TypeScript API Reference

Build type-safe ensembles with full IDE support, autocomplete, and compile-time validation.

Why TypeScript?

TypeScript ensembles offer several advantages over YAML:

Type Safety: Catch configuration errors at compile time
IDE Support: Full autocomplete, inline documentation, and refactoring
Dynamic Logic: Build steps conditionally using code
Reusability: Share and compose steps across multiple ensembles
Testing: Easier unit testing of ensemble configurations

Quick Start

import { createEnsemble, step } from '@anthropic/conductor'

const myWorkflow = createEnsemble('my-workflow')
  .setDescription('A simple greeting workflow')
  .addStep(
    step('greeter')
      .agent('greeter')
      .input({ name: '${input.name}' })
  )
  .build()

export default myWorkflow

createEnsemble

Create a new ensemble with the fluent builder API.

import { createEnsemble } from '@anthropic/conductor'

const ensemble = createEnsemble('ensemble-name')

Methods

`.setDescription(description: string)`

Set a description for the ensemble.

createEnsemble('my-workflow')
  .setDescription('Processes customer orders and sends confirmations')

`.setInput<T>()`

Define the input type for the ensemble (TypeScript generics for type safety).

interface WorkflowInput {
  customerId: string
  orderItems: string[]
}

createEnsemble('order-processor')
  .setInput<WorkflowInput>()

`.setOutput<T>()`

Define the output type for the ensemble.

interface WorkflowOutput {
  orderId: string
  status: 'completed' | 'failed'
  total: number
}

createEnsemble('order-processor')
  .setOutput<WorkflowOutput>()

`.addStep(step: Step)`

Add a step to the ensemble. Steps execute sequentially by default, but steps without dependencies run in parallel.

createEnsemble('my-workflow')
  .addStep(step('fetch').agent('fetcher').input({ url: '${input.url}' }))
  .addStep(step('process').agent('processor').input({ data: '${fetch.output}' }))

`.addSteps(...steps: Step[])`

Add multiple steps at once.

createEnsemble('my-workflow')
  .addSteps(
    step('step1').agent('agent1'),
    step('step2').agent('agent2'),
    step('step3').agent('agent3')
  )

`.build()`

Finalize and return the ensemble configuration.

const ensemble = createEnsemble('my-workflow')
  .addStep(step('greeter').agent('greeter'))
  .build()

export default ensemble

step

Create an individual step within an ensemble.

import { step } from '@anthropic/conductor'

step('step-name')
  .agent('agent-name')
  .input({ key: 'value' })

Methods

`.agent(name: string)`

Reference an agent by name.

step('enrich')
  .agent('company-enricher')

`.operation(type: string)`

Use an inline operation instead of an agent.

step('analyze')
  .operation('think')
  .config({
    provider: 'openai',
    model: 'gpt-4o',
    prompt: 'Analyze: ${input.text}'
  })

`.input(inputs: Record<string, any>)`

Provide inputs to the step. Supports expression syntax like ${input.field} and ${previousStep.output}.

step('process')
  .agent('processor')
  .input({
    data: '${fetch.output}',
    userId: '${input.userId}',
    timestamp: '${Date.now()}'
  })

`.config(config: Record<string, any>)`

Provide configuration for an operation.

step('generate')
  .operation('think')
  .config({
    provider: 'anthropic',
    model: 'claude-3-5-sonnet-20241022',
    temperature: 0.7,
    maxTokens: 1000,
    prompt: '${input.prompt}'
  })

`.condition(expression: string)`

Conditionally execute the step.

step('send-premium-email')
  .agent('email-sender')
  .condition('${input.isPremiumUser === true}')

`.retry(options: RetryOptions)`

Configure retry behavior for the step.

step('api-call')
  .agent('fetcher')
  .retry({
    maxAttempts: 3,
    backoff: 'exponential',
    initialDelay: 1000,
    maxDelay: 30000
  })

`.cache(options: CacheOptions)`

Configure caching for the step.

step('expensive-analysis')
  .agent('analyzer')
  .cache({
    ttl: 3600,
    key: 'analysis-${input.documentId}'
  })

