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Get custom dataset

get_custom_data
Read-only

Get a single custom-data dataset by ID, including its parsed rows.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesCustom-data ID (from list_custom_data)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNoThe dataset — id, name, file_name, columns, and raw_data: the parsed rows, each an object keyed by column name.
successYesTrue when the call succeeded.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • removedInput schema / $schema
      Removed value: -"http://json-schema.org/draft-07/schema#"
    • removedOutput schema / $schema
      Removed value: -"http://json-schema.org/draft-07/schema#"
    • changedOutput schema / properties / success / description
      Previous value: -"True when the call succeeded. A failure comes back as an error result instead."New value: +"True when the call succeeded."
  2. First observed

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds one behavioral detail – it returns 'parsed rows' – which is useful but likely also present in the output schema. No hidden side effects, auth, or error behavior disclosed; acceptable for a read-only getter.

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?

Single sentence, front-loaded with the core action and resource. No filler, every word earns its place. The qualifier 'including its parsed rows' adds value without bloating.

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 one-parameter read-only tool with annotations and an output schema, the description is nearly sufficient. It clearly states the operation and response scope. It doesn't explicitly mention that IDs come from list_custom_data, though the schema does, and it lacks explicit sibling differentiation, but given the tool's simplicity and the surrounding context, the gaps are minor.

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%; the `id` parameter is already documented with 'Custom-data ID (from list_custom_data)', including its source. The description merely says 'by ID', adding no further semantic value beyond the schema. Baseline 3 applies.

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?

States exactly what it does: 'Get a single custom-data dataset by ID' – the verb 'Get' plus resource 'custom-data dataset' and qualifier 'single' differentiates it from list_custom_data. The addition 'including its parsed rows' clarifies the response contents.

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 usage: call it when you have an ID and want the dataset. It does not explicitly steer against alternatives such as list_custom_data for enumerating IDs, nor does it mention when not to use. Schema parameter note 'from list_custom_data' is a hint but not part of the description. Adequate but no explicit routing.

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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