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Omnidim

@omnidim-ai/mcp-server

by Omnidim

createWorkflow

Create a workflow draft for @omnidim-ai/mcp-server, starting with a trigger node or a full graph; returns the revision needed to edit it.

Instructions

Create a workflow with a draft. Without graph, the draft holds one trigger node, ready for editWorkflow ops. Pass graph only to start from a complete graph. The response carries the revision you need to edit.

(Tags: Workflows)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
requestBodyYesThe JSON request body.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.14.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare it is a non-readonly, non-destructive, non-open-world write. The description adds real value beyond that: the default draft content, that graph input passes the same validation as editWorkflow ops, and that the response carries the `revision` needed for editing. It does not state the resulting activation/publish state or any permission requirements.

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?

Four short sentences, front-loaded with the core action, then default behavior, then the graph caveat, then the return contract. No filler; the only overhead is the '(Tags: Workflows)' suffix.

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?

There is no output schema, and the description compensates by naming the `revision` field returned. The deeply nested graph object is fully documented in the schema. Missing only peripheral context such as the created workflow's initial state.

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, but the description adds conditional semantics the schema cannot: what the draft contains when `graph` is omitted, and the 'only' caveat for supplying it. This meaningfully reduces the chance of over-sending a full graph.

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?

Specific verb+resource: 'Create a workflow with a draft', plus the default behavior (one trigger node) that no sibling tool shares. It also names editWorkflow as the downstream consumer, which anchors this tool's role in the workflow lifecycle.

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?

Explicit conditional guidance: omit `graph` to get an editable draft, and 'Pass `graph` only to start from a complete graph.' It does not explicitly frame alternatives at the tool level (e.g., why createWorkflow vs. editWorkflow from scratch), but the when/when-not for the key decision is clear.

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