sports-prediction

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

With no annotations, the description carries the full burden. It discloses the data source (ESPN public API), that no key is required, and the cost ($0.005/call). It also lists the returned fields. However, it does not mention error handling, rate limits, or behavior on invalid input, which would improve transparency. Overall, it provides good disclosure for a read-only tool.

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 concise: 4 sentences covering purpose, supported sports, source, cost, and usage context. It is front-loaded with the primary action and avoids unnecessary words. Every sentence adds value.

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 tool's simplicity (3 optional parameters, no output schema), the description covers the key aspects: what it returns (games with records, venue, time, score), supported sports, source, cost, and when to use it. It could mention the output structure or error handling, but it provides sufficient context for an agent to understand its purpose and usage.

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 baseline is 3. The description repeats the supported sport codes and mentions the default for date (today UTC), which are already in the schema with similar detail. It does not add new parameter-level information beyond what the schema provides, but it does reinforce the context.

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 returns sports games with team win-loss records, venue, scheduled time, and live scores for a given date. It explicitly lists supported leagues (MLB, NBA, etc.) and mentions the use case (before prediction-markets tasks). This distinguishes it from similar tools like 'sports-scores' by emphasizing richer context.

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 provides a clear usage context: 'Use before prediction-markets or sports-content tasks to get accurate team context.' This tells the agent when to invoke it. It does not explicitly mention when not to use it or name alternatives like 'sports-scores', but the guidance is specific and helpful.

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