get_campus_life

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

Annotations already declare readOnlyHint=true, and the description adds that the tool returns housing assignment and Plaid Cash balance. It does not go deeper into data source, freshness, or response behavior, but for a simple read-only getter this is acceptable.

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?

Extremely concise and front-loaded. The first line is a minor fragment ('Housing assignment, and Plaid Cash balance.'), but it immediately conveys the key resources, and the second line gives actionable usage guidance.

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 no-parameter read-only tool with an output schema, the description is largely complete: it states what data is returned and when to call. It could mention the output schema or any limitations, but the structured schema covers return details.

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 the baseline is 4. There is no parameter information needed, and the description fully covers the absence of parameters by focusing on when to 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 clearly identifies the tool's scope: housing assignment and Plaid Cash balance, with explicit user intents ('asks where they live on campus or about their Plaid Cash'). This is specific enough to distinguish it from sibling tools like get_schedule and get_grades.

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?

Provides explicit trigger conditions for when to call the tool. It does not discuss exclusions or alternatives, but the conditions are specific and cover the main use cases.

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