compare_subjects_tool

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

No annotations are provided, so the description fully bears the burden of behavioral disclosure. It lacks details on the nature of comparison (e.g., returns chart? text? percentage?), side effects (likely none but unstated), authentication needs, or rate limits. This omission significantly reduces transparency for a tool with no annotation support.

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 extremely concise with two sentences and an example, containing no extraneous information. Every part serves a purpose: stating the action, specifying the input format, and giving an example.

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 absence of annotations and the presence of an output schema (which may describe return values), the description is minimally complete. It explains what the tool does and how to call it, but omits details like return format, pagination, or error handling. While the output schema could compensate, the description alone feels incomplete for a tool comparing multiple subjects.

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 input schema has one parameter with 0% description coverage. The description adds crucial meaning: it explains the expected format (comma-separated codes or names) and provides two concrete examples. This goes well beyond the bare schema and aids correct parameter construction.

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 compares performance across subjects, using a specific verb and resource. While it distinguishes from siblings like get_grades or get_cgpa by focusing on comparison, it could be more explicit about what 'performance' means (e.g., grades, CGPA) to avoid 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 provides input format guidance and examples, implying when to use it. However, it does not explicitly state when this tool is preferred over sibling tools like get_grade_distribution_tool or recommend_electives_tool, nor does it mention any prerequisites or exclusions.

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