perf(ai-moderation): drop personal user-profile descriptions from context

User insight: personal profile summaries bloat the prompt (less room per
request) and add a per-user DB/Redis round-trip for little moderation signal.
Only the behavioural <user_reputation> history is kept.

- textBatchProcessor: stop fetching getUserProfile; remove <user_profiles>
  block + <user_profile_ref> from message tags. Keep <user_reputation>.
- mediaBatchProcessor + visionAnalyzer: same removal (profile fetch + ref).
- prompts/system.ts + prompts/output.ts: drop stale <user_profiles>/
  <user_profile_ref> instructions; point LLM at <user_reputation> instead.
- aiAnalyzer: gate userProfileLearner behind AI_USER_PROFILE_LEARNING_ENABLED
  (default false) — generates profiles nobody reads, pure LLM/DB waste.
- Add AI_USER_PROFILE_LEARNING_ENABLED config knob.

Net: smaller prompts (more messages fit per request), fewer DB round-trips
per sub-batch, and no background LLM calls learning unused profiles.

tsc, biome, vitest (129) all clean.

services/discord-gateway/src/shared/config/index.ts

@@ -217,6 +217,14 @@ export const configSchema = z
       .default(true),
     // Max glossary terms looked up per analysis batch (keeps latency bounded).
     AI_GLOSSARY_MAX_TERMS: z.coerce.number().int().min(1).max(20).default(6),
+    // Per-user personal profile summaries (userProfileLearner). Disabled by
+    // default: profiles bloat the analysis context and add LLM/DB cost for
+    // little moderation signal — only <user_reputation> history is injected.
+    AI_USER_PROFILE_LEARNING_ENABLED: z
+      .string()
+      .optional()
+      .transform((v) => v === "true")
+      .default(false),
     // Min word length for a term to be considered glossary-worthy.
     AI_GLOSSARY_MIN_WORD_LENGTH: z.coerce
       .number()