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

Annotations already signal read-only, open-world, idempotent, and non-destructive behavior. The description adds important context beyond those annotations: the labels object is mechanical, not an evaluation of trader skill, and must not be restated as judgment; the result includes provenance with feed endpoint and fetch time; and rendering as a sortable table is disclosed.

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 front-loaded with the core purpose in the first sentence, then layers essential detail about labels, provenance, and rendering. Every sentence adds value, especially the critical disclaimer about labels not being judgments, with zero filler.

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?

There is no output schema, so the description carries the burden of explaining what the result contains. It covers row-level labels, their mechanical meaning, the provenance field, and rendering behavior. Combined with the fully documented parameters, an agent has enough context to invoke and interpret the tool correctly.

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 has 100% description coverage and clearly documents limit, metric, window, and response_format with enums and defaults. The description adds no meaningful parameter-level semantics beyond what the schema already provides, so the baseline 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 opens with a specific verb and resource: 'Top Hyperliquid traders ranked by PnL, ROI, volume, and account value across time windows.' This directly states what the tool returns and the ranking dimensions, and the title plus the leaderboard concept clearly separate it from the analytics, liquidation, and wallet sibling 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?

The description makes the use case clear: get a ranked leaderboard of top traders with selectable metrics and time windows. It does not explicitly name sibling alternatives or state when not to use this tool, but the context is strong enough for an agent to infer the appropriate scenario.

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