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control-expert-mcp

control-expert-mcp

by apexsotjo-blip
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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set_dtm_dataset

Import a slave DTM configuration dataset that was previously exported from Control Expert, applying any modifications made to the dataset.

Instructions

Import a slave DTM configuration dataset (previously exported with get_dtm_dataset, possibly modified).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "name": "<name>",
      "xml": "<xml>"
    },
    "name": "set_dtm_dataset"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameYes
xmlYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations provided, the description must carry the full behavioral disclosure. It states the action 'Import', which implies a write operation, but does not describe side effects like overwriting existing data, validation requirements, or persistence. It is basic but not misleading.

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?

The description is a single sentence that is concise and front-loaded with the primary action and resource. There is no superfluous content.

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?

Given no output schema, no annotations, and zero parameter documentation, the description lacks essential details about the xml format, how the dataset is applied, and any confirmation or error behavior. An agent cannot fully anticipate the tool's requirements without additional information.

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

Parameters2/5

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

The input schema has 0% description coverage for the two required parameters (name and xml). The description does not explain what each parameter represents or the expected format, leaving the agent to infer that 'name' is an identifier and 'xml' is the dataset content. This is a significant gap.

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 the verb 'Import' and the resource 'slave DTM configuration dataset', and explicitly references the export counterpart, distinguishing it from get_dtm_dataset and set_master_dtm_dataset. An agent can immediately understand the primary function.

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?

It indicates that the tool is used to import a dataset 'previously exported with get_dtm_dataset, possibly modified', which provides clear context on when to use it. It does not explicitly state when not to use it, but the pairing with its export sibling is sufficient.

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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