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informatics-isi-edu

Deriva MCP Server

Official

create_workflow

Create and register a new workflow definition with a name, type, and description for cataloging and managing machine learning processes.

Instructions

Create and register a new workflow definition.

Args: name: Display name for the workflow. workflow_type: Type from Workflow_Type vocabulary (e.g., "Training", "Inference"). description: What this workflow does.

Returns: JSON with status, rid, name, workflow_type, description.

Example: create_workflow("ResNet Training", "Training", "Trains ResNet50 on image data")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
descriptionNo
workflow_typeYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses that the tool creates and registers, and describes the return structure. However, it does not mention side effects, permissions, or potential errors, leaving gaps in behavioral transparency.

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 Args, Returns, and Example sections. It's front-loaded with the core statement and every sentence provides value. Slightly verbose due to example, but not wasteful.

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?

For a simple create tool, the description covers purpose, parameters, return format, and an example. It doesn't discuss usage alternatives or edge cases, but given the tool's simplicity and the presence of an output schema, it is sufficiently complete.

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 schema provides no descriptions (0% coverage), but the description compensates by adding 'Display name' for name, 'Type from Workflow_Type vocabulary' with examples for workflow_type, and a purpose for description. This adds meaningful context beyond the titles.

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 'Create and register a new workflow definition', using a specific verb and resource. It distinguishes itself from sibling tools like set_workflow_description or add_workflow_type by focusing on the creation/registration aspect.

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

Usage Guidelines3/5

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

The usage is implied: you'd use this to create a workflow. However, there is no explicit guidance on when to use it vs alternatives, no exclusions, and no mention of prerequisites. This is adequate but basic.

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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