`.timeout(ms: number)`

Set a timeout for the step.

step('slow-operation')
  .agent('processor')
  .timeout(30000)

Flow Control Primitives

TypeScript ensembles support advanced flow control patterns through specialized primitives.

parallel

Execute multiple steps concurrently.

import { createEnsemble, step, parallel } from '@anthropic/conductor'

createEnsemble('multi-fetch')
  .addStep(
    parallel('fetch-all')
      .steps(
        step('fetch-a').agent('fetcher').input({ url: 'https://api-a.com' }),
        step('fetch-b').agent('fetcher').input({ url: 'https://api-b.com' }),
        step('fetch-c').agent('fetcher').input({ url: 'https://api-c.com' })
      )
  )
  .addStep(
    step('merge')
      .operation('code')
      .config({ script: 'scripts/merge-results' })
      .input({
        a: '${fetch-a.output}',
        b: '${fetch-b.output}',
        c: '${fetch-c.output}'
      })
  )

branch

Conditional branching based on a condition.

import { createEnsemble, step, branch } from '@anthropic/conductor'

createEnsemble('conditional-workflow')
  .addStep(
    step('classify')
      .operation('think')
      .config({ prompt: 'Classify priority: ${input.text}' })
  )
  .addStep(
    branch('route-by-priority')
      .condition('${classify.output === "urgent"}')
      .then(
        step('urgent-handler').agent('urgent-processor')
      )
      .else(
        step('normal-handler').agent('normal-processor')
      )
  )

foreach

Iterate over an array, executing a step for each item.

import { createEnsemble, step, foreach } from '@anthropic/conductor'

createEnsemble('batch-processor')
  .addStep(
    foreach('process-items')
      .items('${input.items}')
      .as('item')
      .step(
        step('process')
          .agent('item-processor')
          .input({ item: '${item}' })
      )
  )

Options

foreach('process-items')
  .items('${input.items}')
  .as('item')
  .index('idx')                    // Optional: variable name for index
  .concurrency(5)                  // Optional: max parallel executions
  .step(...)

tryStep

Error handling with try/catch semantics.

import { createEnsemble, step, tryStep } from '@anthropic/conductor'

createEnsemble('resilient-workflow')
  .addStep(
    tryStep('safe-fetch')
      .try(
        step('fetch').agent('fetcher').input({ url: '${input.url}' })
      )
      .catch(
        step('fallback').agent('cache-reader').input({ key: '${input.cacheKey}' })
      )
  )

switchStep

Multi-way branching based on a value.

import { createEnsemble, step, switchStep } from '@anthropic/conductor'

createEnsemble('router')
  .addStep(
    switchStep('route-by-type')
      .value('${input.type}')
      .case('email', step('email-handler').agent('email-processor'))
      .case('sms', step('sms-handler').agent('sms-processor'))
      .case('push', step('push-handler').agent('push-processor'))
      .default(step('default-handler').agent('generic-processor'))
  )

whileStep

Loop while a condition is true.

import { createEnsemble, step, whileStep } from '@anthropic/conductor'

createEnsemble('polling-workflow')
  .addStep(
    whileStep('poll-until-ready')
      .condition('${!status.ready}')
      .maxIterations(10)
      .step(
        step('check-status')
          .agent('status-checker')
          .input({ jobId: '${input.jobId}' })
      )
  )

mapReduce

Process items in parallel (map) then aggregate results (reduce).

import { createEnsemble, step, mapReduce } from '@anthropic/conductor'

createEnsemble('analyze-documents')
  .addStep(
    mapReduce('analyze-all')
      .items('${input.documents}')
      .map(
        step('analyze')
          .agent('document-analyzer')
          .input({ doc: '${item}' })
      )
      .reduce(
        step('aggregate')
          .agent('result-aggregator')
          .input({ results: '${mapResults}' })
      )
  )

Version Primitives (Edgit Integration)

Version primitives enable referencing components managed by Edgit with precise version pinning. This is essential for production workflows requiring reproducible deployments.

componentRef

Create a versioned reference to any component type.

import { componentRef } from '@anthropic/conductor'

