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

Annotations already indicate read-only, idempotent, and non-destructive behavior. The description goes further by detailing cost ($0.005 USDC), payment challenge behavior for unpaid calls, and the 'no data no cost' guarantee, which are critical operational details not covered by annotations.

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 well-structured: it starts with the core action, then explains the use case, and finally covers cost and HTTP equivalent. It packs necessary detail (output fields, pricing behavior) without unnecessary fluff, making it efficient and easy to parse.

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?

Despite lacking an output schema, the description enumerates all returned fields (question, Gamma id, condition id, outcomes with prices, best bid/ask, etc.) and explains payment/response edge cases. This gives the agent a complete picture of what to expect, fulfilling the contextual needs.

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 provides 100% coverage with descriptions and examples for all four parameters. While the description mentions ordering by volume/liquidity, it does not add significant meaning beyond the schema's existing parameter descriptions, so the baseline score of 3 is appropriate.

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 primary function: to list live Polymarket markets with detailed fields like question, Gamma id, condition id, outcomes, prices, and liquidity. It also distinguishes this from sibling tools by focusing on market lists ordered by volume/liquidity, 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 provides a concrete use case ('see what the largest real-money prediction markets are pricing right now') and implies this is the go-to for listing markets. However, it does not explicitly contrast with sibling tools like polymarket_events or prediction_market_search, so the guidance could be more direct.

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