get_custom_dataGet a single custom-data dataset by ID, including its parsed rows.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Custom-data ID (from list_custom_data) |
| Name | Required | Description | Default |
|---|---|---|---|
| data | No | The dataset — id, name, file_name, columns, and raw_data: the parsed rows, each an object keyed by column name. | |
| success | Yes | True when the call succeeded. A failure comes back as an error result instead. |
Changes observed during successful MCP inspections.
Output schema / (root)Previous value: -nullNew value: +{
+ "$schema": "http://json-schema.org/draft-07/schema#",
+ "additionalProperties": false,
+ "properties": {
+ "data": {
+ "additionalProperties": {},
+ "description": "The dataset — id, name, file_name, columns, and raw_data: the parsed rows, each an object keyed by column name.",
+ "type": "object"
+ },
+ "success": {
+ "description": "True when the call succeeded. A failure comes back as an error result instead.",
+ "type": "boolean"
+ }
+ },
+ "required": [
+ "success"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, covering the safety profile. The description adds value by disclosing that the response includes parsed rows, which is a behavioral detail beyond the simple 'get' semantics and not obvious from annotations alone.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence with no filler. The core action and key behavioral detail are front-loaded, and every word contributes to understanding the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
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 an output schema and full annotation coverage, the description is sufficient. It clearly communicates what the tool returns and how it is identified, leaving no critical gaps for an agent to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the id parameter is described as 'Custom-data ID (from list_custom_data)', so the schema already provides full parameter semantics. The description does not add significant meaning beyond restating 'by ID', so the baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb ('Get'), resource ('single custom-data dataset'), and scope ('by ID, including its parsed rows'). It distinguishes itself from list_custom_data and other custom-data tools by emphasizing the single-item retrieval plus parsed rows.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool (retrieve a specific custom-data dataset by ID) and the schema notes the ID comes from list_custom_data, which is useful context. However, it does not explicitly contrast with alternatives or state when not to use it, so it falls short of a 5.
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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