// Exact version
const analyzer = componentRef('agent', 'analyzers/sentiment', '1.0.0')

// Compatible version constraint (semver ^)
const processor = componentRef('agent', 'processors/text', '^2.0.0', {
  fallback: '1.9.0',
  resolution: 'compatible'
})

// Latest version
const tool = componentRef('tool', 'search/web', 'latest')

Options

interface ComponentRefOptions {
  fallback?: string         // Fallback version if primary unavailable
  required?: boolean        // Fail if not found (default: true)
  resolution?: 'exact' | 'compatible' | 'latest-matching'
}

versionedAgent

Create a versioned agent reference for use in ensemble steps.

import { versionedAgent, createEnsemble } from '@anthropic/conductor'

// Simple versioned agent
const analyzer = versionedAgent('analyzers/sentiment', '1.0.0')

// With config override
const customAnalyzer = versionedAgent('analyzers/sentiment', '^1.0.0', {
  config: {
    model: 'claude-sonnet-4',
    temperature: 0.5
  },
  input: {
    text: '${input.content}'
  }
})

// Use in ensemble
const pipeline = createEnsemble({
  name: 'analysis-pipeline',
  steps: [
    versionedAgent('preprocessor', '2.1.0').toFlowStep(),
    versionedAgent('analyzer', '^1.0.0').toFlowStep(),
    versionedAgent('formatter', '1.0.0').toFlowStep()
  ]
})

Batch Creation

import { versionedAgents, createEnsemble } from '@anthropic/conductor'

// Define multiple versioned agents at once
const agents = versionedAgents({
  preprocessor: '2.1.0',
  analyzer: '^1.0.0',
  formatter: '~1.2.0',
  // With options
  scorer: {
    version: '^3.0.0',
    options: {
      config: { threshold: 0.8 }
    }
  }
})

// Use in ensemble
const pipeline = createEnsemble({
  name: 'scoring-pipeline',
  steps: [
    agents.preprocessor.toFlowStep(),
    agents.analyzer.toFlowStep(),
    agents.scorer.toFlowStep()
  ]
})

versionedEnsemble

Reference and compose versioned sub-ensembles.

import { versionedEnsemble, createEnsemble, step } from '@anthropic/conductor'

// Reference a versioned sub-ensemble
const analysisPipeline = versionedEnsemble('pipelines/analysis', '^2.0.0', {
  input: { data: '${preprocess.output}' },
  inheritState: true
})

// Compose in a parent ensemble
const mainPipeline = createEnsemble({
  name: 'main-pipeline',
  steps: [
    step('preprocess'),
    // Invoke the versioned sub-ensemble
    { ...analysisPipeline.toInvocation() },
    step('postprocess')
  ]
})

deploymentRef

Reference components by deployment environment rather than explicit version.

import { deploymentRef, componentRef, versionedAgent } from '@anthropic/conductor'

// Reference production deployment
const prodAnalyzer = deploymentRef(
  componentRef('agent', 'analyzers/sentiment', 'latest'),
  'production'
)

// Reference staging with production fallback
const stagingPipeline = deploymentRef(
  versionedAgent('analyzers/sentiment', 'latest'),
  'staging',
  { fallback: 'production' }
)

// Dynamic environment
const dynamicRef = deploymentRef(
  versionedAgent('processor', 'latest'),
  process.env.DEPLOYMENT_ENV || 'development'
)

Version Constraints

Support for semver-style version constraints:

Constraint	Meaning	Example
`1.2.3`	Exact version	Only v1.2.3
`^1.2.0`	Compatible (same major)	v1.2.0, v1.3.0, v1.9.9
`~1.2.0`	Patch-compatible (same minor)	v1.2.0, v1.2.1, v1.2.9
`>=1.0.0`	Minimum version	v1.0.0 and above
`<=2.0.0`	Maximum version	v2.0.0 and below
`latest`	Latest available	Most recent version
`stable`	Latest stable	Most recent non-prerelease

Utility Functions

import { parseVersion, satisfiesVersion } from '@anthropic/conductor'

