chore: import upstream snapshot with attribution

__tests__/evaluation/scoring.ts

@@ -0,0 +1,82 @@
+import type { EvalResult } from './types.js';
+
+export const PASS_THRESHOLD = 0.5;
+
+export function scoreSearchNodes(
+  caseId: string,
+  expectedSymbols: string[],
+  results: Array<{ node: { name: string }; score: number }>,
+  latencyMs: number
+): EvalResult {
+  const expectedLower = expectedSymbols.map((s) => s.toLowerCase());
+  const resultNames = results.map((r) => r.node.name.toLowerCase());
+
+  const found: string[] = [];
+  const missed: string[] = [];
+  let firstRank = 0;
+
+  for (let i = 0; i < expectedLower.length; i++) {
+    const idx = resultNames.indexOf(expectedLower[i]);
+    if (idx !== -1) {
+      found.push(expectedSymbols[i]);
+      if (firstRank === 0) firstRank = idx + 1;
+    } else {
+      missed.push(expectedSymbols[i]);
+    }
+  }
+
+  const recall = expectedSymbols.length > 0 ? found.length / expectedSymbols.length : 0;
+  const mrr = firstRank > 0 ? 1 / firstRank : 0;
+
+  return {
+    caseId,
+    pass: recall >= PASS_THRESHOLD,
+    recall,
+    mrr,
+    foundSymbols: found,
+    missedSymbols: missed,
+    latencyMs,
+  };
+}
+
+export function scoreFindRelevantContext(
+  caseId: string,
+  expectedSymbols: string[],
+  subgraph: { nodes: Map<string, { name: string }>; edges: unknown[]; roots: string[] },
+  latencyMs: number
+): EvalResult {
+  const expectedLower = new Set(expectedSymbols.map((s) => s.toLowerCase()));
+  const nodeNames = new Set<string>();
+  for (const node of subgraph.nodes.values()) {
+    nodeNames.add(node.name.toLowerCase());
+  }
+
+  const found: string[] = [];
+  const missed: string[] = [];
+
+  for (const sym of expectedSymbols) {
+    if (nodeNames.has(sym.toLowerCase())) {
+      found.push(sym);
+    } else {
+      missed.push(sym);
+    }
+  }
+
+  const recall = expectedSymbols.length > 0 ? found.length / expectedSymbols.length : 0;
+  const nodeCount = subgraph.nodes.size;
+  const edgeCount = subgraph.edges.length;
+  const edgeDensity = nodeCount > 0 ? edgeCount / nodeCount : 0;
+
+  return {
+    caseId,
+    pass: recall >= PASS_THRESHOLD,
+    recall,
+    mrr: 0,
+    foundSymbols: found,
+    missedSymbols: missed,
+    nodeCount,
+    edgeCount,
+    edgeDensity,
+    latencyMs,
+  };
+}