tag param, and /api/families with per-tag counts.
- tests: coerce/normalize/upsert/tag-filter/reclassify-replace/tag_counts +
  /api/families. 99 passing.

Corpus reclassify (re-tag + new primary topics) runs separately against the
local LLM. Frontend (B2) pairs with this; the live site is unchanged until then.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

goodnews/queries.py

@@ -36,6 +36,7 @@ _ARTICLE_COLUMNS = f"""
     s.reason_code,
     s.reason_text,
     s.model_name,
+    (SELECT group_concat(t.tag) FROM article_tags t WHERE t.article_id = a.id) AS tags,
     {RANK_SCORE_SQL} AS rank_score
 """
 
@@ -53,6 +54,7 @@ def feed(
     mute_flavors: list[str] | None = None,
     max_cortisol: int | None = None,
     max_ragebait: int | None = None,
+    tag: str | None = None,
 ) -> list[dict]:
     """Return ranked articles with categorical filters applied in SQL.
 
@@ -94,6 +96,9 @@ def feed(
     if max_ragebait is not None:
         clauses.append("COALESCE(s.ragebait_score, 0) <= ?")
         params.append(max_ragebait)
+    if tag:
+        clauses.append("EXISTS (SELECT 1 FROM article_tags at WHERE at.article_id = a.id AND at.tag = ?)")
+        params.append(tag.lower())
 
     where = "WHERE " + " AND ".join(clauses)
     params.extend([limit, offset])
@@ -148,6 +153,22 @@ def brief(conn: sqlite3.Connection, brief_date: str | None = None, limit: int =
     }
 
 
+def tag_counts(conn: sqlite3.Connection, accepted_only: bool = True) -> dict:
+    """How many shown (accepted, non-duplicate) articles carry each grouping tag."""
+    where = "WHERE a.duplicate_of IS NULL" + (" AND s.accepted = 1" if accepted_only else "")
+    rows = conn.execute(
+        f"""
+        SELECT t.tag, COUNT(*) AS count
+        FROM article_tags t
+        JOIN articles a ON a.id = t.article_id
+        JOIN article_scores s ON s.article_id = a.id
+        {where}
+        GROUP BY t.tag
+        """
+    ).fetchall()
+    return {r["tag"]: r["count"] for r in rows}
+
+
 def category_counts(conn: sqlite3.Connection, accepted_only: bool = True) -> list[dict]:
     """Return per topic/flavor article counts for building browse UIs.