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

Since no annotations are provided, the description carries the full burden. It discloses behavioral nuances: for broad topics it returns 'EVERY open market it can find' rather than a top slice, and history=true includes resolved markets with final odds. It does not mention response size limits or error behavior, but for a read-only data tool, the disclosed behavior is adequate.

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 dense paragraph with each sentence serving a purpose: definition, use cases, history explanation, query guidance, and broad-topic behavior. It is slightly longer than strictly necessary but contains no filler; the admonitions and examples make it practical.

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 sufficiently explains what is returned (odds, volume, liquidity, resolution date, related markets) and addresses the trickiest case (broad topics returning all open markets). It does not cover pagination, rate limits, or error scenarios, but the tool is conceptually simple with only two optional parameters and the guidance is otherwise complete.

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?

The input schema already has descriptions for both parameters (100% coverage), setting a baseline of 3. The description adds extra value by coaching usage: 'ALWAYS pass the subject the user named as query', examples of valid queries, and the specific condition for omitting query. This goes beyond the schema's static descriptions.

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 clearly states the tool's purpose with a specific verb ('returns') and resource ('LIVE prediction-market data from Polymarket'), listing concrete outputs (implied odds, volume, liquidity, resolution date, related markets). It distinguishes itself from sibling tools (e.g., stock movers, security checks) by focusing solely on prediction markets.

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?

Provides explicit when-to-use guidance with example queries ('what are the odds of X'), explains when to set history=true for past/settled questions, and gives clear rules for the query parameter (always pass the subject, omit only when user asks generically). Includes a concrete example ('nba markets' -> query='NBA') and clarifies broad-topic behavior.

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