Prediction-market venue methodology and coverage

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

Beyond the annotations (readOnlyHint, destructiveHint), the description adds concrete behavioral context: it is free, requires no API key, and covers every venue with explicit bases. It also discloses the risk of misinterpreting data, which is valuable context for invocation.

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 three sentences and every sentence adds value: the first lists the content, the second provides usage guidance, and the third notes access. It is well-structured and front-loaded.

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?

Given that an output schema exists and the annotations declare read-only, non-destructive behavior, the description sufficiently covers what the tool does, when to use it, and key caveats. It does not need to explain return values because the output schema is present.

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 input schema contains one optional 'fiat' parameter with its own description, and schema coverage is 100%. The tool description does not mention parameters, but the schema already fully defines them, so baseline 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 that the tool provides 'methodology and comparable coverage' for prediction-market venues, enumerating specific data elements such as source kind, supported metrics, market counts, volume bases, currency basis, comparability, and as-of timestamps. This distinguishes it from sibling tools like pm_data_health or pm_data_overview.

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 explicitly instructs to 'Use this before comparing venue totals' and warns against mislabeling completed-day figures as rolling 24h or play-money as USD. It does not name alternative tools or state when not to use it, but the usage context is clear.

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