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

With no annotations, the description carries the full burden, and it usefully discloses the providers and that values are live real-money implied probabilities expressed in percent. It says nothing about freshness/latency, rate limits, or whether odds from the two sources are merged or returned separately, which is a real gap for a market-data tool.

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 leads with the verb and resource, wastes no words, and packs source, data type, and domain coverage into one readable line.

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 two-parameter, annotation-free read query with no output schema, the description conveys the essential idea of the return (odds plus implied probability percentages) and where the data comes from. It stops short of describing result shape, freshness, or multi-source handling, which are minor but not fully covered.

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 'query' and 'limit' are already documented in the schema, and the description adds no syntax, example, or range detail beyond it. Baseline 3 applies when the structured 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?

States a specific verb (Query) plus resource (live prediction market odds and real-money implied probabilities) and names the two data sources, Polymarket and Manifold Markets. The domain enumeration (crypto, macro, political, tech) also separates it cleanly from siblings like defi_yields, token_alpha, or social_search, so an agent can pick it without opening the schema.

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 domain list ('any crypto, macro-economic, political, or technology event') gives clear context for when the tool applies. However, it names no alternatives and includes no when-not guidance, so the agent must still infer that this is not the tool for on-chain yields or raw token metrics.

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