// Parse version strings
parseVersion('1.2.3')      // { major: 1, minor: 2, patch: 3 }
parseVersion('^1.2.0')     // { constraint: '^', major: 1, minor: 2, patch: 0 }
parseVersion('latest')     // { tag: 'latest' }

// Check version compatibility
satisfiesVersion('1.2.3', '^1.0.0')   // true
satisfiesVersion('2.0.0', '^1.0.0')   // false
satisfiesVersion('1.2.5', '~1.2.0')   // true

Integration with Edgit

Version primitives integrate directly with Edgit’s Git tag namespaces:

const analyzer = versionedAgent('sentiment-analyzer', '1.0.0')

// Convert to Edgit Git tag format
console.log(analyzer.toGitTag())
// Output: agents/sentiment-analyzer/v1.0.0

const pipeline = versionedEnsemble('data-pipeline', '2.0.0')
console.log(pipeline.toGitTag())
// Output: ensembles/data-pipeline/v2.0.0

Type-Specific Namespaces

Both Edgit (Git tags) and Conductor (KV storage) use type-specific namespaces:

Component Type	Git Tag Namespace	KV Key Prefix
`prompt`	`prompts/`	`prompts:`
`schema`	`schemas/`	`schemas:`
`config`	`configs/`	`configs:`
`script`	`scripts/`	`scripts:`
`query`	`queries/`	`queries:`
`template`	`templates/`	`templates:`
`tool`	`tools/`	`tools:`
`agent`	`agents/`	`agents:`
`ensemble`	`ensembles/`	`ensembles:`

This alignment ensures Git tags created by Edgit map directly to KV keys used by Conductor at runtime.

Complete Example

Here’s a complete TypeScript ensemble that demonstrates multiple features:

// ensembles/customer-intelligence.ts
import {
  createEnsemble,
  step,
  parallel,
  branch,
  tryStep
} from '@anthropic/conductor'

interface CustomerInput {
  customerId: string
  includeHistory: boolean
}

interface CustomerOutput {
  profile: Record<string, unknown>
  sentiment: string
  recommendations: string[]
}

const customerIntelligence = createEnsemble('customer-intelligence')
  .setDescription('Gather and analyze customer data from multiple sources')
  .setInput<CustomerInput>()
  .setOutput<CustomerOutput>()

  // Parallel data fetching
  .addStep(
    parallel('fetch-data')
      .steps(
        step('fetch-profile')
          .agent('crm-connector')
          .input({ customerId: '${input.customerId}' }),
        step('fetch-transactions')
          .agent('transaction-fetcher')
          .input({ customerId: '${input.customerId}' }),
        step('fetch-support-tickets')
          .agent('support-connector')
          .input({ customerId: '${input.customerId}' })
      )
  )

  // Conditional history fetch
  .addStep(
    branch('check-history')
      .condition('${input.includeHistory}')
      .then(
        step('fetch-history')
          .agent('history-fetcher')
          .input({ customerId: '${input.customerId}' })
      )
  )

  // AI analysis with fallback
  .addStep(
    tryStep('analyze')
      .try(
        step('ai-analysis')
          .operation('think')
          .config({
            provider: 'anthropic',
            model: 'claude-3-5-sonnet-20241022',
            prompt: `
              Analyze this customer:
              Profile: \${fetch-profile.output}
              Transactions: \${fetch-transactions.output}
              Support: \${fetch-support-tickets.output}

              Provide: sentiment, key insights, recommendations
            `
          })
      )
      .catch(
        step('basic-analysis')
          .operation('think')
          .config({
            provider: 'openai',
            model: 'gpt-4o-mini',
            prompt: 'Provide basic analysis for customer: ${fetch-profile.output}'
          })
      )
  )

  .build()

export default customerIntelligence

Expression Syntax

TypeScript ensembles support the same expression syntax as YAML:

Variable Access

'${input.fieldName}'              // Input variable
'${env.API_KEY}'                  // Environment variable
'${state.counter}'                // State variable
'${stepName.output}'              // Step output
'${stepName.output.nested.field}' // Nested output

Array Indexing

'${input.items[0]}'               // First array element
'${input.users[0].name}'          // Property of first element
'${data.results[1].meta.id}'      // Deep nested access

Nullish Coalescing (??)

