race_predictions

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

With no annotations provided, the description must disclose behaviors. It only states the output (predicted results) but does not explain how predictions are derived, what input data is needed (e.g., historical runs, VO2max), or the meaning of the start and end parameters. The agent is left guessing about side effects, data requirements, or constraints.

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 very short—a single line—which is concise. However, it provides only the barest information and lacks structure (e.g., parameter descriptions, usage examples). It is under-specified rather than efficiently complete.

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 presence of an output schema but zero schema coverage for parameters, the description should compensate by explaining parameter semantics and usage context. It does not. The tool has many siblings, yet no differentiation or guidance is provided. The description is far from complete for effective tool invocation.

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 0% and the description does not mention the start and end parameters. The agent has no semantic hints about what these string fields represent (e.g., date range, race names, distance filters). This is a critical gap for a tool with two undocumented parameters.

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 states the tool provides predicted race times for 5K, 10K, half marathon, and full marathon. This gives a specific verb (predict) and resource (race times). The purpose is clear and distinct from siblings like vo2max or get_endurance_score. However, the description is in Chinese, which may reduce clarity for non-Chinese agents, and it does not explicitly distinguish itself from related tools.

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 offers no guidance on when to use this tool versus alternatives such as personal_record or get_endurance_score. It does not mention prerequisites, required data, or typical use cases. An agent would have to infer context from the name alone.

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