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

Annotations already establish read-only, non-destructive, open-world behavior. The description adds meaningful context beyond them: prices are live and "never estimated," the data is free and needs no key, and it enumerates the payload (each leg's price, volume and link, seat holder and rating, forecaster bands, race page) in the absence of an output schema.

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?

Front-loads the use case, then the data scope, then the payload and cost guarantees. Dense but every clause carries information; the long enumeration of returned fields is the only mildly run-on element.

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 one-parameter, no-output-schema tool this covers everything an agent needs: what it fetches, the accepted race identifiers, the races in scope, that prices are live rather than modeled, and that no key is required.

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 coverage is 100% and the single parameter's description already lists state name/code, slug, and district formats. The description repeats the same examples ("TX-34") without adding syntax, matching, or ambiguity-resolution rules, so it neither compensates nor regresses — baseline 3.

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 concrete verb and resource: live Kalshi odds for one 2026 Senate, governor, or competitive House race. Scoping to a single race clearly separates it from map-level siblings like senate_map, and the sample queries ("who wins the Kansas Senate race") make the intent unambiguous.

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?

Opens with explicit "Use for" trigger phrases, giving clear context for when this tool is the right pick. It stops short of naming alternatives or exclusions (e.g. when to use senate_map instead of a single-race lookup), which is the only missing piece.

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