get_predictions

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

With no annotations, the description carries the full burden of behavioral disclosure. It implies a read-only operation by saying 'Upcoming predictions', but does not explicitly state that no modifications occur, nor does it mention authentication, rate limits, or pagination. It adds some behavioral context (returns probabilities and edge) but lacks explicit safety or side-effect disclosure.

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?

A single, front-loaded sentence with no superfluous words. It starts with the core purpose ('Upcoming predictions') and then specifies the included data. This is efficient and well-structured, making it easy for an agent to quickly grasp the tool's function.

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 read-only tool with two optional parameters and no output schema, the description covers the essential return content. However, it lacks context about how this tool relates to siblings (e.g., whether predictions overlap with value bets) and does not clarify the meaning of 'model-vs-market edge'. Adding a brief usage note would improve completeness, but as-is it is mostly 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?

The schema covers both parameters (limit and league) with descriptions, achieving 100% coverage. The tool description does not add any additional semantic meaning beyond the schema, which is acceptable given the schema's clarity. The baseline of 3 is appropriate because the schema already handles parameter explanation adequately.

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 resource ('Upcoming predictions') and the specific data included ('probabilities and model-vs-market edge'). It is a full sentence with a specific verb inferred from the name. While it doesn't explicitly name a sibling to differentiate, the content distinguishes it from related tools like value bets or arbs by focusing on predictions with edge.

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?

There is no guidance on when to use this tool versus alternatives such as get_value_bets or get_arbs. The description does not provide any context about selection criteria, prerequisites, or scenarios where this tool is preferred. This leaves an agent to infer usage, which is a significant gap.

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