Get prediction-market event detail

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

The description reveals that the default summary bounds outputs for agent context windows while preserving counts and core evidence, a behavior not visible in annotations. It also clarifies referenceProbability quoting conventions and that the tool is free and public, adding value beyond readOnlyHint and openWorldHint.

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 longer than the calibration examples but every clause carries operational value—listing return fields, explaining crossSourceMatches, and providing quoting guidance. It is front-loaded with the core purpose and uses clear sectioning through dashes, though it could be tightened.

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 description covers the purpose, output fields, behavioral constraints (summary/full), the relationship to pm_quote, and the absence of auth requirements. With an output schema present and four parameters documented, the description provides sufficient context for an agent to decide when and how to invoke.

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?

All four parameters are already fully described in the schema (100% coverage), so the description adds limited new parameter meaning. It does reinforce that source+slug identify the event and that detail defaults to summary, but this is consistent with the schema.

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 opens with 'Free public detail for one prediction-market event by venue + slug' and lists specific data returned, clearly distinguishing it from list-style siblings like pm_data_events. It also separates itself from pm_quote by labeling itself the 'cross-venue research view.'

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 states this is the 'cross-venue research view' and directs users to pm_quote for tradability. It also explains when to use detail=full versus the default summary, and notes no API key is required. It does not exhaustively enumerate all sibling alternatives, but the guidance is practical and sufficient.

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