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Python
Remote

list_workflows

Read-onlyIdempotent

Discover available workflow templates to check if an existing one matches your goal, then choose to plan or create a new workflow. Also retrieve active workflow run IDs for status tracking.

Instructions

[READ] List all available workflow templates (built-in + custom).

Use this first to see whether a template already covers the goal, then pass its name to plan_workflow; if none fit, use create_workflow instead. Built-in templates are always available. Custom templates are loaded from ~/.vmware/workflows/*.yaml — drop a YAML file there to add your own workflows.

Returns: dict with builtin and custom workflow lists, each with name, description, steps count, plus active_workflows — the IDs of in-flight runs to pass to get_workflow_status.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.11.1
    • addedInput schema / additionalProperties
      Added value: +false
  2. First observedv1.5.22

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already cover readOnly, idempotent, and non-destructive traits. The description adds value by detailing the return structure (dict with builtin, custom, active_workflows) and the source of custom templates (~/.vmware/workflows/*.yaml), which goes beyond annotations and helps the agent understand behavior.

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

Conciseness4/5

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

The description is well-structured with a [READ] marker, clear usage guidance, and a Returns section. It is slightly longer than necessary but each sentence earns its place by providing actionable context. The front-loaded purpose makes it easy to scan.

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

Completeness4/5

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

With no parameters and no output schema, the description compensates by explaining the return structure and linking to related tools (plan_workflow, create_workflow, get_workflow_status). It also explains where custom workflows live, which is essential for an agent to use the tool correctly.

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

Parameters4/5

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

The tool has zero parameters, so the baseline is 4. The description correctly implies no inputs are needed and does not need to explain parameters. It focuses on output and usage, which is appropriate.

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 clearly states the tool lists all available workflow templates (built-in + custom). It uses a specific verb-resource pair and distinguishes itself from siblings by explaining its role as the initial discovery step, routing to plan_workflow or create_workflow as needed.

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?

The description explicitly states when to use this tool ('Use this first to see whether a template already covers the goal') and provides clear alternatives (plan_workflow, create_workflow). It also instructs how to add custom workflows via YAML files, offering concrete usage context.

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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