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

Annotations already declare readOnly/idempotent/non-destructive/openWorld=false, and the description adds substantive, non-obvious semantics: roi_pct is window realized PnL over the CURRENT whole-account value (including native, builder and off-account USDC), while max_drawdown_pct is all-time and account-level. It also discloses null behavior when equity history is insufficient. The phrase 'and for those two modes' is left undefined, which is the main transparency gap.

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?

Purpose and example queries are front-loaded, and the caveats about metric definitions follow logically. The final sentence is dense and carries an underspecified clause ('those two modes'), and the vike.io pipeline attribution is of marginal value to an agent choosing a tool.

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?

With 7 optional parameters and no output schema, the description does a good job of defining the metrics an agent will rank by and filter on, which effectively previews the key returned fields. It does not sketch the returned record structure or describe ordering/pagination beyond the schema's size limit, which is the remaining gap.

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 coverage is 100%, so the baseline is 3, but the description adds meaning the schema does not: it defines what the 'roi' and 'drawdown' sort enum values actually compute and confirms win_rate is on a 0-100 scale. It leaves the remaining enum values (account_value, long_pnl, short_pnl) and filter interaction behavior undefined.

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 first sentence gives a specific verb (rank) plus the exact resource (Hyperliquid perp wallets) and the rankable metrics, so the tool's function is unmistakable. It does not explicitly differentiate itself from close siblings such as hl_leaderboard or hl_cohort_metrics, which leaves some overlap for the agent to disambiguate.

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?

Concrete example queries ('top HL traders with win rate > 75%', 'best HL perp wallets last 7d') make the intended use case clear and demonstrate how filters combine. There is no explicit when-not guidance or named alternative for overlapping goals like cohort metrics or a single-wallet lookup.

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