Returns the first value that is not null or undefined:

'${input.name ?? "default"}'      // Use "default" if null/undefined
'${input.query.name ?? input.body.name ?? "Guest"}'  // Chain fallbacks
'${input.count ?? 0}'             // Preserves 0 (unlike ||)

Falsy Coalescing (||)

Returns the first truthy value (catches "", 0, false, null, undefined):

'${input.name || "default"}'      // Use "default" if empty/falsy
'${input.count || 10}'            // Use 10 if count is 0
'${input.a || input.b || "fallback"}'  // Chain values

Ternary Conditionals (?:)

'${input.enabled ? "yes" : "no"}'       // Returns "yes" if truthy
'${input.premium ? 100 : 10}'           // Numeric conditional
'${input.type ? input.type : "default"}' // Path in branches

Boolean Negation (!)

'${!input.disabled}'              // true if disabled is falsy
'${!stepName.executed}'           // true if step didn't run

Conditionals

'${input.value > 10}'
'${stepName.success}'
'${stepName.failed}'
'${!stepName.executed}'
'${input.type === "premium"}'
'${input.age >= 18 && input.verified}'

Filter Chains

'${input.text | uppercase}'       // Apply uppercase filter
'${input.text | split(" ") | first}'  // Chain filters
'${input.items | length}'         // Array/string length

Functions

'${Date.now()}'
'${JSON.stringify(object)}'
'${array.length}'
'${array.map(item => item.id)}'
'${string.toUpperCase()}'

AgentExecutionContext

When writing TypeScript handlers for agents, you receive a rich execution context with access to all project resources.

interface AgentExecutionContext {
  input: Record<string, unknown>  // Input from ensemble
  env: Env                        // Cloudflare Workers env
  request?: Request               // Original HTTP request (if triggered by HTTP)

  // Component registries
  schemas: {
    get(name: string): Schema | undefined
    validate(name: string, data: unknown): ValidationResult
    isValid(name: string, data: unknown): boolean
  }

  prompts: {
    get(name: string): Prompt | undefined
    render(name: string, vars: Record<string, unknown>): string
  }

  configs: {
    get(name: string): unknown
  }

  queries: {
    getSql(name: string): string
  }

  scripts: {
    get(name: string): Function
  }

  templates: {
    render(name: string, vars: Record<string, unknown>): string
  }

  // Discovery registries
  agentRegistry: {
    list(): AgentMetadata[]
    get(name: string): AgentDefinition | undefined
  }

  ensembleRegistry: {
    list(): EnsembleMetadata[]
    get(name: string): EnsembleDefinition | undefined
  }

  // Project config
  config: ConductorConfig
}

Using AgentExecutionContext

// agents/my-agent/handler.ts
import type { AgentExecutionContext } from '@ensemble-edge/conductor'

export default async function handler(ctx: AgentExecutionContext) {
  // Access input from ensemble
  const { userId, action } = ctx.input

  // Validate with shared schema
  const isValid = ctx.schemas.isValid('user-request', ctx.input)
  if (!isValid) {
    throw new Error('Invalid input')
  }

  // Render prompt with variables
  const prompt = ctx.prompts.render('analyze-user', {
    userId,
    context: 'detailed analysis'
  })

  // Get shared configuration
  const apiConfig = ctx.configs.get('api-settings')

  // Access SQL query template
  const query = ctx.queries.getSql('user-lookup')

  // Access environment variables
  const apiKey = ctx.env.API_KEY

  // Access project config
  const projectName = ctx.config.name

  // Discover available agents
  const agents = ctx.agentRegistry.list()

  return {
    result: 'success',
    data: { /* ... */ }
  }
}

Component Registries

Component registries provide access to versioned, reusable project resources:

// Schemas - validation and type checking
const schema = ctx.schemas.get('user-profile')
const validation = ctx.schemas.validate('order', orderData)
if (!validation.valid) {
  console.error(validation.errors)
}

