Biggest Trades

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

Annotations already carry readOnlyHint=true and idempotentHint=true, so the description adds limited behavioral context: it confirms cross-exchange scope and the wins/losses split but does not describe sorting, result shape, or edge cases like empty thresholds. No contradiction with 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?

Three short sentences, each earning its place: scope, parameter guidance, and use case. No redundancy or filler; key information is 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 read-only list tool with fully documented parameters, the only notable omissions are return-value shape and explicit sorting direction, but 'biggest' plus schema parameters make behavior inferable. It's nearly complete.

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%, with each parameter fully documented (type enum, limit bounds/default, threshold semantics, useToonFormat). The description only adds reiteration of the type parameter, so it doesn't meaningfully raise the baseline of 3.

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?

Description opens with a specific verb and resource ('Get the biggest winning or losing trades across all of Hyperliquid'), then clarifies the type parameter meaning. This establishes a clear scope distinct from sibling trade-volume or liquidation tools.

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?

States an explicit use case ('market sentiment and narrative analysis') that tells an agent when this is appropriate, but it does not mention alternatives or exclusions relative to nearby siblings like pulse_recent_trades or pulse_top_liquidators.

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