prediction_markets

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

Annotations already declare readOnly, idempotent, openWorld, and non-destructive, so the safety profile is covered. The description adds genuine context beyond that: the data is live, sourced from two named venues, and expressed as real-money implied probabilities in percent. It stops short of noting refresh cadence or coverage limits per venue.

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?

A single front-loaded sentence that packs verb, data type, sources, and domain coverage with no filler or redundancy. Nothing could be removed without losing information.

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?

With no output schema, the description usefully states the return units (percent implied probability) and the sources, which is the key missing piece for interpreting results. It could go further by describing result ordering or how multiple markets per query are ranked.

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 description coverage is 100%, so both parameters (query, limit) are fully documented with examples and bounds in the schema. The description adds no parameter-level detail of its own, which is the expected baseline when the schema does the heavy lifting.

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?

Specific verb (Query) plus a precisely scoped resource (live prediction market odds & implied probabilities) with named sources (Polymarket, Manifold) and supported domains (crypto, macro, political, tech). No sibling tool covers prediction markets, so it is unambiguously distinguishable.

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 implies when the tool is useful (any event with market-implied odds) but gives no explicit when-to-use vs. alternatives, no exclusions, and no guidance on how it relates to siblings like domain_intel or social_search. Usage is inferable rather than stated.

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