dataset_detailsGet full metadata for a single dataset by numeric id (from search_datasets). Returns the JSON:API dataset object: title, notes, license, keywords, regions, institution relationship and resource count.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Dataset numeric id, e.g. "771". | |
| lang | No | Language hint "en" or "pl". |
Changes observed during successful MCP inspections.
Input schema / examplesAdded value: +[
+ {
+ "id": "771"
+ },
+ {
+ "id": "771",
+ "lang": "pl"
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds value by specifying the return format (JSON:API dataset object) and listing included fields. No contradictions.
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?
Two sentences, no wasted words, front-loaded with key information. Every sentence earns its place.
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?
Given the tool's simplicity (2 params, no nested objects, no output schema), the description is fairly complete. It covers what, how, and what to expect. Could mention optional lang effect but schema covers it.
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 description coverage is 100%, so baseline is 3. The description mentions 'numeric id' but does not add significant meaning beyond the schema. The 'lang' parameter is not addressed in the description.
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 the action ('Get full metadata'), resource ('single dataset'), and identifier ('by numeric id from search_datasets'), distinguishing it from sibling tools like search_datasets and other read-only tools.
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 the tool should be used after search_datasets to retrieve full details, providing clear context. It could be more explicit about when not to use it, but the guidance is sufficient for an AI agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.