List Students Needing Attention

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

Annotations already mark read-only and non-destructive, so the description adds valuable behavioral context beyond that: each finding lists the exact signals that fired and the thresholds used, and it explicitly states the report is factual rather than predictive. It also clarifies permission requirements. However, it does not describe pagination, ordering, or the full finding structure.

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?

Two compact sentences with zero filler. The core verb+resource and discriminating signals are front-loaded, and the permission note and non-prediction caveat are expressed efficiently in the second sentence.

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?

There is no output schema, so the partial output description ('Each finding lists the exact signals... thresholds') is helpful but incomplete. Missing details about ordering, pagination, or handling of courses with no such students would be beneficial. The openWorldHint annotation partly compensates by signaling unknown output freedom, but an agent may still guess at result shape.

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 schema already explains each parameter. The description adds that thresholds are reflected back in the output, which ties parameters to behavior, but it does not add new meaning to the parameters themselves beyond the schema. Baseline 3 is appropriate.

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 names a specific verb ('Report'), a resource ('students who may need instructor attention'), and a clear composite signal set ('inactivity, missing or late submissions, and low current score'). This distinguishes it from sibling tools like list_submissions_awaiting_grading or get_missing_submissions by aggregating multiple signals rather than focusing on a single one.

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 states the permission prerequisite (requires instructor/TA) but gives no explicit guidance on when to choose this tool over closely related siblings like get_missing_submissions or list_submissions_awaiting_grading. There is no 'use this instead of X when...' or exclusionary condition, so the agent must infer the intended usage context.

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