get_event_predictions

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

Annotations already provide readOnlyHint and idempotentHint. The description adds that availability and field structure vary, and some events return null or partial data. This supplements the annotations with important behavioral context.

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?

Three sentences efficiently convey purpose, return format, and caveats. No unnecessary words. The description is front-loaded with the main purpose.

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 one parameter and no output schema, the description covers return structure, variability, and key discovery. It could mention that results are TBA-generated and what 'partial data' entails, but overall it is sufficient.

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 single parameter event_key has 100% schema coverage, and the description adds significant meaning: it explains the key format (season year + event code), provides examples, and directs to get_events or get_events_keys for discovery. This goes well beyond the baseline.

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 it retrieves match score predictions and ranking predictions for an event, specifying the return format (keyed by match key and team key). It distinguishes itself from sibling tools like get_event_rankings or get_event_oprs by focusing on predictions.

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 indicates predictions are available 'when computed' and notes variability by event and year. It does not explicitly mention when not to use or suggest alternatives, but the context is clear enough for an agent to infer appropriate usage.

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