suggest

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

No annotations are provided, so the description must disclose behavioral traits. It mentions 'OpenSearch-style autocomplete' implying prefix matching and suggestion behavior, but omits details like rate limits, result limits, or whether it is a read-only operation. Adequate but not thorough.

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 concise at two sentences, front-loading the core purpose and use case. It avoids unnecessary details, though it could be slightly more structured with bullet points for key aspects.

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 autocomplete tool, the description covers the main purpose and usage context. However, it lacks details such as maximum number of suggestions, sorting order, case sensitivity, and what happens with empty or invalid queries. The absence of an output schema is acceptable but the description could compensate more.

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?

The input schema already describes the 'query' parameter as 'Prefix or partial term', achieving 100% coverage. The tool description adds context by specifying 'OpenSearch-style autocomplete', reinforcing the parameter's purpose and behavior. This adds value beyond the schema.

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 provides OpenSearch-style autocomplete combining courses and glossary terms, which is a specific and identifiable purpose. It distinguishes itself from sibling search tools by focusing on autocomplete rather than full-text 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?

The description mentions it is useful for autocomplete UI in client integrations, giving a clear use case. However, it does not explicitly state when not to use it or differentiate from alternative tools like search_glossario or search_normativa, leaving some ambiguity for the agent.

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