Project GPA

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

With no annotations, the description carries the full burden and meets it by disclosing nontrivial behavior: only the last attempt of a course counts, equivalent course codes are treated as the same course, and the tool self-checks against the GPA reported by OBS to expose silent model drift.

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 earn their place: purpose plus example in the first sentence, modeling rules and output behavior in the second. No redundant phrasing or filler.

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?

The tool is low in complexity with one optional parameter and an output schema present, so the description need not explain return values. It covers input format, computation rules, and drift-check behavior; only explicit usage boundaries are missing.

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%, so the description compensates by showing the exact 'COURSECODE:GRADE' shape via the example. It does not spell out accepted grade values or null behavior in detail, but the single optional parameter is made sufficiently concrete for an agent to call the tool correctly.

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 opens with a specific verb+resource: 'Project the cumulative GPA under hypothetical grades,' which clearly identifies this as a simulation tool rather than a retrieval tool like obs_get_grades or obs_get_transcript. The concrete example input makes the operation unmistakable.

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?

It clearly frames when to use the tool: for hypothetical grade scenarios rather than actual GPA retrieval, and it even provides an example input. It does not explicitly name sibling alternatives or state exclusions, but the context is strong enough for an agent to route correctly.

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