feat: latency vs prompt size scatter plot on dashboard

Router: new /metrics/scatter endpoint returns individual data points
(prompt_tokens, inference_ms, model, agent, reason, stream)
for scatter visualization.

Dashboard: new panel showing latency vs prompt size by model.
- Log-scale X axis (prompt tokens) with model color coding
- Dropdown to filter by individual model or view all
- Hover tooltips with details per point
- Auto-refresh every 30s

Enables direct observation of context-length vs latency
relationship — validates routing tier decisions.

router/router.py

@@ -537,6 +537,36 @@ def performance():
     except Exception as e:
         return jsonify({"error": str(e)}), 500
 
+@app.route("/metrics/scatter")
+def scatter():
+    """Return individual data points for scatter plots (prompt_tokens vs latency)."""
+    if not r: return jsonify({"error": "Redis unavailable"}), 503
+    try:
+        window_hours = int(request.args.get("window", "24"))
+        model_filter = request.args.get("model", "all")
+        cutoff = time.time() - (window_hours * 3600)
+        raw = r.lrange("perf:recent", 0, -1)
+        points = []
+        for x in raw:
+            try:
+                rec = json.loads(x)
+                if rec["ts"] >= cutoff:
+                    if model_filter == "all" or rec["model"] == model_filter:
+                        points.append({
+                            "model": rec["model"],
+                            "agent": rec["agent"],
+                            "reason": rec["reason"],
+                            "prompt_tokens": int(rec.get("prompt_tokens", 0)),
+                            "completion_tokens": rec.get("completion_tokens", 0),
+                            "inference_ms": round(rec["inference_ms"], 1),
+                            "tokens_per_sec": rec.get("tokens_per_sec", 0),
+                            "stream": rec.get("stream", False)
+                        })
+            except: pass
+        return jsonify({"points": points, "count": len(points)})
+    except Exception as e:
+        return jsonify({"error": str(e)}), 500
+
 @app.route("/v1/models")
 def models():
     def _h(m): return check_gpu_health(m, sidecar_timeout=1.5, gpu_timeout=1)