Retrieve details for a specific USPTO bulk dataset product by product ID to check available patent data files and metadata.
Get details of a specific bulk dataset product.
Args:
product_id: Dataset product identifier
| Name | Required | Description | Default |
|---|---|---|---|
| product_id | Yes |
Changes observed during successful MCP inspections.
v1.8.1Output schema / (root)Previous value: -{
- "properties": {
- "result": {
- "additionalProperties": true,
- "title": "Result",
- "type": "object"
- }
- },
- "required": [
- "result"
- ],
- "title": "odp_get_datasetOutput",
- "type": "object"
-}New value: +nullv1.1.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint, so the safety profile is fully covered. The description adds only the 'bulk dataset product' framing and nothing about return shape, rate limits, or auth, so with the lowered bar it is adequate but thin.
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?
Extremely short and front-loaded, with the core action stated first. The Args block is boilerplate but harmless given a single parameter.
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 get-by-id tool with full annotation coverage and no output schema, the description is minimally sufficient. It omits where product_id comes from and gives no sense of what 'details' are returned, which an agent would want for a bulk dataset lookup.
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 0%, so the description must carry the burden. It labels product_id as a 'Dataset product identifier,' which adds minimal semantic value beyond the parameter name, but at least confirms it is an identifier rather than free text.
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?
States a specific verb and resource: 'Get details of a specific bulk dataset product.' An agent can distinguish it from the sibling odp_search_datasets by the 'specific' qualifier, though the contrast is implicit rather than stated.
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 odp_search_datasets as the way to discover the product_id this tool requires. The only hint of context is 'specific,' which leaves the agent to infer that an identifier must already be known.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.