dataset_columnsThe columns, which of them are numeric, the row count and the provenance banner of the Inductvo dataset. Call this first to learn the schema.
This tool declares no required parameters. Add optional parameters from the input schema as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {},
"name": "dataset_columns"
}
}| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears the full burden, and it discloses the concrete output contents: columns, numeric indicators, row count, and provenance banner. The read-only intent is implied by 'learn the schema,' though it does not explicitly state side-effect absence or failure behavior.
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 sentence that front-loads the output contents and immediately gives the usage directive. Every part contributes value, with no filler or repetition.
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 zero-parameter schema introspection tool with no output schema or annotations, the description covers what the agent needs to know: what data will be returned and when to call it. Nothing essential is missing.
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?
The tool has zero parameters, so the description need not explain parameter meaning. The baseline of 4 applies, and no additional explanation is required.
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 what the tool returns: columns, numeric flags, row count, and provenance banner for the Inductvo dataset, and identifies its role as a first-step schema learner. It does not explicitly name sibling tools or explain how it differs from dataset_provenance or dataset_stats, so it stops short of full sibling differentiation.
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?
It gives explicit usage guidance: 'Call this first to learn the schema.' This tells the agent when to use it. It does not mention when not to use it or name alternatives, but the instruction is clear enough for an obvious first-step introspection tool.
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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