Look up an instructor

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

Annotations already cover read-only, idempotent, non-destructive behavior. The description adds meaningful behavioral context by stating that it returns courses taught and an average GPA aggregated across all courses, which goes beyond the schema and helps the agent understand aggregation behavior.

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 concise sentences with no filler. The core action and output are front-loaded, and the use case is added in a single closing sentence. Every word earns its place.

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 rich annotations, complete schema descriptions, and optional parameters, the description provides enough context for an agent to select and call the tool. It does not fully specify behavior when no parameters are supplied, but the schema's optionality and openWorldHint mitigate that gap.

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 description coverage is 100%, so the baseline is 3. The description does not add meaning beyond the schema for parameters like name, ucinetid, and includeGrades, but it does imply the output context in which those parameters are used.

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 uses a specific verb ('Find') and resource ('UCI instructor'), and enumerates the exact returned data points: title, department, courses taught, and average GPA. This clearly distinguishes it from sibling tools like course_grades, which focus on grades for a course rather than an instructor profile.

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 gives an explicit use case: 'Use to evaluate a professor before enrolling.' It does not name alternative tools or state when not to use it, but the context is clear enough for an agent to select it over the listed siblings.

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