// Prompts - templated AI instructions
const prompt = ctx.prompts.get('sentiment-analyzer')
const rendered = ctx.prompts.render('sentiment-analyzer', {
  text: userInput,
  language: 'en'
})

// Configs - shared configuration
const settings = ctx.configs.get('app-settings')

// Queries - SQL templates
const sqlQuery = ctx.queries.getSql('analytics-report')

// Scripts - shared JavaScript/TypeScript modules
const utilFunction = ctx.scripts.get('data-transformer')

// Templates - HTML/text templates
const html = ctx.templates.render('email-template', {
  userName: 'Alice',
  message: 'Welcome!'
})

Discovery Registries

Discovery registries enable runtime introspection of available agents and ensembles:

// List all available agents
const allAgents = ctx.agentRegistry.list()
console.log(allAgents.map(a => a.name))

// Get specific agent definition
const enricher = ctx.agentRegistry.get('company-enricher')
if (enricher) {
  console.log(enricher.description)
  console.log(enricher.inputs)
}

// List all ensembles
const ensembles = ctx.ensembleRegistry.list()

// Get specific ensemble
const workflow = ctx.ensembleRegistry.get('user-onboarding')

Project Configuration Access

Access the full project configuration from any agent:

// Project metadata
const projectName = ctx.config.name
const version = ctx.config.version

// Documentation settings
const docsUI = ctx.config.docs?.ui
const docsCache = ctx.config.docs?.cache

// Observability settings
const loggingLevel = ctx.config.observability?.logging

Type Definitions

EnsembleDefinition

interface EnsembleDefinition {
  name: string
  description?: string
  apiExecutable?: boolean        // Control Execute API access (default: true)
  trigger?: TriggerConfig[]
  inputs?: Record<string, InputDefinition>
  state?: StateConfig
  agents: AgentStep[]
  output?: OutputConfig
}

AgentDefinition

interface AgentDefinition {
  name: string
  description?: string
  apiExecutable?: boolean        // Control Execute API access (default: true)
  inputs?: Record<string, InputDefinition>
  operations: OperationConfig[]
  outputs?: Record<string, string>
}

OutputConfig

interface OutputConfig {
  status?: number
  headers?: Record<string, string>
  format?: OutputFormat | FormatType
  body?: Record<string, unknown>
}

OutputFormat

type FormatType =
  | 'json'      // application/json
  | 'text'      // text/plain
  | 'html'      // text/html
  | 'xml'       // application/xml
  | 'csv'       // text/csv
  | 'markdown'  // text/markdown
  | 'yaml'      // application/x-yaml
  | 'ics'       // text/calendar
  | 'rss'       // application/rss+xml
  | 'atom'      // application/atom+xml

interface OutputFormat {
  type: FormatType
  extract?: string               // Field to extract from body for serialization
}

ApiConfig

Project-level configuration for Execute API access control.

interface ApiConfig {
  execution?: {
    agents?: {
      requireExplicit?: boolean  // When true, agents must have apiExecutable: true
    }
    ensembles?: {
      requireExplicit?: boolean  // When true, ensembles must have apiExecutable: true
    }
  }
}

RetryOptions

interface RetryOptions {
  maxAttempts?: number           // Default: 3
  backoff?: 'exponential' | 'linear'  // Default: 'exponential'
  initialDelay?: number          // Default: 1000 (ms)
  maxDelay?: number              // Default: 30000 (ms)
  retryOn?: number[]             // HTTP status codes to retry
}

CacheOptions

interface CacheOptions {
  ttl: number                    // Time to live in seconds
  key: string                    // Cache key (supports expressions)
}

Step

interface Step {
  name: string
  agent?: string
  operation?: string
  input?: Record<string, unknown>
  config?: Record<string, unknown>
  condition?: string
  retry?: RetryOptions
  cache?: CacheOptions
  timeout?: number
}

Migration from YAML

Converting a YAML ensemble to TypeScript:

YAML
TypeScript

ensemble: greet-user

agents:
  - name: greeter
    agent: greeter
    inputs:
      name: ${input.name}
      style: ${input.style}

