feat: cap-aware autoscaler + token-gated whole-instance tag reset (operator feedback)

Autoscaler (agent 2026-07-02.5): the buffer-occupancy signal alone would peg
downloaders at DL_MAX while the bandwidth CAP — not concurrency — is the real
constraint (8 streams sharing 8 MB/s move no more data than 4). Growth is now
gated on the pipe having headroom (net < 85% of cap) and a pipe pinned at the
cap (>= 95%) sheds streams down to 3; dead band prevents flapping. The UI hint
says 'holding at the bandwidth cap' and /status reports bw_capped, so the
behavior is legible without tests that need the ML stack.

Reset content tagging: stays a FULL-instance reset (operator's call), but now
lives in a fenced 'Danger zone' section on Cleanup and the apply is gated by a
preview-derived confirm token (mirrors the Tier-C bulk-delete pattern — stale
counts are rejected server-side). Copy no longer claims suggestions repopulate:
it says plainly the heads' training examples are deleted and re-tagging starts
fresh. Moved out of TagMaintenanceCard into DangerZoneCard.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CDgx8bQS5YrGRK76v8HUnM

backend/app/api/admin.py

@@ -276,18 +276,48 @@ async def posts_reconcile_duplicates():
     return await _run_dry_run_op(reconcile_duplicate_posts, source_id=source_id)
 
 
+def _reset_content_confirm_token(projection: dict) -> str:
+    """Stable 8-hex token derived from the live counts (mirrors the Tier-C
+    bulk-delete token): it changes whenever the data changes, so the apply can
+    only ever run against numbers the operator just previewed."""
+    canon = f"reset-content:{projection.get('count')}:{projection.get('applications')}"
+    return hashlib.sha256(canon.encode("utf-8")).hexdigest()[:8]
+
+
 @admin_bp.route("/tags/reset-content", methods=["POST"])
 async def tags_reset_content():
-    """Tier-A: delete ALL general + character tags (the Camie-suggestable
-    content vocabulary) so the operator can re-tag from scratch via
-    auto-suggest. fandom + series tags + series_page ordering are preserved,
-    and image_prediction rows are untouched so suggestions repopulate.
-    dry-run preview returns per-kind counts + applications + a sample so the
-    UI shows exactly what'll go before the operator confirms (dry_run=false).
-    Irreversible except via DB backup restore."""
+    """Full-instance reset of the CONTENT vocabulary: deletes ALL general +
+    character tags and their image applications — INCLUDING the examples the
+    tagging heads learned from. Suggestions do NOT repopulate on their own
+    (the Camie predictions that once did are long retired): the operator
+    re-tags from scratch and the heads retrain from the new signal. fandom +
+    series tags + series_page ordering are preserved.
+
+    Deliberately Tier-C-gated despite the Tier-A shape (operator 2026-07-02:
+    the full reset stays, but behind extra steps): dry_run returns the
+    projection + a `confirm` token derived from the live counts; the apply
+    must echo that token back or it is rejected."""
     from ..services.cleanup_service import reset_content_tagging
 
-    return await _run_dry_run_op(reset_content_tagging)
+    body = await request.get_json(silent=True) or {}
+    dry_run = bool(body.get("dry_run", False))
+    async with get_session() as session:
+        projection = await session.run_sync(
+            lambda s: reset_content_tagging(s, dry_run=True)
+        )
+        token = _reset_content_confirm_token(projection)
+        if dry_run:
+            projection["confirm"] = token
+            return jsonify(projection)
+        if str(body.get("confirm", "")) != token:
+            return _bad(
+                "confirm_mismatch",
+                detail="run a fresh preview and echo its confirm token",
+            )
+        result = await session.run_sync(
+            lambda s: reset_content_tagging(s, dry_run=False)
+        )
+    return jsonify(result)
 
 
 @admin_bp.route("/tags/normalize", methods=["POST"])