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Omnidim

@omnidim-ai/mcp-server

by Omnidim

getWorkflowNodeType

Read-only

Retrieve a workflow node type's config fields, required flags, and outputs before adding or editing nodes. Use full detail for help text and examples.

Instructions

The settings one node type reads, with their types, required flags and outputs. Call it before you add or edit a node, because its fields are the keys of the node's config. Use detail=full only when you need help text and examples.

(Tags: Workflows)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
detailNo`full` adds descriptions, examples and `output_example`.minimal
node_typeYesA node type from `listWorkflowNodeTypes`, such as `whatsapp`.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.14.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds real behavioral context beyond that: the returned `fields` are the config keys for the node, and `detail=full` expands the response with descriptions, examples and output_example, which tells the agent what a heavier call costs.

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?

Two tight sentences with zero filler; the primary purpose and the pre-edit usage rule are front-loaded, and the detail-param caveat follows as secondary guidance.

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?

No output schema exists, yet the description still characterizes the return (settings with types, required flags, outputs, and what full detail adds). Combined with full param coverage and read-only annotations, an agent has everything needed to call it 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?

Schema coverage is 100%, so the baseline is 3. The description earns above baseline by explaining the practical trade-off of `detail=full` (help text and examples, use only when needed) and by tying `node_type` semantics to the config-key relationship, adding meaning the enum/default alone doesn't convey.

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

Purpose4/5

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

States a specific verb and resource: it returns the settings one node type reads, including types, required flags and outputs. It's clear what comes back, but it never explicitly names its closest sibling (listWorkflowNodeTypes) to contrast the single-type lookup against the listing, leaving that distinction to the schema.

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

Usage Guidelines4/5

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

Gives a concrete when-to-use rule ('Call it before you add or edit a node') grounded in a reason (its fields are the keys of the node's config), and adds a when-to-use for the detail param. It stops short of stating when not to use it or naming an alternative tool.

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