ReasonerContext

agent.reasoner('analyze', async (ctx) => {
  // Access input data
  const { text } = ctx.input;

  // Use AI with the context
  const analysis = await ctx.ai(`Analyze: ${text}`);

  // Access memory
  await ctx.memory.set('last_analysis', analysis);

  // Call other agents
  const enriched = await ctx.call('enrichment-agent.enrich', { data: analysis });

  return { analysis, enriched };
});

// Simple text generation
const response = await ctx.ai('Explain quantum computing');

// With system prompt
const response = await ctx.ai('Analyze this text', {
  system: 'You are a sentiment analyzer.'
});

// Structured output with Zod
import { z } from 'zod';

const SentimentSchema = z.object({
  sentiment: z.enum(['positive', 'negative', 'neutral']),
  confidence: z.number(),
  keywords: z.array(z.string())
});

const result = await ctx.ai('I love this product!', {
  schema: SentimentSchema
});
// result is typed as { sentiment, confidence, keywords }

const stream = await ctx.aiStream('Write a long story');

for await (const chunk of stream) {
  process.stdout.write(chunk);
}

// Call another agent's reasoner
const result = await ctx.call('sentiment-agent.analyze', {
  text: 'Great product!'
});

// Call a skill
const formatted = await ctx.call('formatter-agent.format_json', {
  data: result
});

const discovery = await ctx.discover({
  tags: ['analysis'],
  includeDescriptions: true
});

for (const agent of discovery.json?.capabilities || []) {
  console.log(`${agent.agentId}: ${agent.reasoners.length} reasoners`);
}

import { z } from 'zod';

const TicketAnalysis = z.object({
  category: z.string(),
  priority: z.enum(['low', 'medium', 'high', 'critical']),
  sentiment: z.string(),
  suggestedAction: z.string()
});

agent.reasoner('analyze_ticket', async (ctx) => {
  const { ticketId, content } = ctx.input;

  // Track progress
  await ctx.workflow.progress(10, { status: 'analyzing' });

  // Get customer history from memory
  const history = await ctx.memory.session(ticketId).get('history') || [];

  // Analyze with AI
  const analysis = await ctx.ai(
    `Analyze this support ticket:\n${content}\n\nCustomer history: ${JSON.stringify(history)}`,
    {
      system: 'You are a support ticket analyzer.',
      schema: TicketAnalysis
    }
  );

  await ctx.workflow.progress(50, { status: 'enriching' });

  // Enrich with external data
  const enriched = await ctx.call('data-agent.get_customer_info', {
    ticketId
  });

  // Store analysis
  await ctx.memory.set(`ticket_${ticketId}_analysis`, {
    ...analysis,
    enrichedData: enriched,
    analyzedAt: new Date().toISOString()
  });

  // Generate credential for audit trail
  await ctx.did.generateCredential({
    inputData: { ticketId },
    outputData: analysis
  });

  await ctx.workflow.progress(100, { status: 'completed' });

  return {
    ticketId,
    analysis,
    executionId: ctx.executionId
  };
});