design_workflow
Designs multi-step workflows from natural language descriptions with constraints, producing a draft for review and iterative refinement.
Instructions
[WRITE] Start designing a workflow from a natural language description.
Call this when the user describes a complex operation and you need to design a multi-step workflow. Returns a DRAFT workflow with proposed steps for the user to review and edit before execution.
Design flow:
AI calls design_workflow(goal="...") → returns draft with proposed steps
User reviews: "step 3 should use vm_power_off instead" or "add an approval before step 4"
AI calls update_draft(workflow_id, ...) to modify
User confirms: "looks good"
AI calls confirm_draft(workflow_id) → state changes to PENDING
AI calls run_workflow(workflow_id) → execute
The AI should use get_skill_catalog() first to understand available tools, then propose steps based on the user's goal.
Args: goal: Natural language description of what the user wants to accomplish. constraints: Optional constraints (e.g. "must have approval before any destructive step", "use NSX for networking", "target is vcenter-prod").
Returns: dict with workflow_id (state=DRAFT), proposed steps placeholder, and instructions for the AI to fill in steps via update_draft.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| goal | Yes | ||
| constraints | No |