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

Annotations already establish read-only, idempotent, non-destructive behavior, and the description aligns with those. It adds valuable behavioral context beyond annotations: the cost model, the free first cached result, x402 payment requirement, and the disclaimer that this is event-probability context only.

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?

Three sentences with no redundancy: the first states the data scope, the second sets expectations, and the third explains cost. The most decision-relevant facts are front-loaded.

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 simple, read-only tool with one optional parameter and no output schema, the description covers the key output fields and the payment behavior. It lacks exact output formatting and details on "eligible cached intelligence," but those are minor given the tool's simplicity.

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 description coverage is 100% for the single optional x_payment parameter, so the schema already documents the payment flow. The description adds cost-related context but no additional parameter syntax or format, matching the baseline for high schema coverage.

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 names a specific verb and resource: "Read the highest-volume open Polymarket markets" with concrete data fields like probabilities, liquidity, volume, and end dates. It clearly conveys the tool's core purpose, though it does not explicitly differentiate itself from sibling tools like otto_pm_crypto.

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 implies usage context by covering live event-probability data and explicitly states "not a recommendation." However, it does not say when to prefer this tool over siblings or when not to use it, leaving some routing decisions to inference.

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