ncaa_get_rankings

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

No annotations are provided, so the description carries the full burden of disclosing behavioral traits. It only states what the tool does (get rankings) without mentioning any potential side effects, data freshness, rate limits, or permissions. As a read operation, minimal disclosure is acceptable, but the lack of any behavioral context beyond the action itself earns a low score.

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 sentence that efficiently conveys the tool's purpose with examples, containing no unnecessary words or repetition. It is well-structured for quick comprehension.

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?

While the description covers the basic purpose, it lacks details about the response format (no output schema) and provides no guidance on optional versus required parameters beyond what the schema specifies. Given the tool's five parameters, a more complete description would enhance usability, but it remains minimally adequate.

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?

All five parameters have descriptions in the input schema (100% coverage), so the description adds no additional meaning beyond what the schema already provides. The baseline score of 3 applies, as the description does not improve parameter understanding.

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 action ('Get'), the resource ('NCAA rankings/polls'), and provides examples (AP, Coaches, CFP), making the purpose unmistakable. It also distinguishes from sibling NCAA tools like ncaa_get_game or ncaa_get_schedule by focusing specifically on rankings.

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 lists poll examples but does not explicitly state when to use this tool versus alternatives (e.g., ncaa_get_standings for standings data). Usage context is implied but not clearly delineated, leaving the agent to infer without guidance.

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