diff --git a/figs/f2b_session_skew_prod.png b/figs/f2b_session_skew_prod.png
new file mode 100644
index 0000000..61e9e1d
Binary files /dev/null and b/figs/f2b_session_skew_prod.png differ
diff --git a/scripts/plot_session_skew_cdf.py b/scripts/plot_session_skew_cdf.py
index 4fe1477..e840c4d 100644
--- a/scripts/plot_session_skew_cdf.py
+++ b/scripts/plot_session_skew_cdf.py
@@ -47,32 +47,11 @@ def load_production_cdf(
     return xs, ys, d["n_sessions"], d["anchors_check"]
 
 
-def main() -> None:
-    parser = argparse.ArgumentParser()
-    parser.add_argument(
-        "--replay-trace",
-        default="traces/w600_r0.0015_st30.jsonl",
-    )
-    parser.add_argument(
-        "--prod-cache",
-        default="analysis/characterization/data/production_session_skew_cdf.json",
-    )
-    parser.add_argument("--out", default="figs/f2b_session_skew.png")
-    args = parser.parse_args()
+ANNOTATE_PTS = [1.0, 5.0, 10.0, 25.0, 50.0]
 
-    prod_x, prod_y, prod_n, prod_anchors = load_production_cdf(Path(args.prod_cache))
-    replay_rank_pct, replay_cum_pct, replay_n = load_replay_cdf(Path(args.replay_trace))
 
-    fig, ax = plt.subplots(figsize=(9, 5.5))
-
-    ax.plot(
-        prod_x, prod_y,
-        color="#c44e52", lw=2.4,
-        label=f"production trace (n={prod_n:,} sessions, 456-pt sampled)",
-    )
-
-    annotate_pts = [1.0, 5.0, 10.0, 25.0, 50.0]
-    for p in annotate_pts:
+def _annotate_anchors(ax, prod_x, prod_y) -> None:
+    for p in ANNOTATE_PTS:
         y = float(np.interp(p, prod_x, prod_y))
         ax.scatter([p], [y], color="#c44e52", s=55, zorder=5)
         ax.annotate(
@@ -83,32 +62,64 @@ def main() -> None:
             color="#7a1d1d",
         )
 
-    ax.plot(
-        replay_rank_pct, replay_cum_pct,
-        color="#2f6fab", lw=1.6,
-        alpha=0.85,
-        label=f"replay window (n={replay_n} sessions, raw CDF)",
-    )
 
-    ax.plot(
-        [0, 100], [0, 100],
-        color="#888", ls="--", lw=1,
-        label="uniform reference (y = x)",
-    )
-
-    ax.set_xlim(0, 100)
-    ax.set_ylim(0, 102)
+def plot_combined(prod_x, prod_y, prod_n, replay_rank_pct, replay_cum_pct, replay_n,
+                  out_path: Path) -> None:
+    fig, ax = plt.subplots(figsize=(9, 5.5))
+    ax.plot(prod_x, prod_y, color="#c44e52", lw=2.4,
+            label=f"production trace (n={prod_n:,} sessions, 456-pt sampled)")
+    _annotate_anchors(ax, prod_x, prod_y)
+    ax.plot(replay_rank_pct, replay_cum_pct, color="#2f6fab", lw=1.6, alpha=0.85,
+            label=f"replay window (n={replay_n} sessions, raw CDF)")
+    ax.plot([0, 100], [0, 100], color="#888", ls="--", lw=1,
+            label="uniform reference (y = x)")
+    ax.set_xlim(0, 100); ax.set_ylim(0, 102)
     ax.set_xlabel("Session rank percentile (top → bottom by input-token mass)")
     ax.set_ylabel("Cumulative % of input-token mass")
     ax.set_title("Session input-token mass CDF — Qwen3 production trace")
     ax.grid(True, alpha=0.3)
     ax.legend(loc="lower right", framealpha=0.92, fontsize=9)
-
-    out_path = Path(args.out)
     out_path.parent.mkdir(parents=True, exist_ok=True)
     fig.savefig(out_path, dpi=150, bbox_inches="tight")
+    plt.close(fig)
     print(f"wrote {out_path}")
 
 
+def plot_production_solo(prod_x, prod_y, prod_n, out_path: Path) -> None:
+    fig, ax = plt.subplots(figsize=(9, 5.5))
+    ax.plot(prod_x, prod_y, color="#c44e52", lw=2.6)
+    _annotate_anchors(ax, prod_x, prod_y)
+    ax.set_xlim(0, 100); ax.set_ylim(0, 102)
+    ax.set_xlabel("Session rank percentile (top → bottom by input-token mass)")
+    ax.set_ylabel("Cumulative % of input-token mass")
+    ax.set_title(
+        f"Session input-token mass CDF — Qwen3 production trace (n = {prod_n:,} sessions)"
+    )
+    ax.grid(True, alpha=0.3)
+    out_path.parent.mkdir(parents=True, exist_ok=True)
+    fig.savefig(out_path, dpi=150, bbox_inches="tight")
+    plt.close(fig)
+    print(f"wrote {out_path}")
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--replay-trace", default="traces/w600_r0.0015_st30.jsonl")
+    parser.add_argument(
+        "--prod-cache",
+        default="analysis/characterization/data/production_session_skew_cdf.json",
+    )
+    parser.add_argument("--out-combined", default="figs/f2b_session_skew.png")
+    parser.add_argument("--out-solo", default="figs/f2b_session_skew_prod.png")
+    args = parser.parse_args()
+
+    prod_x, prod_y, prod_n, _ = load_production_cdf(Path(args.prod_cache))
+    replay_rank_pct, replay_cum_pct, replay_n = load_replay_cdf(Path(args.replay_trace))
+
+    plot_combined(prod_x, prod_y, prod_n, replay_rank_pct, replay_cum_pct, replay_n,
+                  Path(args.out_combined))
+    plot_production_solo(prod_x, prod_y, prod_n, Path(args.out_solo))
+
+
 if __name__ == "__main__":
     main()