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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds meaningful behavioral context: the data is live, sourced from a regulated exchange, expressed in cents as implied probabilities, and carries legal/advice caveats. No contradiction with annotations.

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 deliver the core purpose, an interpretation rule, and necessary caveats without waste. The most important information is front-loaded, and every sentence earns its place.

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 odds tool with no output schema, the description explains the data source, the meaning of the numeric output, and the comparison purpose. It doesn't specify error cases or the exact response shape, but those are minor given the simple two-parameter request and read-only annotation.

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?

Input schema has 100% coverage with clear examples for both required parameters, so the baseline applies. The description doesn't add parameter-level detail beyond the schema, though it does clarify how the returned values should be interpreted.

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 a specific action — retrieving live prediction-market prices from Kalshi — and clearly identifies the resource as cricket match odds. It also distinguishes itself from the server's own win probability, separating it from sibling tools like cricket_win_probability without ambiguity.

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?

It conveys the use case: comparing live market prices against this server's own win probability, which implies when to select this tool over a probability-only tool. However, it doesn't explicitly name sibling tools or state when not to use it, so it stops short of full exclusionary guidance.

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