get_professor

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

With no annotations, fully describes caching behavior ('cached RateMyProfessors rating'), the `ratings_available` flag meaning, and confidence caveats. Does not mention auth or rate limits, but these are less critical for a read-only lookup.

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?

Three sentences, each adding value: first states core purpose, second clarifies name flexibility and output interpretation, third explains a key flag. No wasted words.

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 no output schema, description covers all return fields (ratings, courses, match_confidence, caveats, ratings_available). Completely explains what the agent needs to know for invocation and result interpretation.

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%, so descriptions must compensate. Explains name accepts any format and provides examples. The `term` parameter is mentioned indirectly ('this term') but lacks format or allowed values.

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 specifies the verb 'Look up', the resource 'professor by name', and the exact data returned (cached ratings and courses). It clearly differentiates from sibling tools like get_course or search_courses.

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?

Provides explicit instructions on name formats ('Professor Smith', 'J. Smith', SOC format) and how to handle low-confidence matches. Lacks explicit when-not-to-use but sibling tools are clearly distinct in function.

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