feat: LLM accuracy testing framework with 17-test catalog

Framework runs a category/subcategory test catalog against multiple
LLMs through an OpenAI-compatible endpoint. Deterministic evaluators
score each response. Reports render as table, markdown, or JSON.

internal/tests/web_test.go

@@ -0,0 +1,31 @@
+package tests
+
+import (
+	"context"
+	"testing"
+)
+
+func TestWebRobotsAICrawlersTest_Eval(t *testing.T) {
+	tc := webRobotsAICrawlersTest()
+
+	tests := []struct {
+		name     string
+		response string
+		want     float64
+	}{
+		{"correct: only ClaudeBot", `["ClaudeBot"]`, 1},
+		{"correct fenced", "```json\n[\"ClaudeBot\"]\n```", 1},
+		{"includes decoy Googlebot", `["ClaudeBot","Googlebot"]`, 0.5},
+		{"includes disallowed GPTBot", `["ClaudeBot","GPTBot"]`, 0.5},
+		{"empty answer", `[]`, 0},
+		{"only wrong bots", `["GPTBot","PerplexityBot"]`, 0},
+	}
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			got := tc.Eval.Evaluate(context.Background(), tt.response)
+			if got.Value != tt.want {
+				t.Errorf("Eval.Evaluate(%q) = %v, want %v (detail: %s)", tt.response, got.Value, tt.want, got.Detail)
+			}
+		})
+	}
+}