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

Annotations already declare readOnlyHint and openWorldHint, and the description adds genuinely non-structured context: append-only same-timestamp receipts, deterministic scoring at resolution, Brier scores for AI and market, and the fact that losses are published. This is real behavioral/methodological disclosure beyond the annotations, though it doesn't discuss freshness or pagination.

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 purpose and the use-triggers are front-loaded, and the closing sentence on auditable losses reinforces (rather than repeats) the value proposition. It is slightly longer than strictly necessary but every sentence carries information.

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?

With no parameters and an output schema that covers return structure, the description supplies exactly the missing context: what the record contains, how it is scored, and that it is uncurated. Nothing needed to call or interpret the tool is absent.

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 tool takes zero parameters, so the schema has nothing to document and the baseline is 4. The description correctly implies a parameterless, aggregate look-up rather than a per-entity query.

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?

States a specific verb ('Get') plus a precisely scoped resource ('VoxOdds' audited AI-vs-market forecast track record'), which is distinguishable from the sibling get_forecaster_record. An agent can tell what data is returned without opening the schema.

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?

Gives explicit trigger conditions ('when the user asks whether AI forecasts beat prediction markets, how reliable VoxOdds' AI is, or for citable forecasting-performance data'), which is strong when-to-use guidance. It does not name a sibling alternative or an exclusion (e.g., vs get_forecaster_record), so it falls short of a 5.

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