OpenAgentsControl/.opencode/context/development/ai/mastra-ai/concepts/workflows.md

Concept: Mastra Workflows

Purpose: Linear and parallel execution chains for complex AI tasks.

Last Updated: 2026-01-09

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Core Idea

Workflows in Mastra are directed graphs of steps that process data sequentially or in parallel. They provide a structured way to handle multi-stage LLM operations with built-in state management and human-in-the-loop (HITL) support.

Key Points

• Step Definition: Created with createStep, requiring inputSchema, outputSchema, and an execute function.
• Chaining: Steps are linked using .then() for sequential and .parallel() for concurrent execution.
• HITL Support: Steps can suspend execution to wait for human input and resume when data is provided.
• State Access: Each step has access to the global workflow state and the inputData from the previous step.

Quick Example

const workflow = createWorkflow({ id: 'my-workflow', inputSchema, outputSchema })
  .then(step1)
  .parallel([step2a, step2b])
  .then(mergeStep)
  .commit();

const { runId, start } = workflow.createRun();
const result = await start({ inputData: { ... } });

Reference: src/mastra/workflows/ Related:

• concepts/core.md
• examples/workflow-example.md