lookup_term

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

The description discloses matching behavior (case-insensitive, exact) and explains where glossary entries come from (Markdown patterns, RST blocks). This adds context beyond the readOnlyHint annotation, though it does not cover auth or rate limits.

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 two sentences long, with the first sentence clearly stating the purpose and the second adding key details. It is front-loaded and concise with no extraneous information.

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 tool's simplicity (2 parameters, no output schema), the description covers purpose, matching behavior, and data source. It lacks an explicit description of the return format, but the context of glossary lookup makes it acceptable. Annotations provide some safety context.

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 schema has 0% coverage, and the description only explains the 'term' parameter's matching semantics (case-insensitive, exact). The 'repo' parameter is not described, leaving ambiguity. The description partially compensates for the lack of schema descriptions.

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 does a glossary lookup, returning entries matching the query exactly and case-insensitively. It specifies the resource (glossary terms) and the action (lookup), distinguishing it from the sibling 'list_terms' which likely lists all terms.

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 implies the tool is for finding a specific glossary term, but it does not explicitly state when to use it versus alternatives like 'list_terms' or exclude other scenarios. No when-not-to-use guidance is provided.

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