Docs: Update benchmark for openai/gpt-5.2 EFF:xhigh

tests/2_convex_hull/outputs/openai_gpt-5.2 EFF_xhigh.js

@@ -0,0 +1,41 @@
+const loadLodash = (() => {
+  let p;
+  return () =>
+    p || (p = import("https://cdn.jsdelivr.net/npm/lodash@4.17.21/+esm")
+      .then(m => m.default || m)
+      .catch(e => (p = null, Promise.reject(e))));
+})();
+
+async function findConvexHull(points) {
+  const _ = await loadLodash();
+  if (!Array.isArray(points)) throw new TypeError("Expected an array of points");
+
+  const pts = _.uniqBy(
+    points.filter(p => p && Number.isFinite(p.x) && Number.isFinite(p.y)),
+    p => `${p.x}|${p.y}`
+  );
+
+  if (pts.length < 2) return pts.slice();
+
+  const s = _.sortBy(pts, ["x", "y"]);
+  const cross = (o, a, b) =>
+    (a.x - o.x) * (b.y - o.y) - (a.y - o.y) * (b.x - o.x);
+
+  const build = arr => {
+    const h = [];
+    for (const p of arr) {
+      while (h.length > 1 && cross(h[h.length - 2], h[h.length - 1], p) <= 0) h.pop();
+      h.push(p);
+    }
+    return h;
+  };
+
+  const lo = build(s);
+  const up = build(s.slice().reverse());
+  lo.pop();
+  up.pop();
+  return lo.concat(up);
+}
+export default findConvexHull;
+// Generation time: 134.929s
+// Result: PASS