Cross-venue prediction-market statistics

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

Annotations already indicate read-only and non-destructive behavior. The description adds valuable transparency: volume reporting basis, real-money venue scope, self-computed aggregates requiring citation, and a link to methodology.

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 a single paragraph of four sentences, front-loaded with purpose, followed by essential caveats. No redundant wording, and every sentence adds value.

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 the tool's simplicity (one optional param, output schema exists), the description covers inputs, output types, venue scope, and usage terms. It is complete enough for an agent to select and use the tool correctly.

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?

Only one optional parameter (fiat) with 100% schema coverage. The description adds context about monetary figures being real-money only and volume basis, which indirectly aids parameter understanding, but the schema already defines the parameter adequately.

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 precisely states the tool provides cross-venue prediction-market statistics including counts, volume, and liquidity, with a specific list of venues. It clearly distinguishes from sibling tools like pm_data_event or pm_data_whales.

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 explains that the tool is free and public, and that no API key is required, implying easy access for overview statistics. However, it does not explicitly contrast with sibling tools or provide when-not-to-use guidance.

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