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

With no annotations provided, the description carries full burden for behavioral disclosure. While 'Get' implies a read operation, it doesn't specify whether this requires authentication, has rate limits, returns real-time or historical data, or what format the output takes. For a data retrieval tool with zero annotation coverage, this represents significant gaps in behavioral context.

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 extremely concise - a single sentence that efficiently communicates the core functionality. Every word earns its place by specifying the action, resource, and sources. There's no redundancy or unnecessary elaboration, making it easy for an agent to parse quickly.

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 tool that retrieves data from multiple prediction market platforms with no annotations and no output schema, the description is insufficient. It doesn't explain what format the prices come in, whether it returns all markets matching the keyword or just some, how results from different platforms are organized, or any error conditions. The agent lacks critical context to understand what to expect from using this tool.

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 schema description coverage is 100%, with the single parameter 'keyword' well-documented in the schema. The description doesn't add any parameter-specific information beyond what's already in the schema. This meets the baseline expectation when the schema does the heavy lifting, but doesn't provide additional semantic context about how the keyword parameter affects results across the different platforms.

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 action ('Get') and resource ('prediction market prices') with specific sources listed (Polymarket, PredictIt, Kalshi). It distinguishes this as a data retrieval operation rather than creation or modification. However, without sibling tools, we cannot assess differentiation from alternatives, preventing a perfect score.

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 provides no guidance on when to use this tool versus alternatives, prerequisites, or limitations. It simply states what the tool does without context about appropriate use cases or constraints. This leaves the agent with insufficient information to make informed decisions about tool selection.

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