Suggest Educational Institutions

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

No annotations are provided, so the description carries the full disclosure burden. It does add real behavior information beyond the schema: matching is prefix-based rather than substring/fuzzy, and results carry ids. It omits result limits, ordering/ranking, behavior on empty or very short input, and whether matching is case-sensitive.

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?

One front-loaded sentence with no filler; the distinguishing qualifier ('by name prefix') and the return content ('with their ids') both earn their place. It is slightly terse for a tool with zero parameter documentation and no annotations.

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 one-parameter lookup with no annotations or output schema, the description covers what is matched and what comes back. It leaves open result-set size, ordering, and how it relates to the non-suggest dictionary tool, which an agent would need when picking among the many suggest_* siblings.

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% and the single parameter 'text' is bare, so the description must compensate. 'By name prefix' successfully establishes that 'text' is the institution-name prefix to match, but it says nothing about trimming, casing, or minimum length.

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 names a specific verb ('Suggest'), a specific resource ('educational institutions'), and the matching and return semantics ('by name prefix with their ids'). An agent can tell it apart from the plain dictionary sibling dict_educational_institutions by the prefix-matching scope, though the difference is implied 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?

The phrase 'by name prefix' implies an autocomplete/typeahead pattern, which is useful context for choosing it over a full dictionary lookup. However, it never explicitly says when to use this versus dict_educational_institutions, nor any minimum prefix length or when it is inappropriate.

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