diff --git a/scripts/plot_run.py b/scripts/plot_run.py
new file mode 100644
index 0000000..b34750d
--- /dev/null
+++ b/scripts/plot_run.py
@@ -0,0 +1,54 @@
+"""Re-render a run's trajectory plot from its events.jsonl, without re-running the loop.
+
+Why this exists: the loop imports plot.py at process start, so a plot-code fix never
+reaches an already-running job. events.jsonl persists every stage (base/steered/healed),
+so we can rebuild the `stages` list offline and call the CURRENT write_trajectory.
+
+    uv run python scripts/plot_run.py --run-dir out/20260604T172126_gemma-3-4b-it_kl_rev_s42/
+
+A run from before the `base` event was persisted has no base node; pass it explicitly
+(tyro reads negatives as flags, so use `=`):
+    ... --base-auth=-2.35 --base-care=-1.30 --base-coh=0.996
+"""
+import sys
+from pathlib import Path
+
+import srsly
+import tyro
+
+from steer_heal.plot import write_trajectory
+
+
+def main(run_dir: Path, base_auth: float | None = None,
+         base_care: float | None = None, base_coh: float | None = None):
+    events = list(srsly.read_jsonl(run_dir / "events.jsonl"))
+    by_stage = lambda s: [e for e in events if e["stage"] == s]
+
+    base_ev = by_stage("base")
+    if base_ev:
+        bm = base_ev[0]
+        base = {"auth_nats": bm["auth_nats"], "care_nats": bm["care_nats"], "coherence": bm["coherence"]}
+    else:
+        # older run: base wasn't persisted. require it on the CLI (fail fast, no silent default).
+        assert base_auth is not None, (
+            f"{run_dir}/events.jsonl has no `base` event (ran before run.py persisted it); "
+            "pass --base-auth/--base-care/--base-coh from the run's base eval log line."
+        )
+        base = {"auth_nats": base_auth, "care_nats": base_care, "coherence": base_coh}
+
+    stages = [{"round": "-", "stage": "base", "m": base}]
+    steered = {e["round"]: e for e in by_stage("steered_eval")}
+    healed = {e["round"]: e for e in by_stage("round")}
+    for rnd in sorted(healed):  # one steered + one healed per completed round, in order
+        for src, kind in [(steered, "steered"), (healed, "healed")]:
+            e = src[rnd]
+            stages.append({"round": rnd, "stage": kind,
+                           "m": {"auth_nats": e["auth_nats"], "care_nats": e["care_nats"],
+                                 "coherence": e["coherence"]}})
+
+    png = write_trajectory(run_dir, stages)
+    print(f"re-rendered {png} from {len(stages)} stages ({len(healed)} rounds)", file=sys.stderr)
+
+
+if __name__ == "__main__":
+    tyro.cli(main)
diff --git a/src/steer_heal/plot.py b/src/steer_heal/plot.py
index 998f70a..af56e02 100644
--- a/src/steer_heal/plot.py
+++ b/src/steer_heal/plot.py
@@ -86,17 +86,23 @@ def write_trajectory(run_dir: Path, stages: list[dict]) -> Path:
         marker=dict(size=14, color=GREY, symbol="star"), showlegend=False,
         hovertext=[f"base auth={bx:.3f} coh={by:.3f}"], hoverinfo="text",
     ), row=1, col=2)
+    # scatter, NOT a polyline: the left zigzag panel already carries round order, so a
+    # connecting line here would just duplicate it (and tangle at 10 rounds). The map's one
+    # job is WHERE the two populations land in trait-coherence space -- steered scatters left
+    # (more trait, more variance), healed clusters near base (the stall). Label only the
+    # extremes (r0 + last round) so the labels don't collide in the cluster.
+    last_rnd = max(p["round"] for p in stages if p["stage"] == "healed")
     for stage_kind, color, label in [("steered", RED, "steer"), ("healed", GREEN, "heal")]:
         pts = [s for s in stages if s["stage"] == stage_kind]
-        xs = [bx] + [p["m"]["auth_nats"] for p in pts]
-        ys = [by] + [p["m"]["coherence"] for p in pts]
-        txt = [""] + [f"r{p['round']}" for p in pts]
-        hov = [f"base"] + [f"{label} r{p['round']} auth={p['m']['auth_nats']:.3f} "
-                           f"coh={p['m']['coherence']:.3f} care={p['m']['care_nats']:.3f}" for p in pts]
+        xs = [p["m"]["auth_nats"] for p in pts]
+        ys = [p["m"]["coherence"] for p in pts]
+        txt = [f"r{p['round']}" if p["round"] in (0, last_rnd) else "" for p in pts]
+        hov = [f"{label} r{p['round']} auth={p['m']['auth_nats']:.3f} "
+               f"coh={p['m']['coherence']:.3f} care={p['m']['care_nats']:.3f}" for p in pts]
         fig.add_trace(go.Scatter(
-            x=xs, y=ys, mode="lines+markers+text", text=txt, textposition="top center",
-            line=dict(color=color, width=2), marker=dict(size=11, color=color),
-            name=label, showlegend=False, hovertext=hov, hoverinfo="text",
+            x=xs, y=ys, mode="markers+text", text=txt, textposition="top center",
+            marker=dict(size=11, color=color), name=label, showlegend=False,
+            hovertext=hov, hoverinfo="text",
         ), row=1, col=2)
     fig.update_xaxes(title_text="auth_nats  (← more trait)", row=1, col=2)
     # same fixed coherence range as the line panel: shows the points hug the ceiling (coherence
diff --git a/src/steer_heal/run.py b/src/steer_heal/run.py
index 5d01c16..1ad8308 100644
--- a/src/steer_heal/run.py
+++ b/src/steer_heal/run.py
@@ -105,6 +105,7 @@ def steer_heal(model, tok, cfg: RunConfig, run_dir: Path) -> dict:
     # trait), not just coherence. One extra eval per run.
     logger.info(f"\n=== EVAL base [tinymfv classic] gpu {gpu_mem()} ===")
     base_m = evaluate_model(model, tok, cfg)
+    log_event(run_dir, stage="base", round=-1, **base_m)  # persist so offline plot_run.py is self-contained
     stages = [{"round": "-", "stage": "base", "m": base_m}]  # base -> steered -> healed, for table + trajectory plot
     for rnd in range(cfg.n_rounds):
         logger.info(f"\n\n=== ROUND {rnd} [{cfg.model.split('/')[-1]} reg={cfg.reg}] gpu {gpu_mem()} ===")