get_prediction_odds

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

With no annotations, description carries full burden. It discloses that it returns up to 'limit' active markets with specific fields and that data is crowd-sourced. Lacks details on error handling, pagination, or rate limits.

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?

Description is concise, well-structured, and front-loaded. Each sentence serves a purpose: purpose, usage, return values, caveat, and example. No wasted words.

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?

Given simple parameters and no output schema, description covers the main return fields and data source. It lacks detail on return format (e.g., is it a list?) and error conditions, but suffices for basic usage.

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 coverage is 0%, but description adds meaning by explaining 'limit' controls number of results and providing an example usage. It does not explicitly define 'query' but context makes it clear.

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 it searches Polymarket for probability estimates, specifying the resource (Polymarket) and action (search). It provides a usage scenario (user asks 'what are the odds of X?'), which helps differentiate from siblings like get_prediction_event_by_id, but does not explicitly contrast.

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?

Explicitly says to use when user asks 'what are the odds of X?' for macro events, and notes data is crowd-sourced. However, it does not mention when not to use or compare with alternatives.

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