grades

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

With no annotations provided, the description carries the burden of behavioral disclosure. It does disclose a key behavioral trait: results are shown only 'when visible to the token,' which is useful context about access scoping. However, it does not describe the return format, whether grades are aggregated or per-assignment, or any rate-limit/auth implications.

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?

A single, compact sentence that front-loads the resource ('grade/score metadata') and adds the key scoping condition. Every word earns its place; no filler or repetition.

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?

For a parameterless read tool, the description is mostly sufficient: an agent knows what it returns and the visibility caveat. However, with no output schema and no annotations, the agent is left guessing about the response shape (e.g., per-course objects, numeric scores, letter grades), which is a meaningful gap for a tool whose entire purpose is returning data.

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 tool has zero parameters, so there is no schema to compensate for. The description adds meaning by specifying the scope ('by enrolled course') and the visibility condition, which is the only semantic content an agent needs for a parameterless call.

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 states a specific resource ('grade/score metadata by enrolled course') and a condition ('when visible to the token'), which clearly distinguishes it from sibling tools like list_courses or list_assignments. It lacks a strong verb like 'retrieve' or 'list', but the noun phrase is specific enough to convey the tool's purpose.

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 a read-only lookup of grade metadata, and the sibling names (list_courses, list_assignments, upcoming, overdue) suggest it is the grade-specific counterpart. However, it does not explicitly state when to prefer this tool over alternatives or mention any exclusions, leaving the agent to infer usage context.

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