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create_flow

Create a new empty automation flow as a draft. Use when the user wants to start from scratch ("make a new flow", "I want to build a flow for X"). The flow has no nodes/edges yet — use add_node and add_edge to build it, or call generate_flow instead to have AI build it from a description. Trigger config is optional; if omitted the user picks one in the canvas.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
triggerNo
platformNo
accountIdYes
descriptionNo
platformUserIdYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It says the flow is a draft, has no nodes/edges yet, and that trigger configuration is optional with a fallback to user selection in the canvas. This is meaningful behavioral context beyond the schema, though it does not describe response shape or side effects in detail.

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?

Three sentences, no filler, and the core action is front-loaded. Every sentence adds distinct value: what it creates, when to use it, how to proceed, and the alternative path. This is an appropriately sized, well-structured description.

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

Completeness3/5

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

The description covers the creation intent, empty draft state, trigger fallback, and next steps via add_node/add_edge. However, since there is no output schema, it does not explain what the tool returns or how the agent should obtain the flow ID needed to reference the created flow in subsequent calls. That is a meaningful gap for invoking the tool correctly in a multi-step workflow.

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

Parameters3/5

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

Schema description coverage is 0%, so the description is expected to compensate. It adds key semantics for the trigger parameter by stating it is optional and what happens if omitted. However, it does not explain accountId, platformUserId, platform, or description beyond what their names imply; the schema structure and enums do most of the work.

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 opens with a specific verb and resource: 'Create a new empty automation flow as a draft.' It clearly distinguishes this from siblings like general flow creation and from generate_flow, which builds flows from descriptions. An agent can immediately tell what this tool is for.

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?

It explicitly states when to use it ('Use when the user wants to start from scratch') and names the alternative: 'call generate_flow instead to have AI build it from a description.' It also points to add_node and add_edge for the next steps, giving clear routing and sequencing guidance.

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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