Suggest Fields Of Study

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

With no annotations, the description carries the full burden. It does disclose that results come back with ids, which is useful, but says nothing about result limits, ordering, minimum prefix length, case sensitivity, or what happens on no match — meaningful gaps for an autocomplete-style tool with no output schema.

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 sentence with the operation, matching mode, and return content front-loaded. No padding or redundant restatement of the title.

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 one-parameter suggest tool with no output schema, the description covers purpose, matching semantics, return payload, and usage context adequately. The remaining gap is behavior on empty or ambiguous prefixes, which is minor but real.

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% on the single 'text' parameter, so the description must compensate, and it does by explaining that matching happens 'by name prefix'. That tells an agent what to pass (a name prefix, not an id or free text), though it does not specify length or case constraints.

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 and resource ('Suggest fields of study') plus a clarifying gloss ('specialties') and the matching mode ('by name prefix'), so an agent can tell it apart from the dict_* lookup siblings. It stops short of naming a specific sibling alternative like dict_dictionaries.

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 scopes usage to 'resume and vacancy education blocks', which gives real context about when this tool applies. It offers no explicit exclusions or statement of when to use dict lookups instead, leaving the alternative implicit.

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