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christianclaudio

mcp-server-sigma

Datasets Swap Data Model Sources

datasets_swap_data_model_sources

Swap a data model's data sources by passing its ID and source mappings, so AI assistants can reroute datasets without rebuilding the model.

Instructions

Swap data sources for a data model.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYes
data_model_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv2.0.4

TDQS

C2.6/5.0
Behavior2/5

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

Annotations already declare this is a non-read-only, non-destructive, open-world operation, so the safety profile is partly covered. However, the description adds nothing beyond the name: it does not say what 'swap' does to existing sources (replace vs. add), whether the operation is reversible, what permissions it needs, or what the nested body must contain.

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?

A single front-loaded sentence with no padding or redundancy. It is appropriately sized, though the brevity reflects under-specification rather than disciplined concision.

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?

For a mutation tool whose body parameter is a completely opaque object, the definition leaves the agent unable to construct a correct call. The output schema exists, so return values need not be explained, but the missing body semantics and usage context make this inadequate for a 2-param write operation.

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% with two required parameters, one of which is a free-form nested object (additionalProperties: true) with no documented shape. The description gives no parameter information at all, so it fails to compensate for the coverage gap on the critical body payload.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clear verb+resource: 'Swap data sources for a data model.' An agent can distinguish it from the workbook/report swap siblings by the object ('data model'), but the description never names or explicitly contrasts those siblings, so differentiation requires inference from the tool name.

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

Usage Guidelines2/5

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

No when-to-use, no prerequisites, no alternatives. Nothing tells the agent when a source swap is appropriate versus datasets_swap_report_sources or elements_swap_workbook_sources, or what state the data model must be in first.

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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