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

With no annotations, the description carries the burden of behavioral disclosure. It explains the normalized output and preservation of raw venue fields, but does not mention async behavior (though it's in the schema), rate limits, or error handling. It adds some value but is not exhaustive.

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 two concise sentences, front-loaded with the action, and efficiently conveys the key benefit and output format without unnecessary detail.

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?

The tool has no output schema and no annotations, but the description provides a clear output structure and the primary use case. It lacks mention of async execution and result behaviors like pagination, but overall it is adequate for a search tool with a well-described schema.

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%, and each parameter has a clear description in the schema. The tool description does not add parameter-specific meaning beyond the schema, so the baseline of 3 is appropriate.

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's function: search live prediction markets across Polymarket and Kalshi in one call, with a normalized output shape. It distinguishes itself from single-venue siblings by emphasizing the cross-venue normalization and listing the returned fields.

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 implies usage for queries spanning both venues and needing normalized data, but it does not explicitly mention alternatives or when not to use it. The 'in one call' phrasing suggests a preference over separate venue calls, but no explicit exclusion is provided.

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