search_datasets

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full transparency burden. It discloses case-insensitive matching, the specific fields searched, the maximum return count (20), and the response schema. It does not cover pagination, ordering, or empty result behavior, but for a simple search tool the disclosure is fairly comprehensive.

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 three concise sentences. The first sentence states the core purpose, the second adds detail on matching behavior, and the third specifies output. No extraneous words; 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 and the presence of an output schema (though not shown), the description covers essential aspects: search scope, matching logic, result limit, and returned fields. It does not mention sorting or relevance, but for a basic search tool the information provided is sufficient for correct usage.

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 coverage is 0%, so the description must explain parameters. It effectively describes 'keywords' as the search term and 'catalog' as an optional filter: 'across all catalogs or one' implies null means all, string means one. This adds meaningful context beyond the schema's type definitions.

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 tool's purpose: finding dataset collections by keywords across all catalogs or a specific one. It specifies the matching fields (id, title, description, keywords) and the return structure (up to 20 hits with catalog, id, title, summary). This is specific and distinguishes it from sibling tools like search_imagery.

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 when to use the tool (for keyword-based dataset search) and hints at scope (all catalogs or one). However, it does not explicitly state when not to use it or mention alternatives among siblings (e.g., list_catalogs for browsing, search_imagery for imagery). Usage guidance is adequate but lacks explicit exclusions or comparisons.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.