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mcp-fabric-api

mcp-fabric-api

by mkoziel2000
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

semantic_model_update_tmdl

Update a semantic model by applying TMDL definitions from .tmdl and .pbism files in a specified directory. Supply workspace ID, model ID, and path to trigger the update.

Instructions

Update a semantic model's definition from TMDL files (long-running). Reads .tmdl and .pbism files from the specified directory.

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": {
      "workspaceId": "<workspaceId>",
      "semanticModelId": "<semanticModelId>",
      "filesDirectoryPath": "<filesDirectoryPath>"
    },
    "name": "semantic_model_update_tmdl"
  }
}

Input Schema

NameRequiredDescriptionDefault
workspaceIdYesThe workspace ID
semanticModelIdYesThe semantic model ID
filesDirectoryPathYesPath to a directory containing .tmdl and .pbism files

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.8.0

TDQS

A3.7/5.0
Behavior3/5

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

Annotations indicate readOnlyHint=false and destructiveHint=false, and the description adds useful context that this is a long-running operation and that it reads .tmdl and .pbism files. It does not disclose whether the operation overwrites the existing definition, whether prior content is lost, or how completion is reported, which would be valuable for a mutating long-running operation.

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 short and front-loaded with the action, then adds the key behavioral note about long-running execution and the specific file extensions. Every clause earns its place without excessive verbosity.

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?

For a simple three-parameter tool with clear schema coverage, the description is mostly adequate. However, because this is a long-running mutation with no output schema, some guidance about expected results, side effects, or how to check operation status would improve completeness.

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 100%, so all three parameters are already documented. The description adds minimal extra meaning beyond noting that filesDirectoryPath contains .tmdl and .pbism files, which largely mirrors the schema. This matches the baseline of 3 for fully schema-documented parameters.

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 action: updating a semantic model's definition from TMDL files. It distinguishes itself from related siblings like semantic_model_update_bim (BIM-based update) and semantic_model_create_tmdl (creation), by focusing on TMDL-file-driven updates.

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 description implies the tool is for updating an existing semantic model from local TMDL files, and touts that it is long-running. However, it does not explicitly state when to choose this over semantic_model_update_bim, semantic_model_create_tmdl, or semantic_model_update_details, leaving alternatives to inference.

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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