diff --git a/scripts/analyze-browser-metrics.py b/scripts/analyze-browser-metrics.py
new file mode 100755
index 00000000..27d38dab
--- /dev/null
+++ b/scripts/analyze-browser-metrics.py
@@ -0,0 +1,142 @@
+#!/usr/bin/env python3
+"""
+Analyze recorded browser-agent metrics and flag GHOST SUCCESS: tasks that
+report "completed" but show no evidence of real work (errors-only, looped, or
+zero productive mutation). A task ending without an exception is NOT proof the
+goal was achieved, this is the independent reality check.
+
+Usage:
+  python3 scripts/analyze-browser-metrics.py [metrics_dir]
+Defaults to $OPENSWARM_BROWSER_METRICS_DIR, else
+~/Library/Application Support/OpenSwarm/data/browser_metrics (mac) or backend/data/.
+"""
+
+import json
+import os
+import sys
+from collections import Counter, defaultdict
+
+# Tools that actually change page state (vs. read/meta). A "completed" task that
+# never ran one of these did nothing but look around, suspicious.
+_PRODUCTIVE = {
+    "BrowserClick", "BrowserClickIndex", "BrowserType", "BrowserNavigate",
+    "BrowserPressKey", "BrowserBatch", "BrowserReplayRoute",
+}
+
+
+def _default_dir():
+    env = os.environ.get("OPENSWARM_BROWSER_METRICS_DIR")
+    if env:
+        return env
+    mac = os.path.expanduser("~/Library/Application Support/OpenSwarm/data/browser_metrics")
+    if os.path.isdir(mac):
+        return mac
+    return os.path.join(os.path.dirname(__file__), "..", "backend", "data", "browser_metrics")
+
+
+def _load(path):
+    if not os.path.exists(path):
+        return []
+    out = []
+    with open(path) as f:
+        for line in f:
+            line = line.strip()
+            if line:
+                try:
+                    out.append(json.loads(line))
+                except Exception:
+                    pass
+    return out
+
+
+def ghost_verdict(task, events_for_task):
+    """Return (is_ghost, [reasons]). Conservative: only flags 'completed' tasks
+    that show no evidence the work happened."""
+    if task.get("status") != "completed":
+        return False, []
+    reasons = []
+    tools = [e["tool"] for e in events_for_task]
+    productive = [t for t in tools if t in _PRODUCTIVE]
+    errs = sum(1 for e in events_for_task if not e.get("ok"))
+    total = len(events_for_task)
+    if total == 0:
+        reasons.append("completed with ZERO tool calls (model declared done without acting)")
+    if total and not productive:
+        reasons.append("no state-changing action ran (only reads/meta) yet marked completed")
+    if total and errs / total >= 0.5:
+        reasons.append(f"{errs}/{total} tool calls errored but still marked completed")
+    if any(e.get("is_loop") for e in events_for_task):
+        reasons.append("loop detector fired during a 'completed' task")
+    prod_ok = [e for e in events_for_task if e["tool"] in _PRODUCTIVE and e.get("ok")]
+    if productive and not prod_ok:
+        reasons.append("every state-changing action errored, yet marked completed")
+    return (len(reasons) > 0), reasons
+
+
+def main():
+    d = sys.argv[1] if len(sys.argv) > 1 else _default_dir()
+    events = _load(os.path.join(d, "events.jsonl"))
+    tasks = _load(os.path.join(d, "tasks.jsonl"))
+    print(f"metrics dir: {d}")
+    print(f"events: {len(events)}  tasks: {len(tasks)}\n")
+    if not tasks and not events:
+        print("No metrics recorded yet. Run some browser-agent tasks first.")
+        return
+
+    ev_by_session = defaultdict(list)
+    for e in events:
+        ev_by_session[e.get("session_id")].append(e)
+
+    # Per-tier rollup across all events
+    tier_calls, tier_ms, tier_err = Counter(), Counter(), Counter()
+    for e in events:
+        t = e.get("tier", "other")
+        tier_calls[t] += 1
+        tier_ms[t] += int(e.get("elapsed_ms", 0) or 0)
+        if not e.get("ok"):
+            tier_err[t] += 1
+
+    print("=== PER-TIER (across all tool calls) ===")
+    print(f"{'tier':<20}{'calls':>6}{'avg_ms':>9}{'err%':>7}")
+    for t in sorted(tier_calls, key=lambda x: -tier_calls[x]):
+        c = tier_calls[t]
+        avg = round(tier_ms[t] / c, 1) if c else 0
+        errp = round(100 * tier_err[t] / c, 1) if c else 0
+        print(f"{t:<20}{c:>6}{avg:>9}{errp:>6}%")
+
+    print("\n=== PER-TASK (completion, time, cost, ghost check) ===")
+    completed = ghosts = 0
+    all_errs = Counter()
+    for tk in tasks:
+        evs = ev_by_session.get(tk.get("session_id"), [])
+        is_ghost, reasons = ghost_verdict(tk, evs)
+        if tk.get("status") == "completed":
+            completed += 1
+        if is_ghost:
+            ghosts += 1
+        for err, n in tk.get("recurring_errors", []):
+            all_errs[err] += n
+        flag = "  ⚠️ GHOST" if is_ghost else ""
+        print(f"- [{tk.get('status')}] {tk.get('total_ms')}ms turns={tk.get('turns')} "
+              f"tools={tk.get('tool_calls')} tok_in={tk.get('tokens_in')} "
+              f"tok_out={tk.get('tokens_out')} :: {str(tk.get('task'))[:60]}{flag}")
+        for r in reasons:
+            print(f"      ghost-reason: {r}")
+
+    print("\n=== RECURRING ERRORS (top 10 across tasks) ===")
+    for err, n in all_errs.most_common(10):
+        print(f"  x{n}  {err}")
+
+    print("\n=== SUMMARY ===")
+    n = len(tasks)
+    print(f"tasks: {n}  completed: {completed}  ghost-completed: {ghosts}")
+    if n:
+        avg_ms = round(sum(t.get("total_ms", 0) for t in tasks) / n)
+        avg_tok = round(sum(t.get("tokens_in", 0) + t.get("tokens_out", 0) for t in tasks) / n)
+        print(f"avg task time: {avg_ms}ms   avg tokens/task: {avg_tok}")
+        print(f"honest completion rate: {round(100*(completed-ghosts)/n,1)}% "
+              f"(completed minus ghosts)")
+
+
+if __name__ == "__main__":
+    main()