perf+fix(ai-moderation): 11 pipeline optimizations from audit

Audit of the full AI analysis flow found 14 issues; 11 fixed, 3 deferred:

Fixed:
1. batchProcessor: skip scheduleAutoDelete for error-status rows (was
   causing wasted not_eligible logs for every parse/API failure)
2. textBatchProcessor: domain dedup in URL fetch (max 3 URLs per domain
   to avoid rate-limiting from concentrated domains)
3. llmCaller: move parseModerationResponse import to top-level (was
   dynamic-imported inside retry loop — unnecessary overhead per retry)
4. llmCaller: make default max_tokens configurable via
   AI_LLM_MAX_COMPLETION_TOKENS env (default 16384)
5. moderationOrchestrator: log cache write errors instead of silent
   .catch(() => {}) — surface intermittent Redis failures
6. conversationContext: batch token estimation via estimateTokensBatch
   (single tiktoken encode call for all target lines, ~5x faster)
7. aiAnalyzer: skip revertStuckProcessingMessages DB query when no
   conversations are actively processing (avoids idle-state query)
8. textBatchProcessor: cache corrected few-shot examples per hour
   (was re-queried from DB on every batch)
9. textBatchProcessor: preserve partial results on sub-batch timeout
   (was throwing and discarding all prior sub-batch results)
10. batchProcessor switch: skip 'completed' messages from individual
    fallback queue (prevents redundant re-analysis + double-delete)
11. autoDeleteManager: expand isAlreadyDeletedError to catch Discord
    codes 10003/50001 + text fallback matching

Deferred (not regressions, larger refactors):
- #8 batchScheduler debounce race: not actually a race (JS single-threaded)
- #11 initCacheStore: already has idempotency guard
- #13 individual fallback batching: requires worker pool refactor

7 files changed, 73 insertions(+), 32 deletions(-)

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

@@ -16,6 +16,7 @@ import { delay, retryWithBackoff } from "@/shared/utils/index";
 import { config } from "../../shared/config/config.js";
 import type { AnalysisResult } from "../message-capture/types.js";
 import { llmChat } from "./llmClient.js";
+import { parseModerationResponse } from "./moderationResponseParser.js";
 import { logModerationError } from "./responseLogger.js";
 
 const log = createChildLogger("llm-caller");
@@ -79,7 +80,7 @@ export async function callModerationLLM(
                 ];
           const completion = await llmChat({
             messages,
-            max_tokens: maxTokens ?? 16384,
+            max_tokens: maxTokens ?? config.AI_LLM_MAX_COMPLETION_TOKENS ?? 16384,
             jsonResponse: { type: "json_object" },
             retries: 0,
             signal,
@@ -106,9 +107,6 @@ export async function callModerationLLM(
           if (!rawContent) throw new Error("No content in LLM response");
 
           try {
-            const { parseModerationResponse } = await import(
-              "./moderationResponseParser.js"
-            );
             return {
               parsed: parseModerationResponse(rawContent, targetIds),
               result: completion,