debug: expose full inputs/outputs in Recalculer response for diagnosis

_run_auto_analysis now returns a rich dict {ok, inputs, node_values, actual_moves, error}
instead of bool. The refresh endpoint captures and forwards:
- inputs: what values were fed to evaluate_graph
- node_keys: which nodes were computed in prediction
- actual_moves: actual price pips fetched
- run_error: exception message if it failed

Frontend shows all of this after clicking Recalculer so the root cause is visible.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

backend/routers/causal_lab.py

@@ -1127,11 +1127,10 @@ def _build_graph_json_from_spec(spec: dict) -> dict:
     }
 
 
-def _run_auto_analysis(event: dict, template_id: int) -> bool:
+def _run_auto_analysis(event: dict, template_id: int) -> dict:
     """
     Causal analysis for the auto_template pipeline.
-    Builds inputs from event fields, evaluates the graph, fetches actual prices,
-    and upserts into causal_event_analyses so the instrument frise can score it.
+    Returns {"ok": bool, "inputs": dict, "node_values": dict, "actual_moves": dict, "error": str}.
     """
     try:
         from services.database import get_conn
@@ -1142,7 +1141,7 @@ def _run_auto_analysis(event: dict, template_id: int) -> bool:
         if not tmpl:
             conn.close()
             logger.warning(f"[auto_analysis] template #{template_id} introuvable")
-            return False
+            return {"ok": False, "error": f"template #{template_id} introuvable"}
 
         graph   = tmpl["graph_json"]
         inputs  = {}
@@ -1310,11 +1309,17 @@ def _run_auto_analysis(event: dict, template_id: int) -> bool:
         conn.commit()
         conn.close()
         logger.info(f"[auto_analysis] upserted event #{event_id}, tmpl #{template_id}, actual_moves={actual_moves}")
-        return True
+        return {
+            "ok": True,
+            "inputs": inputs,
+            "node_values": node_values,
+            "actual_moves": actual_moves,
+            "instruments": instruments,
+        }
 
     except Exception as e:
-        logger.error(f"[auto_analysis] event #{event.get('id')}: {e}")
-        return False
+        logger.error(f"[auto_analysis] event #{event.get('id')}: {e}", exc_info=True)
+        return {"ok": False, "error": str(e)}
 
 
 def auto_assign_template(event_id: int) -> dict:
@@ -1481,13 +1486,16 @@ def refresh_auto_analyses():
                 detail["actual_value"]    = ev.get("actual_value")
                 detail["expected_value"]  = ev.get("expected_value")
                 detail["start_date"]      = ev.get("start_date")
-                ok = _run_auto_analysis(ev, row["template_id"])
-                detail["result"] = "ok" if ok else "failed"
-                if ok:
+                res = _run_auto_analysis(ev, row["template_id"])
+                detail["result"]         = "ok" if res["ok"] else "failed"
+                detail["inputs"]         = res.get("inputs", {})
+                detail["node_keys"]      = list(res.get("node_values", {}).keys())
+                detail["actual_moves"]   = res.get("actual_moves", {})
+                detail["run_error"]      = res.get("error")
+                if res["ok"]:
                     refreshed += 1
                 else:
                     failed += 1
-                    detail["result"] = "run_returned_false"
             except Exception as _e:
                 logger.warning(f"[refresh_auto_analyses] cea#{row['cea_id']}: {_e}")
                 detail["result"] = f"exception: {_e}"

frontend/src/pages/InstrumentDashboard.tsx

@@ -1152,13 +1152,16 @@ function ExplanationScore({
                 : <span>Refresh: {debugInfo.refreshed} ok / {debugInfo.failed} err / {debugInfo.total} total</span>
               }
               {debugInfo.details?.map((d: any, i: number) => (
-                <div key={i} className="mt-0.5">
-                  #{d.event_id} {(d.event_name ?? '').slice(0, 22)} → <span className={d.result === 'ok' ? 'text-emerald-600' : 'text-red-500'}>{d.result}</span>
-                  {d.surprise_pct != null
-                    ? <span className="text-cyan-700 ml-1">surp:{Number(d.surprise_pct).toFixed(1)}%</span>
-                    : d.actual_value != null
-                    ? <span className="text-amber-700 ml-1">act:{d.actual_value} exp:{d.expected_value ?? '?'}</span>
-                    : <span className="text-red-800 ml-1">surp=null</span>}
+                <div key={i} className="mt-1 border-t border-slate-800/40 pt-1">
+                  <span className={d.result === 'ok' ? 'text-emerald-500' : 'text-red-500'}>{d.result}</span>
+                  <span className="text-slate-500 ml-1">#{d.event_id} {(d.event_name ?? '').slice(0, 20)}</span>
+                  {d.run_error && <span className="text-red-400 ml-1">err:{d.run_error.slice(0, 40)}</span>}
+                  <div className="ml-2 text-slate-600">
+                    surp:{d.surprise_pct != null ? Number(d.surprise_pct).toFixed(1)+'%' : `null (act=${d.actual_value} exp=${d.expected_value})`}
+                    {' | '}inputs:{JSON.stringify(d.inputs ?? {})}
+                    {' | '}pred_keys:[{(d.node_keys ?? []).join(',')}]
+                    {' | '}actual:{JSON.stringify(d.actual_moves ?? {})}
+                  </div>
                 </div>
               ))}
             </div>