signal_log: weight-research data points, scan_outcomes forward labels, watch provenance

New additive columns on every logged scan: bar_ts (primary closed-bar label, indexed with
timeframe), engine_fingerprint (hash of the scoring config incl. the regime weight table in
force - SignalAggregator.engine_config_fingerprint, twin of the gate fingerprint), code_version
(short git SHA), penalty_tags_json / penalty_total / momentum_fading / exhaustion_count, and
post-hoc watch_level / watch_kinds / watch_line written by violent_watch.attach_watch via
signal_log.update_watch. Each indicators_json entry now also carries eff_weight (base weight x
regime multiplier, the weight the composite actually used) and wscore.

engine: IndicatorSignal.effective_weight / weighted_score are stamped inside _compute_composite
(record-keeping only); regime_weight_table(config) is the single source of truth for the
multiplier table (override honoured). Composite output byte-identical (120-report hash proof).

New table scan_outcomes: model-free forward moves per scan (fwd_1h/4h/24h in $ and ATRs,
mfe/mae over 24h, burst_1h, bars_used, complete) measured on the stored candle stream with the
advisory model's continuity rule; labelled opportunistically at the end of log() (time-boxed,
throttled, idempotent) - no daemon; scripts/label_scan_outcomes.py drives the backlog
(--dry-run is read-only). analyze_signal_log --scan-outcomes: forward move + hit rate by
TF x signal/grade with a NEUTRAL baseline and burst rate by watch level. Readers dedup by the
first row per (timeframe, bar_ts).

Module 31 (10 tests). Suite: 463 passed. Backtester untouched (test-locked).

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01RWV2yLt3YXHHGVYHSQU2EE

violent_watch.py

@@ -350,6 +350,21 @@ def assess(report: Any,
                         readings=readings, likely_direction=direction)
 
 
+def _log_watch(report: Any, watch: "ViolentWatch") -> None:
+    """Persist the assessment onto the scan's signals.db row (fail-safe).
+
+    The row is inserted inside analyze_pair — BEFORE a surface attaches
+    the watch — so these columns arrive by post-hoc update, exactly like
+    the panel verdict. Level and kinds are written even when the display
+    line is off: evaluating the watch needs the assessment, not the text.
+    """
+    try:
+        from signal_log import log_watch_update
+        log_watch_update(report, watch)
+    except Exception:
+        logger.debug("violent watch: logging failed", exc_info=True)
+
+
 def attach_watch(report: Any,
                  primary_tf: Optional[Timeframe],
                  settings: Dict[str, Any],
@@ -377,6 +392,7 @@ def attach_watch(report: Any,
         watch = assess(report, moment, events, primary_tf)
         if settings.get("alert_line", True):
             report.watch_line = watch.line()
+        _log_watch(report, watch)
         return watch
     except Exception:
         logger.exception("violent watch: assessment failed")