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

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety and world-access are covered by structured data. The description adds real behavioral context beyond that: results are ordered by 24h volume and are limited to live markets, which shapes how an agent interprets the output. It stops short of describing pagination or result count behavior.

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?

Four tight sentences with zero filler; the primary purpose and ordering are front-loaded, then filters, then the sibling routing. Every sentence earns its place.

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 read-only browsing tool with an output schema already defining return values and annotations covering safety, the description supplies everything else an agent needs: ordering, filter semantics, and the alternative tool. No meaningful gap remains.

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 limit, search and category are already documented in the schema. The description restates the category enum values and clarifies that search matches the market question, which is useful but largely duplicates structured data. Baseline 3 applies 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?

States a specific verb (List), resource (live prediction markets) and ordering (by 24h volume), which immediately separates it from get_market_odds and the quote-fetching siblings. An agent can tell this is a browsing/list tool 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?

Gives two explicit use cases ('browse what the market is pricing right now' or 'find a specific market') and names the alternative with its selecting condition: 'to answer a specific question about one event use get_market_odds.' Nothing is left to inference.

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