feat(heads): auto-apply observability + on by default (#114 auto-apply B)

Auto-apply is now ON by default (operator-asked: opt-OUT, not opt-in) — migration
0059 + model default flipped. The support (>=30) + measured-precision gates keep
it safe and every auto-tag is reversible.

Observability so the operator can tune from real data:
- MISFIRE = an auto-applied (source='head_auto') tag the operator later removes.
  UNDER-FIRE = a tag with a head the operator adds by hand (the head missed it).
  Both captured at correction time in TagService.add_to_image/remove_from_image
  (source is lost on delete) into durable per-tag counters (head_metric), keyed
  by tag so they survive head retrain/prune.
- Daily snapshot_head_metrics writes a per-concept time-series point
  (head_metrics_snapshot): auto-applied volume + cumulative misfires/under-fires
  + head quality; 180-day retention; daily beat.
- GET /api/heads/metrics: per-concept current counts + realized misfire rate +
  head quality, plus the snapshot time-series — the report to tune the precision
  target + support floor.

Migration 0060. Tests: misfire/under-fire counting (and the negatives — manual
removal isn't a misfire, headless manual add isn't an under-fire), snapshot
time-series, metrics API.

What's the autofire threshold? There's no single number — each graduated head
derives its OWN probability cutoff from its PR curve: the operating point that
holds precision >= head_auto_apply_precision (0.97) at max recall. The global
knobs are that target + the >=30 support floor.

NEXT (slice 3): UI — enable toggle, dry-run preview, per-concept trends.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Ttrj5P7upUTueSfoJcxEqa

alembic/versions/0059_head_auto_apply.py

@@ -49,7 +49,7 @@ def upgrade() -> None:
         "ml_settings",
         sa.Column(
             "head_auto_apply_enabled", sa.Boolean(), nullable=False,
-            server_default=sa.false(),
+            server_default=sa.true(),  # opt-out: on by default (operator-asked)
         ),
     )
     op.add_column(

alembic/versions/0060_head_metrics.py

@@ -0,0 +1,74 @@
+"""head_metric + head_metrics_snapshot: auto-apply observability (#114)
+
+Running misfire/under-fire counters per concept (captured at correction time,
+since image_tag.source is lost on delete) + a daily per-concept time-series so
+the operator can tune the precision target + support floor from real data.
+
+Revision ID: 0060
+Revises: 0059
+Create Date: 2026-06-29
+"""
+from typing import Sequence, Union
+
+import sqlalchemy as sa
+from alembic import op
+
+revision: str = "0060"
+down_revision: Union[str, None] = "0059"
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    op.create_table(
+        "head_metric",
+        sa.Column(
+            "tag_id", sa.Integer(),
+            sa.ForeignKey("tag.id", ondelete="CASCADE"), primary_key=True,
+        ),
+        sa.Column("n_misfires", sa.Integer(), nullable=False, server_default="0"),
+        sa.Column("n_underfires", sa.Integer(), nullable=False, server_default="0"),
+        sa.Column(
+            "updated_at", sa.DateTime(timezone=True), nullable=False,
+            server_default=sa.func.now(),
+        ),
+    )
+
+    op.create_table(
+        "head_metrics_snapshot",
+        sa.Column("id", sa.Integer(), primary_key=True),
+        sa.Column(
+            "tag_id", sa.Integer(),
+            sa.ForeignKey("tag.id", ondelete="CASCADE"),
+        ),
+        sa.Column("name", sa.String(length=255), nullable=False),
+        sa.Column(
+            "snapshot_at", sa.DateTime(timezone=True), nullable=False,
+            server_default=sa.func.now(),
+        ),
+        sa.Column("n_auto_applied", sa.Integer(), nullable=False, server_default="0"),
+        sa.Column("n_misfires", sa.Integer(), nullable=False, server_default="0"),
+        sa.Column("n_underfires", sa.Integer(), nullable=False, server_default="0"),
+        sa.Column("ap", sa.Float(), nullable=True),
+        sa.Column("precision_cv", sa.Float(), nullable=True),
+        sa.Column("recall", sa.Float(), nullable=True),
+        sa.Column("n_pos", sa.Integer(), nullable=True),
+    )
+    op.create_index(
+        "ix_head_metrics_snapshot_tag_id", "head_metrics_snapshot", ["tag_id"],
+    )
+    op.create_index(
+        "ix_head_metrics_snapshot_snapshot_at", "head_metrics_snapshot",
+        ["snapshot_at"],
+    )
+
+
+def downgrade() -> None:
+    op.drop_index(
+        "ix_head_metrics_snapshot_snapshot_at", table_name="head_metrics_snapshot"
+    )
+    op.drop_index(
+        "ix_head_metrics_snapshot_tag_id", table_name="head_metrics_snapshot"
+    )
+    op.drop_table("head_metrics_snapshot")
+    op.drop_table("head_metric")