Creating workflow.ts Files

Overview

This skill documents how to create workflow.ts files for Output SDK workflows. The workflow file contains the main orchestration logic that coordinates step execution.

When to Use This Skill

• Creating a new workflow's main definition
• Understanding workflow structure requirements
• Debugging workflow orchestration issues
• Refactoring existing workflow logic

Critical Rules

1. Import Pattern

// CORRECT - Import from @output.ai/core
import { workflow, z } from '@output.ai/core';

// WRONG - Never import z from zod
import { z } from 'zod';

2. ES Module Imports

All imports MUST use .js extension:

// CORRECT
import { stepName } from './steps.js';
import { WorkflowInputSchema } from './types.js';

// WRONG - Missing .js extension
import { stepName } from './steps';
import { WorkflowInputSchema } from './types';

3. Determinism Requirement

CRITICAL: The workflow fn must be deterministic. No direct I/O operations are allowed in the workflow function.

// WRONG - Direct I/O in workflow
export default workflow({
  // ...
  fn: async (input) => {
    const response = await fetch('https://api.example.com'); // NEVER do this!
    return response.json();
  }
});

// CORRECT - Delegate I/O to steps
export default workflow({
  // ...
  fn: async (input) => {
    const result = await fetchDataStep(input); // Steps handle I/O
    return result;
  }
});

Related Skill: output-error-nondeterminism

Basic Structure

import { workflow, z } from '@output.ai/core';

import { stepOne, stepTwo } from './steps.js';
import { WorkflowInputSchema, WorkflowOutput } from './types.js';

export default workflow({
  name: 'workflowName',
  description: 'Brief description of what the workflow does',
  inputSchema: WorkflowInputSchema,
  outputSchema: z.object({ /* output shape */ }),
  fn: async (input): Promise<WorkflowOutput> => {
    // Orchestrate step calls
    const result = await stepOne(input);
    const final = await stepTwo(result);
    return final;
  }
});

Required Properties

name (string)

Unique identifier for the workflow. Use camelCase.

name: 'contentUtilsImageInfographicNano'

description (string)

Human-readable description of the workflow's purpose.

description: 'Generate high-quality infographic images using AI-powered ideation'

inputSchema (Zod schema)

Schema for validating workflow input. Import from types.ts.

inputSchema: WorkflowInputSchema

Related Skill: output-dev-types-file

outputSchema (Zod schema)

Schema for validating workflow output.

outputSchema: z.object({
  results: z.array(z.string()),
  metadata: z.object({
    processedAt: z.string()
  })
})

fn (async function)

The workflow execution function. Must be deterministic.

fn: async (input): Promise<WorkflowOutput> => {
  // Step orchestration only - no direct I/O
  const result = await processStep(input);
  return result;
}

Complete Example

Based on a real workflow (image_infographic_nano):

import { workflow, z } from '@output.ai/core';

import {
  generateImageIdeas,
  generateImages,
  validateReferenceImages
} from './steps.js';
import {
  WorkflowInput,
  WorkflowInputSchema,
  WorkflowOutput
} from './types.js';
import { normalizeReferenceImageUrls } from './utils.js';

export default workflow({
  name: 'contentUtilsImageInfographicNano',
  description: 'Generate high-quality infographic images using Google Gemini 3 Pro Image model with AI-powered ideation',
  inputSchema: WorkflowInputSchema,
  outputSchema: z.array(z.string()),
  fn: async (rawInput: WorkflowInput): Promise<WorkflowOutput> => {
    // Pre-process input (pure function - OK in workflow)
    const input = {
      ...rawInput,
      referenceImageUrls: normalizeReferenceImageUrls(rawInput.referenceImageUrls)
    };

    // Conditional step execution
    if (input.referenceImageUrls && input.referenceImageUrls.length > 0) {
      await validateReferenceImages({
        referenceImageUrls: input.referenceImageUrls as string[]
      });
    }

    // Sequential step execution
    const ideas = await generateImageIdeas({
      content: input.content,
      numberOfIdeas: input.numberOfIdeas,
      colorPalette: input.colorPalette,
      artDirection: input.artDirection
    });

    // Parallel step execution
    const generations = await Promise.all(
      ideas.map(idea =>
        generateImages({
          input: {
            referenceImageUrls: input.referenceImageUrls,
            aspectRatio: input.aspectRatio,
            resolution: input.resolution,
            numberOfGenerations: input.numberOfGenerations,
            storageNamespace: input.storageNamespace
          },
          prompt: idea
        })
      )
    );

    return generations.flat();
  }
});

Orchestration Patterns

Sequential Execution

Execute steps one after another:

fn: async (input) => {
  const step1Result = await stepOne(input);
  const step2Result = await stepTwo(step1Result);
  const step3Result = await stepThree(step2Result);
  return step3Result;
}

Parallel Execution

Execute independent steps concurrently:

fn: async (input) => {
  const [resultA, resultB, resultC] = await Promise.all([
    stepA(input),
    stepB(input),
    stepC(input)
  ]);
  return { resultA, resultB, resultC };
}

Conditional Execution

Execute steps based on conditions:

fn: async (input) => {
  if (input.includeImages) {
    await processImages(input);
  }

  const result = input.mode === 'fast'
    ? await quickProcess(input)
    : await detailedProcess(input);

  return result;
}

Fan-Out Pattern

Process multiple items in parallel:

fn: async (input) => {
  const results = await Promise.all(
    input.items.map(item => processItem({ item }))
  );
  return { processedItems: results };
}

Pipeline Pattern

Chain multiple transformations:

fn: async (input) => {
  const extracted = await extractData(input);
  const transformed = await transformData(extracted);
  const validated = await validateData(transformed);
  const enriched = await enrichData(validated);
  return enriched;
}

What is Allowed in Workflow fn

Allowed (Deterministic Operations)

• Calling step functions
• Pure data transformations
• Conditional logic based on input
• Array operations (map, filter, reduce)
• Object destructuring and construction
• Promise.all for parallel steps
• Control flow (if/else, loops)

NOT Allowed (Non-Deterministic Operations)

• HTTP requests (use steps)
• Database queries (use steps)
• File system operations (use steps)
• Random number generation
• Current date/time access
• Environment variable access
• Any external service calls

Verification Checklist

• workflow and z imported from @output.ai/core
• All imports use .js extension
• Default export used for the workflow
• name is camelCase and unique
• description clearly explains the workflow
• inputSchema imported from types.ts
• outputSchema matches actual return type
• fn is deterministic (no direct I/O)
• All I/O delegated to step functions

Related Skills

• output-dev-step-function - Creating step functions that handle I/O
• output-dev-types-file - Defining input/output schemas
• output-dev-folder-structure - Where workflow.ts belongs
• output-error-nondeterminism - Fixing determinism violations
• output-error-zod-import - Fixing schema import issues