get_instructor_fces

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

With no annotations, the description fully covers behavior: it returns compact summaries aggregated across semesters, requires auth token, and references return type. No contradictions or missing side effects; it explicitly notes default behavior ('compact summary').

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 (approx. 100 words) and well-structured with clear sections (Auth, Args, Returns). Every sentence serves a purpose, with no redundancy or outdated info.

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, output schema exists), the description covers all essential aspects: purpose, auth, parameter details, return type reference, and usage context. It is fully adequate for an agent to invoke correctly.

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 explains both parameters: instructor requires exact match and references search_instructors; include_all is explained via get_course_fces and notes default False. This adds necessary meaning beyond the schema's field names.

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's purpose: 'Fetch Faculty Course Evaluations (FCE) ratings for an instructor.' It also specifies use cases ('for a professor's teaching record across courses, or to compare instructors'), differentiating it from sibling tools like get_course_fces and search_instructors.

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 instructs when to use the tool (e.g., for teaching records or comparisons) and provides a prerequisite ('use search_instructors' for exact name match). It references get_course_fces for include_all details but lacks explicit exclusion guidance or full alternative comparisons.

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