  - name: formatter
    operation: code
    config:
      script: scripts/format-greeting
    input:
      greeting: ${greeter.output}

output:
  message: ${formatter.output}

import { createEnsemble, step } from '@anthropic/conductor'

const greetUser = createEnsemble('greet-user')
  .addStep(
    step('greeter')
      .agent('greeter')
      .input({
        name: '${input.name}',
        style: '${input.style}'
      })
  )
  .addStep(
    step('formatter')
      .operation('code')
      .config({ script: 'scripts/format-greeting' })
      .input({ greeting: '${greeter.output}' })
  )
  .build()

export default greetUser

Best Practices

Export as default - Always export your ensemble as the default export
Use TypeScript generics - Define input/output types for better type safety
Organize by domain - Keep related ensembles in the same directory
Reuse steps - Extract common patterns into shared step factories
Validate early - Use ensemble conductor validate to check TypeScript ensembles

Next Steps

Your First Ensemble

Build your first ensemble

YAML Schema

YAML configuration reference

CLI Commands

Command line reference

Flow Control

Advanced flow patterns

​TypeScript API Reference

​Why TypeScript?

​Quick Start

​createEnsemble

​Methods

​.setDescription(description: string)

​.setInput<T>()

​.setOutput<T>()

​.addStep(step: Step)

​.addSteps(...steps: Step[])

​.build()

​step

​Methods

​.agent(name: string)

​.operation(type: string)

​.input(inputs: Record<string, any>)

​.config(config: Record<string, any>)

​.condition(expression: string)

​.retry(options: RetryOptions)

​.cache(options: CacheOptions)

​.timeout(ms: number)

​Flow Control Primitives

​parallel

​branch

​foreach

​Options

​tryStep

​switchStep

​whileStep

​mapReduce

​Version Primitives (Edgit Integration)

​componentRef

​Options

​versionedAgent

​Batch Creation

​versionedEnsemble

​deploymentRef

​Version Constraints

​Utility Functions

​Integration with Edgit

​Type-Specific Namespaces

​Complete Example

​Expression Syntax

​Variable Access

​Array Indexing

​Nullish Coalescing (??)

​Falsy Coalescing (||)

​Ternary Conditionals (?:)

​Boolean Negation (!)

​Conditionals

​Filter Chains

​Functions

​AgentExecutionContext

​Using AgentExecutionContext

​Component Registries

​Discovery Registries

​Project Configuration Access

​Type Definitions

​EnsembleDefinition

​AgentDefinition

​OutputConfig

​OutputFormat

​ApiConfig

​RetryOptions

​CacheOptions

​Step

​Migration from YAML

​Best Practices

​Next Steps

Your First Ensemble

YAML Schema

CLI Commands

Flow Control

TypeScript API Reference

Why TypeScript?

Quick Start

createEnsemble

Methods

`.setDescription(description: string)`

`.setInput<T>()`

`.setOutput<T>()`

`.addStep(step: Step)`

`.addSteps(...steps: Step[])`

`.build()`

step

Methods

`.agent(name: string)`

`.operation(type: string)`

`.input(inputs: Record<string, any>)`

`.config(config: Record<string, any>)`

`.condition(expression: string)`

`.retry(options: RetryOptions)`

`.cache(options: CacheOptions)`

`.timeout(ms: number)`

Flow Control Primitives

parallel

branch

foreach

Options

tryStep

switchStep

whileStep

mapReduce

Version Primitives (Edgit Integration)

componentRef

Options

versionedAgent

Batch Creation

versionedEnsemble

deploymentRef

Version Constraints

Utility Functions

Integration with Edgit

Type-Specific Namespaces

Complete Example

Expression Syntax

Variable Access

Array Indexing

Nullish Coalescing (??)

Falsy Coalescing (||)

Ternary Conditionals (?:)

Boolean Negation (!)

Conditionals

Filter Chains

Functions

AgentExecutionContext

Using AgentExecutionContext

Component Registries

Discovery Registries

Project Configuration Access

Type Definitions

EnsembleDefinition

AgentDefinition

OutputConfig

OutputFormat

ApiConfig

RetryOptions

CacheOptions

Step

Migration from YAML

Best Practices

Next Steps