feat: add Mixture of Agents (MoA) for arbiter verdicts

When MOA_ENABLED=true, arbiter queries multiple LLM models in parallel
via OpenAI-compatible API, then an aggregator model synthesizes the
final verdict from all opinions. Falls back to single-agent arbiter
when MoA is disabled.

Config: MOA_BASE_URL, MOA_API_KEY, MOA_REFERENCE_MODELS, MOA_AGGREGATOR_MODEL

src/message-agent-executor.ts

@@ -41,9 +41,14 @@ import {
 import {
   CODEX_REVIEW_SERVICE_ID,
   SERVICE_SESSION_SCOPE,
+  TIMEZONE,
   isClaudeService,
   getRoleModelConfig,
+  getMoaConfig,
 } from './config.js';
+import { buildArbiterContextPrompt } from './arbiter-context.js';
+import { runMoaArbiter } from './moa.js';
+import { readArbiterPrompt } from './platform-prompts.js';
 import {
   activateCodexFailover,
   getEffectiveChannelLease,
@@ -323,6 +328,75 @@ export async function runAgentForGroup(
     return 'success';
   }
 
+  // ── MoA arbiter path ────────────────────────────────────────────
+  // When MoA is enabled and we're in arbiter mode, query multiple
+  // models in parallel instead of spawning a single agent process.
+  const moaConfig = getMoaConfig();
+  if (arbiterMode && moaConfig.enabled && pairedExecutionContext) {
+    logger.info(
+      {
+        chatJid,
+        group: group.name,
+        runId,
+        referenceModels: moaConfig.referenceModels.map((m) => m.model),
+        aggregator: moaConfig.aggregator.model,
+      },
+      'Running MoA arbiter instead of single agent',
+    );
+
+    const systemPrompt =
+      readArbiterPrompt(process.cwd()) || 'You are an arbiter.';
+    const contextPrompt = buildArbiterContextPrompt({
+      chatJid,
+      taskId: pairedExecutionContext.task.id,
+      roundTripCount: pairedExecutionContext.task.round_trip_count,
+      timezone: TIMEZONE,
+    });
+
+    try {
+      const moaResult = await runMoaArbiter({
+        config: moaConfig,
+        systemPrompt,
+        contextPrompt,
+      });
+
+      pairedExecutionSummary = moaResult.verdict.slice(0, 500);
+      pairedExecutionStatus = 'succeeded';
+
+      // Build display text with reference model opinions
+      const referenceSection = moaResult.referenceResponses
+        .filter((r) => !r.error)
+        .map((r) => `**${r.model}**: ${r.response.split('\n')[0]}`)
+        .join('\n');
+      const displayText = referenceSection
+        ? `${moaResult.verdict}\n\n---\n*MoA references: ${moaResult.referenceResponses.filter((r) => !r.error).length} models queried*\n${referenceSection}`
+        : moaResult.verdict;
+
+      await onOutput?.({
+        status: 'success',
+        result: null,
+        output: { visibility: 'public', text: displayText },
+        phase: 'final',
+      });
+    } catch (error) {
+      logger.error(
+        { chatJid, group: group.name, runId, error },
+        'MoA arbiter failed',
+      );
+      pairedExecutionSummary = 'ESCALATE\nMoA arbiter failed';
+      pairedExecutionStatus = 'failed';
+    }
+
+    completePairedExecutionContext({
+      taskId: pairedExecutionContext.task.id,
+      role: 'arbiter',
+      status: pairedExecutionStatus,
+      summary: pairedExecutionSummary,
+    });
+    pairedExecutionCompleted = true;
+    return pairedExecutionStatus === 'succeeded' ? 'success' : 'error';
+  }
+
   const runAttempt = async (
     provider: string,
   ): Promise<{