search_glossary

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

Annotations are absent, so the description carries the full burden. It does disclose the return shape ('List of matching entries with relevance scores, or error dict'), but it does not state read-only behavior, result ordering, empty-result handling, or any operational caveats.

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 compact and well-structured: a one-line purpose, an Args block, and a Returns block. Every sentence contributes meaningful information without redundancy.

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 output schema exists and the tool only has three parameters, the description covers essential invocation details. It could be more complete by explaining when to choose this over lookup_term, but nothing critical is missing for making a basic call.

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%, but the description compensates by defining query as a natural-language search, domain as an optional filter, and limit as max results with defaults and maximum. It adds practical meaning to all parameters, though domain values remain unspecified.

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 opens with a specific action and resource: 'Semantic search for glossary entries.' It clearly states what the tool does, though it does not explicitly differentiate itself from sibling tools like lookup_term or list_glossary.

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?

There is no guidance on when to use semantic search versus lookup_term or list_glossary, and no mention of alternatives or exclusions. The natural-language query intent is implied but never framed as a usage rule.

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