interface AgentEvent {
  id: string                    // ULID
  agent_did: string
  session_id: string
  event_type: EventType
  outcome: 'success' | 'error' | 'timeout' | 'skipped'
  timestamp: string             // ISO-8601
  duration_ms?: number
  
  // Trace correlation
  trace_id?: string
  parent_span_id?: string
  span_id: string
  
  // Flexible context
  context: Record<string, unknown>
  
  // Decision reasoning
  reasoning?: {
    decision: string
    rationale: string
    alternatives?: string[]
    confidence?: number
  }
  
  // Error details
  error?: {
    code: string
    message: string
    stack?: string
    retryable: boolean
  }
}

import { ulid } from 'ulid'

class EventEmitter {
  constructor(
    private db: D1Database,
    private agentDid: string,
    private sessionId: string
  ) {}
  
  async emit(event: Omit<AgentEvent, 'id' | 'agent_did' | 'session_id' | 'timestamp'>): Promise<string> {
    const id = ulid()
    
    await this.db.prepare(`
      INSERT INTO events (id, agent_did, session_id, event_type, outcome, timestamp, duration_ms, trace_id, span_id, parent_span_id, context, reasoning, error)
      VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
    `).bind(
      id,
      this.agentDid,
      this.sessionId,
      event.event_type,
      event.outcome,
      new Date().toISOString(),
      event.duration_ms,
      event.trace_id,
      event.span_id,
      event.parent_span_id,
      JSON.stringify(event.context),
      event.reasoning ? JSON.stringify(event.reasoning) : null,
      event.error ? JSON.stringify(event.error) : null
    ).run()
    
    return id
  }
  
  // Convenience methods
  async toolCall(name: string, params: unknown, result: unknown, durationMs: number): Promise<string> {
    return this.emit({
      event_type: 'agent.tool_call',
      outcome: 'success',
      duration_ms: durationMs,
      span_id: ulid(),
      context: { tool_name: name, params, result_summary: summarize(result) }
    })
  }
  
  async decision(type: string, decision: string, rationale: string, alternatives?: string[]): Promise<string> {
    return this.emit({
      event_type: 'decision',
      outcome: 'success',
      span_id: ulid(),
      context: { decision_type: type },
      reasoning: { decision, rationale, alternatives, confidence: 0.9 }
    })
  }
}

# Recent logs (JSON output)
zap logs

# Human-friendly
zap logs --pretty

# Filter by time
zap logs --since 5m
zap logs --since 2h
zap logs --since "2025-01-01"

# Filter by type
zap logs --type tool_call
zap logs --type decision,memory.store

# Filter by outcome
zap logs --outcome error

# Watch mode (tail)
zap logs --watch
zap logs --watch --type error

# Complex filters (jq-style)
zap logs --filter '.duration_ms > 1000'
zap logs --filter '.context.tool_name == "remember"'

# Built-in presets
zap query --preset slow_tools
zap query --preset error_rate
zap query --preset decision_confidence
zap query --preset memory_hotspots

# Custom SQL
zap query --sql "SELECT event_type, COUNT(*) FROM events GROUP BY event_type"

# Output formats
zap query --preset error_rate --format json
zap query --preset error_rate --format csv

# View reasoning for event
zap trace <event-id>

# Find low-confidence decisions
zap traces --confidence-lt 0.5

# Replay decision sequence
zap replay --session sess-123 --type decision

# Health check
zap doctor

# Storage usage
zap storage

# Index health
zap indexes

const PRESETS = {
  slow_tools: `
    SELECT 
      context->>'tool_name' as tool,
      COUNT(*) as calls,
      AVG(duration_ms) as avg_ms,
      MAX(duration_ms) as max_ms
    FROM events
    WHERE event_type = 'agent.tool_call'
    GROUP BY context->>'tool_name'
    HAVING AVG(duration_ms) > 100
    ORDER BY avg_ms DESC
  `,
  
  error_rate: `
    SELECT 
      event_type,
      COUNT(*) as total,
      SUM(CASE WHEN outcome = 'error' THEN 1 ELSE 0 END) as errors,
      ROUND(100.0 * SUM(CASE WHEN outcome = 'error' THEN 1 ELSE 0 END) / COUNT(*), 2) as error_pct
    FROM events
    GROUP BY event_type
    ORDER BY error_pct DESC
  `,
  
  decision_confidence: `
    SELECT 
      context->>'decision_type' as type,
      reasoning->>'decision' as decision,
      reasoning->>'confidence' as confidence,
      reasoning->>'rationale' as rationale
    FROM events
    WHERE event_type = 'decision'
    AND CAST(reasoning->>'confidence' AS REAL) < 0.7
    ORDER BY confidence ASC
    LIMIT 20
  `,
  
  memory_hotspots: `
    SELECT 
      context->>'collection' as collection,
      COUNT(*) as accesses,
      COUNT(DISTINCT session_id) as sessions
    FROM events
    WHERE event_type IN ('memory.store', 'memory.search')
    GROUP BY context->>'collection'
    ORDER BY accesses DESC
  `
}

async function compactEvents(db: D1Database): Promise<void> {
  const now = Date.now()
  const oneDay = 24 * 60 * 60 * 1000
  const sevenDays = 7 * oneDay
  const thirtyDays = 30 * oneDay
  
  // 7-30 days: aggregate to hourly buckets
  await db.prepare(`
    INSERT INTO events_hourly (hour, agent_did, event_type, count, avg_duration, error_count)
    SELECT 
      strftime('%Y-%m-%d %H:00:00', timestamp) as hour,
      agent_did,
      event_type,
      COUNT(*),
      AVG(duration_ms),
      SUM(CASE WHEN outcome = 'error' THEN 1 ELSE 0 END)
    FROM events
    WHERE timestamp < datetime('now', '-7 days')
    AND timestamp >= datetime('now', '-30 days')
    GROUP BY hour, agent_did, event_type
    ON CONFLICT DO NOTHING
  `).run()
  
  // Delete raw events older than 7 days
  await db.prepare(`
    DELETE FROM events
    WHERE timestamp < datetime('now', '-7 days')
  `).run()
  
  // Delete hourly aggregates older than 30 days
  await db.prepare(`
    DELETE FROM events_hourly
    WHERE hour < datetime('now', '-30 days')
  `).run()
}

#!/usr/bin/env bun

import { Command } from 'commander'

const program = new Command()
  .name('zap')
  .description('Agent observability CLI')
  .version('1.0.0')

program
  .command('logs')
  .description('View agent logs')
  .option('--since <time>', 'Show logs since time (e.g., 5m, 2h)')
  .option('--type <types>', 'Filter by event type (comma-separated)')
  .option('--outcome <outcome>', 'Filter by outcome')
  .option('--filter <expr>', 'jq-style filter expression')
  .option('--watch', 'Watch mode (tail)')
  .option('--pretty', 'Human-friendly output')
  .option('--limit <n>', 'Max results', '50')
  .action(async (options) => {
    // Implementation
  })

program
  .command('query')
  .description('Run SQL analytics')
  .option('--preset <name>', 'Use preset query')
  .option('--sql <query>', 'Custom SQL query')
  .option('--format <fmt>', 'Output format (json, csv, table)', 'json')
  .action(async (options) => {
    // Implementation
  })

program
  .command('trace <event-id>')
  .description('View decision trace')
  .action(async (eventId) => {
    // Implementation
  })

program
  .command('doctor')
  .description('Health check')
  .action(async () => {
    // Implementation
  })

program.parse()