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/llm/llm.go

@@ -0,0 +1,36 @@
+// Package llm defines the OpenAI-compatible chat client interface used to
+// exercise language models under test, plus a concrete HTTP implementation.
+package llm
+
+import (
+	"context"
+	"time"
+)
+
+// Message is a single chat message in an OpenAI-compatible conversation.
+type Message struct {
+	Role    string
+	Content string
+}
+
+// Request is one chat-completion request sent to a model.
+type Request struct {
+	Model       string
+	Messages    []Message
+	MaxTokens   int
+	Temperature float64
+}
+
+// Response is the normalized result of a chat-completion call.
+type Response struct {
+	Text             string
+	PromptTokens     int
+	CompletionTokens int
+	Latency          time.Duration
+}
+
+// Client completes chat requests against a language model backend.
+// Implementations must be safe for concurrent use.
+type Client interface {
+	Complete(ctx context.Context, req Request) (Response, error)
+}