analyze_course_feedback

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

No annotations are provided, so the description must fully disclose behavioral traits. It describes the analysis as returning structured outputs but does not mention side effects, read-only nature, error handling, or limitations (e.g., input size limits are only in the schema). The description does not contradict annotations (none exist), but it is insufficient for an agent to safely invoke the tool without additional assumptions.

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, front-loaded with the primary purpose and outputs. No extraneous information, perfectly scoped for quick comprehension.

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 that an output schema exists to document return values and the tool is a non-destructive analysis, the description covers the main purpose, input type, and high-level output categories. It lacks details on error behavior or scalability, but for this type of tool, it is largely complete.

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?

Input schema coverage is 100%, so baseline is 3. The description adds minimal meaning beyond the schema—it only restates that input is a JSON array of feedback strings. The optional parameters 'course_name' and 'analysis_focus' are not mentioned in the description, missing an opportunity to clarify their purpose.

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 analyzes a batch of student course feedback and lists specific outputs: sentiment scores, top themes, complaints, praises, and improvement suggestions. It uses a specific verb 'analyze' and resource 'course feedback', and the sibling tools handle unrelated tasks (report generation, outline creation, etc.), so there is no ambiguity.

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 when to use the tool (when you have a batch of student feedback to analyze) but does not explicitly state when not to use it or provide alternatives. Given the siblings are clearly different, the usage is reasonably implied, but no explicit guidance is given.

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