feat: add multi-source research aggregation example

Demonstrates parallel analyst execution with dependency-based
synthesis using runTasks(), sharedMemory, and dependsOn:

1. Three analyst agents research the same topic in parallel
   (technical, market, community perspectives)
2. Synthesizer waits for all analysts via dependsOn, reads
   shared memory, cross-references findings, and produces
   a unified report

Fixes #76

examples/13-research-aggregation.ts

@@ -0,0 +1,167 @@
+/**
+ * Example 13 — Multi-Source Research Aggregation
+ *
+ * Demonstrates:
+ * - Parallel execution: three analyst agents research the same topic independently
+ * - Dependency chain: synthesizer waits for all analysts to finish
+ * - Shared memory: analysts write findings, synthesizer reads and cross-references
+ *
+ * Flow:
+ *   [technical-analyst, market-analyst, community-analyst] (parallel) → synthesizer
+ *
+ * Run:
+ *   npx tsx examples/13-research-aggregation.ts
+ *
+ * Prerequisites:
+ *   ANTHROPIC_API_KEY env var must be set.
+ */
+
+import { OpenMultiAgent } from '../src/index.js'
+import type { AgentConfig, OrchestratorEvent, Task } from '../src/types.js'
+
+// ---------------------------------------------------------------------------
+// Topic
+// ---------------------------------------------------------------------------
+
+const TOPIC = 'WebAssembly adoption in 2026'
+
+// ---------------------------------------------------------------------------
+// Agents — three analysts + one synthesizer
+// ---------------------------------------------------------------------------
+
+const technicalAnalyst: AgentConfig = {
+  name: 'technical-analyst',
+  model: 'claude-sonnet-4-6',
+  systemPrompt: `You are a technical analyst. Given a topic, research its technical
+capabilities, limitations, performance characteristics, and architectural patterns.
+Write your findings as structured markdown. Store your analysis in shared memory
+under the key "technical_findings". Keep it to 200-300 words.`,
+  maxTurns: 2,
+}
+
+const marketAnalyst: AgentConfig = {
+  name: 'market-analyst',
+  model: 'claude-sonnet-4-6',
+  systemPrompt: `You are a market analyst. Given a topic, research industry adoption
+rates, key companies using the technology, market size estimates, and competitive
+landscape. Write your findings as structured markdown. Store your analysis in
+shared memory under the key "market_findings". Keep it to 200-300 words.`,
+  maxTurns: 2,
+}
+
+const communityAnalyst: AgentConfig = {
+  name: 'community-analyst',
+  model: 'claude-sonnet-4-6',
+  systemPrompt: `You are a developer community analyst. Given a topic, research
+developer sentiment, ecosystem maturity, learning resources, community size,
+and conference/meetup activity. Write your findings as structured markdown.
+Store your analysis in shared memory under the key "community_findings".
+Keep it to 200-300 words.`,
+  maxTurns: 2,
+}
+
+const synthesizer: AgentConfig = {
+  name: 'synthesizer',
+  model: 'claude-sonnet-4-6',
+  systemPrompt: `You are a research director who synthesizes multiple analyst reports
+into a single cohesive document. Read all findings from shared memory, then:
+
+1. Cross-reference claims across reports — flag agreements and contradictions
+2. Identify the 3 most important insights
+3. Produce a structured report with: Executive Summary, Key Findings,
+   Areas of Agreement, Open Questions, and Recommendation
+
+Keep the final report to 300-400 words.`,
+  maxTurns: 2,
+}
+
+// ---------------------------------------------------------------------------
+// Orchestrator + team
+// ---------------------------------------------------------------------------
+
+function handleProgress(event: OrchestratorEvent): void {
+  if (event.type === 'task:start') {
+    console.log(`  [START] ${event.taskTitle} → ${event.agentName}`)
+  }
+  if (event.type === 'task:complete') {
+    console.log(`  [DONE]  ${event.taskTitle} (${event.success ? 'OK' : 'FAIL'})`)
+  }
+}
+
+const orchestrator = new OpenMultiAgent({
+  defaultModel: 'claude-sonnet-4-6',
+  onProgress: handleProgress,
+})
+
+const team = orchestrator.createTeam('research-team', {
+  name: 'research-team',
+  agents: [technicalAnalyst, marketAnalyst, communityAnalyst, synthesizer],
+  sharedMemory: true,
+})
+
+// ---------------------------------------------------------------------------
+// Tasks — three analysts run in parallel, synthesizer depends on all three
+// ---------------------------------------------------------------------------
+
+const tasks: Task[] = [
+  {
+    title: 'Technical analysis',
+    description: `Research the technical aspects of ${TOPIC}. Focus on capabilities, limitations, performance, and architecture. Store findings in shared memory as "technical_findings".`,
+    assignee: 'technical-analyst',
+  },
+  {
+    title: 'Market analysis',
+    description: `Research the market landscape for ${TOPIC}. Focus on adoption rates, key players, market size, and competition. Store findings in shared memory as "market_findings".`,
+    assignee: 'market-analyst',
+  },
+  {
+    title: 'Community analysis',
+    description: `Research the developer community around ${TOPIC}. Focus on sentiment, ecosystem maturity, learning resources, and community activity. Store findings in shared memory as "community_findings".`,
+    assignee: 'community-analyst',
+  },
+  {
+    title: 'Synthesize report',
+    description: `Read all analyst findings from shared memory (technical_findings, market_findings, community_findings). Cross-reference claims, identify key insights, flag contradictions, and produce a unified research report.`,
+    assignee: 'synthesizer',
+    dependsOn: ['Technical analysis', 'Market analysis', 'Community analysis'],
+  },
+]
+
+// ---------------------------------------------------------------------------
+// Run
+// ---------------------------------------------------------------------------
+
+console.log('Multi-Source Research Aggregation')
+console.log('='.repeat(60))
+console.log(`Topic: ${TOPIC}`)
+console.log('Pipeline: 3 analysts (parallel) → synthesizer')
+console.log('='.repeat(60))
+console.log()
+
+const result = await orchestrator.runTasks(team, tasks)
+
+// ---------------------------------------------------------------------------
+// Output
+// ---------------------------------------------------------------------------
+
+console.log('\n' + '='.repeat(60))
+console.log(`Overall success: ${result.success}`)
+console.log(`Tokens — input: ${result.totalTokenUsage.input_tokens}, output: ${result.totalTokenUsage.output_tokens}`)
+console.log()
+
+for (const [name, r] of result.agentResults) {
+  const icon = r.success ? 'OK  ' : 'FAIL'
+  const tokens = `in:${r.tokenUsage.input_tokens} out:${r.tokenUsage.output_tokens}`
+  console.log(`  [${icon}] ${name.padEnd(20)} ${tokens}`)
+}
+
+const synthResult = result.agentResults.get('synthesizer')
+if (synthResult?.success) {
+  console.log('\n' + '='.repeat(60))
+  console.log('SYNTHESIZED REPORT')
+  console.log('='.repeat(60))
+  console.log()
+  console.log(synthResult.output)
+}
+
+console.log('\nDone.')