Опис та параметри публічно доступного набору даних.
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": {
"dataset_id": "<dataset_id>"
},
"name": "describe_dataset"
}
}| Name | Required | Description | Default |
|---|---|---|---|
| dataset_id | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. It only conveys that the dataset is publicly available (implying no auth), with no information about behavior for invalid IDs, error modes, response shape, or stability of the returned metadata.
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?
A single short, front-loaded sentence with no filler. It is efficient, though it errs toward under-specification rather than excess.
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?
With no output schema, the description partially discharges the burden by stating what is returned (description and parameters of the dataset). However, with no annotations and an undocumented required ID parameter, key invocation details remain 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?
There is one parameter with 0% schema description coverage, so the description must compensate and does not. It never explains the dataset_id format or where the identifier comes from (e.g. list_datasets), leaving the agent to guess.
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 names a clear verb (describe) and resource (dataset) and adds the scope 'publicly available dataset' plus what is returned (description and parameters). It is understandable without opening the schema, but it does not differentiate itself from siblings like list_datasets or get_catalog_info.
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?
No when-to-use guidance, no prerequisites, and no mention of alternatives. An agent cannot tell from the text when describe_dataset should be preferred over list_datasets or get_catalog_info, though the name implies a single-item lookup.
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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