pulse_biggest_trades

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

No annotations are provided, so the description carries the full burden. It discloses that the tool covers all of Hyperliquid and the criteria for biggest trades, but lacks details on data freshness, rate limits, or performance characteristics. This is adequate but not thorough.

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 composed of two concise, front-loaded sentences. It efficiently conveys purpose and usage without unnecessary 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?

For a tool with 4 parameters and no output schema, the description provides enough context to understand what the tool does and when to use it. It briefly mentions the return format (toon format) via the schema, but could be more explicit about output structure. Overall, it is complete for the tool's complexity.

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%, so the baseline is 3. The description adds a minor elaboration on the type parameter (market sentiment) and the use case, but does not significantly enhance the schema's own descriptions.

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 retrieves the biggest winning or losing trades across all of Hyperliquid, with explicit examples using type='wins' or 'losses'. It distinguishes itself from sibling pulse_* tools by focusing on extreme trades for market sentiment and narrative analysis.

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 context for when to use this tool—market sentiment and narrative analysis—and explains the type parameter's role. It does not explicitly state when not to use or mention alternatives, but the context is clear enough for the intended use.

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