Fetch detailed information for a single dataset using its slug, owner/slug, or ul:// URI.
Get details for one dataset by slug, owner/slug, or a ul://owner/datasets/slug URI.
| Name | Required | Description | Default |
|---|---|---|---|
| dataset | Yes | Dataset ref by slug, owner/slug, or a ul://owner/datasets/slug URI. |
Changes observed during successful MCP inspections.
v0.1.13Input schema / properties / dataset / descriptionPrevious value: -"Dataset ref by slug, owner/slug, or ul:// URI."New value: +"Dataset ref by slug, owner/slug, or a ul://owner/datasets/slug URI."v0.1.12Input schema / properties / dataset / descriptionPrevious value: -"Dataset ref by id, slug, username/slug, or ul:// URI."New value: +"Dataset ref by slug, owner/slug, or ul:// URI."v0.1.6Input schema / properties / dataset / descriptionAdded value: +"Dataset ref by id, slug, username/slug, or ul:// URI."v0.1.0Does 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 the accepted identifier forms, but that is more parameter-related than behavioral; it does not disclose things like not-found behavior, authentication needs, or response shape.
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 compact sentence with no filler. The verb, resource, and the three accepted formats are all front-loaded and immediately actionable.
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 simple single-parameter read operation with annotations covering safety, the description is nearly complete. The only minor gap is that with no output schema, it does not describe the response structure, but 'details' conveys enough for an agent to know what to expect.
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% and the only parameter, 'dataset,' already documents the same slug, owner/slug, and URI formats. The description restates this information rather than adding meaning beyond the schema, so the baseline score of 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 uses a specific verb ('Get') and resource ('details for one dataset'), and clearly enumerates the acceptable reference formats. It is immediately distinguishable from sibling tools like datasets_list or explore_datasets.
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 single-dataset lookup by using 'one dataset,' but it does not explicitly state when to prefer this over sibling tools such as datasets_list or explore_datasets. No exclusions or alternative conditions are given, so guidance is only implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.