search_selections

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

No annotations are provided, so the description carries full responsibility. It describes the search behavior and recommendation for Czech language but does not explicitly state that it is read-only, mention consent or rate limits, or disclose any side effects. For a search tool, this is adequate but not exhaustive.

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?

Three clear sentences: purpose, context, and usage tip. No unnecessary words. Front-loaded with the core action.

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?

With an output schema present, the description does not need to detail return values. It covers what the tool does, what selections are, how to use the results, and a search optimization tip. Missing details like search behavior (fuzzy, partial match) but sufficient for typical use.

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?

Input schema has 0% description coverage, but the description adds that the query is a keyword and recommends Czech language for best results. This provides meaningful guidance beyond the schema structure.

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 states 'Search for predefined data tables (selections) by keyword,' which is a specific verb-resource combination. It distinguishes from siblings like search_datasets (which targets datasets) and list_selections (which lists all without search).

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?

It provides clear context: selections are pre-configured views, easiest way to get data. It suggests using Czech for best results and directs users to get_selection_data for retrieval. However, it does not explicitly state when not to use or compare with alternatives like search_datasets.

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