perf(ai): kontiguitas batch budget + max_tokens dinamis + urutan kronologis RETURNING

- pickBatchWithinBudget: stop di overflow pertama (break), bukan skip —
  batch tetap prefix kronologis tanpa gap analisis di tengah timeline.
  Diekstrak ke batchBudget.ts (pure, estimator di-inject) + regression test.
- callModerationLLM: param opsional maxTokens; text/media caller menghitung
  ceiling dari estimasi prompt (floor 2048, cap 16384) — batch kecil tak
  lagi reserve window completion 16k.
- getPending/IncompleteMessagesByConversation: sort hasil UPDATE..RETURNING
  by created_at ASC — Postgres tak menjamin urutan, konsumen (anchor konteks
  messages[0], prefix batch) bergantung pada urutan kronologis.

services/discord-gateway/src/modules/ai-moderation/llmCaller.ts

@@ -49,6 +49,10 @@ export async function callModerationLLM(
   targetIds: string[],
   label: string,
   signal?: AbortSignal,
+  // Output-side token cap. Defaults to the previous hard-coded value; batch
+  // callers pass a prompt-derived ceiling so small batches don't reserve a
+  // 16k completion budget (some routers pre-allocate KV cache per max_tokens).
+  maxTokens?: number,
 ): Promise<{
   results: AnalysisResult[];
   raw: ChatCompletion | null;
@@ -75,7 +79,7 @@ export async function callModerationLLM(
                 ];
           const completion = await llmChat({
             messages,
-            max_tokens: 16384,
+            max_tokens: maxTokens ?? 16384,
             jsonResponse: { type: "json_object" },
             retries: 0,
             signal,