get_usc_meal_plan_rules

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

No annotations are provided, so the description carries the full burden. It only states the tool's purpose without disclosing any behavioral traits (e.g., read-only, no side effects, expected behavior). The one-sentence description is insufficient for transparency.

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 a single clear sentence with no fluff, earning its place. It is front-loaded with the purpose. However, it could be expanded slightly without losing conciseness to improve completeness.

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 output schema exists but the description does not summarize what the rules contain, and the tool has many siblings, the description is too sparse. It fails to provide enough context for an AI agent to understand when to use this tool vs others like get_campus_card_balances.

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 with 100% schema coverage, so the description does not need to add parameter details. Baseline 4 is appropriate as there is nothing to compensate for.

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 gets 'USC CarolinaCard meal-swipe rules' and mentions usage by 'optimizer tools,' which distinguishes it from sibling tools like estimate_usc_retail_swipe_value. However, it does not explicitly contrast with other get tools, missing full differentiation.

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?

No guidance on when to use this tool versus alternatives. The phrase 'used by optimizer tools' implies a specific context but does not provide explicit when-to-use or when-not-to-use instructions.

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