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

With no annotations, the description carries the burden of disclosing behavior. It accurately implies a read-only search operation but does not mention result ordering, pagination, or that it returns only matching markets. This is adequate for a simple search tool but lacks explicit safety or performance details.

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 sentence that immediately communicates the tool's function and input type. No filler or redundant 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?

The description is sufficient for a simple 2-parameter search tool, but since there is no output schema, it would be helpful to mention what the response contains (e.g., market IDs, titles, probabilities). Without that, the agent may not know what to expect.

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 describes both parameters (query and limit) with 100% coverage. The description adds semantic value by specifying that the query accepts natural language, not just keywords—which goes beyond the schema's 'Search query' placeholder.

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 identifies the action ('Search'), the resource ('prediction markets'), and the scope ('500+'). It also distinguishes from sibling tools like list_markets by emphasizing keyword or natural language querying, making its purpose unambiguous.

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 gives clear context for when to use this tool: when searching markets by keyword or natural language. It does not explicitly mention when not to use it or name alternative tools like list_markets for browsing, so it falls short of a 5.

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