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create_workflow

Define and create a custom workflow from your step list, with optional approval gates, when no built-in template fits your process.

Instructions

[WRITE] Create a custom workflow dynamically from a step list.

Use this when you already know the steps and no built-in template matches; prefer plan_workflow when one does, and design_workflow when the user gave a goal rather than steps. Call get_skill_catalog first for the skill and tool names a step may target.

Each step dict must have: action, skill, tool, params. Optional: rollback_tool, rollback_params. action="require_approval" inserts a human approval gate — run_workflow refuses ungated destructive steps.

Args: name: Workflow name (used as workflow_type). description: Human-readable description. steps: List of step dicts, each with action/skill/tool/params. save_as_template: If True, save as YAML to ~/.vmware/workflows/ for reuse.

Returns: dict with workflow_id and plan summary. Next call review_workflow to check the plan, then run_workflow to execute; rollback undoes it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
stepsYes
descriptionYes
save_as_templateNo
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description discloses key behavioral traits beyond annotations: the [WRITE] prefix, dynamic creation from steps, the requirement for approval for destructive steps, and the side effect of saving a YAML file when save_as_template is true. Annotations are consistent (readOnlyHint=false), so no contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured and front-loaded with the primary purpose. It uses clear sections for usage, step requirements, args, and returns, with each sentence earning its place. No filler or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description is complete for a complex tool with no output schema and low schema coverage. It covers prerequisites (get_skill_catalog), step structure, approval gates, side effects, and the full follow-up flow (review_workflow, run_workflow, rollback). No gaps remain.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Despite 0% schema description coverage, the description fully documents each parameter: name (used as workflow_type), description, steps (with required sub-fields action/skill/tool/params and optional rollback fields), and save_as_template (with file path). This adds critical meaning beyond the bare schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description immediately states a specific verb+resource: 'Create a custom workflow dynamically from a step list.' It clearly distinguishes this from siblings by naming plan_workflow and design_workflow as alternatives with different applicability criteria.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit usage guidance is provided: use when you already know the steps and no built-in template matches; prefer plan_workflow when a template matches; prefer design_workflow when the user gave a goal. It also instructs calling get_skill_catalog first for skill and tool names.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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