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christopher2lllp3t-cell

materials-studio-mcp-moc

ms_recommend_workflow

Recommends a Materials Studio workflow for a natural-language task request, using the MCP server's catalog to match input structure and calculation context to the appropriate preparation step.

Instructions

Recommend the best available Materials Studio MCP workflow for a natural-language task request.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
requestYes
input_structureNo
calculation_contextNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

With no annotations, the description carries the burden of disclosing behavioral traits. It only says 'recommend', which suggests no side effects, but does not specify whether it executes workflows, reads files, or what 'best available' means. The lack of detail leaves ambiguity about how the recommendation is produced and whether it has side effects.

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 a single, front-loaded sentence with no filler words, making it efficient. However, it is perhaps too terse for a recommendation tool with three parameters, but it earns a 4 for zero waste.

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

Completeness2/5

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

The tool has three parameters and an output schema, and lacks annotations. The description does not explain how the parameters affect the recommendation, what 'best available' means, or how this tool fits with sibling workflow tools. It is too sparse for a router tool that likely needs to communicate prerequisites and usage context.

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

Parameters1/5

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

Schema description coverage is 0% and the description does not describe any parameters. The request parameter is obvious from the description, but input_structure and calculation_context are unexplained, and the format or use of request is not elaborated.

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 a specific verb (recommend) and resource (best available Materials Studio MCP workflow) for a natural-language task request. It distinguishes itself from sibling execution tools, which perform specific actions rather than recommending among workflows.

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 phrase 'for a natural-language task request' implies when to use the tool, but it does not provide explicit when-not-to-use guidance or name alternative tools such as ms_execute_task_request or ms_task_catalog. The usage context is implied rather than directly stated.

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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