search_datasetsSearch public dataset family IDs, names, slugs, and publishers in the canonical ClinicMarketIQ catalog.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover readOnly, idempotent, and non-destructive behavior, so the safety burden is handled. The description adds useful scope ('public') and the searchable fields, but it does not disclose pagination, matching behavior, ordering, or return 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?
A single, focused sentence with no filler. The verb and scope are front-loaded, making the core behavior immediately clear.
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 two-parameter search tool with strong annotations, the definition is usable but incomplete. It lacks sibling differentiation and any hint about result format, and with no output schema those details would add meaningful context.
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 compensate. Listing the searched fields gives meaning to the query parameter, but limit is left to its name and schema constraints, which are fairly self-explanatory. Partial compensation for the coverage gap.
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 ('Search'), a resource ('public dataset family IDs, names, slugs, publishers'), and a scope ('canonical ClinicMarketIQ catalog'). However, it does not explicitly differentiate this from list_datasets, leaving some distinction to inference.
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 or alternatives are provided. The agent must infer that search_datasets is for query-based lookup rather than enumeration via list_datasets, and no exclusions are stated.
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.
Each tool targets a clearly distinct operation: catalog discovery (list/search), metadata retrieval, download URL retrieval, schema retrieval, and checksum verification. The only potential overlap is between metadata and download URL, but the descriptions make their boundaries explicit.
Tool names consistently follow a snake_case verb_noun pattern: get_*, list_datasets, search_datasets, verify_checksum. The naming style is uniform and every verb accurately reflects the action.
Six tools is a well-scoped set for a public dataset metadata and access server. Each tool covers a necessary step in the discovery-to-download workflow without redundancy.
The workflow is complete for the stated domain: discover datasets, inspect metadata and schema, obtain download URLs, and verify checksums. Direct dataset bytes are intentionally not proxied, so this is not a gap given the server's defined purpose.