Regime

Leaderboard rank check

leaderboard_rank_check

Read-onlyIdempotent

How much company a return has. Send a return (+340%) and a window (day, week, month or all time) and get how many accounts on Hyperliquid's whole public leaderboard did the same or better, out of how many traded, its percentile, and the median account next to it. Every row of the exchange's own table, refreshed daily; the denominator is the accounts that traded, not the ones that sat idle.

Use when a trader or an ad quotes a return ("+340% this month") and you want to know how rare it is. Hyperliquid accounts only. Whether last month's top accounts stay on top is copy_trading_check; whether luck explains a win rate, overfitting_odds.

Input Schema

Name	Required	Description	Default
`window`	Yes	day, week, month (default) or allTime.	month
`return_pct`	Yes	In percent: 340 means +340%.

Output Schema

Name	Required	Description
`ok`	No	false when we do not hold that data. Never a zero standing in for an answer.
`error`	No	no_data when ok is false.
`model`	No	The method, stated.
`one_in`	No	One account in how many.
`reason`	No	Why, in one sentence, and what we do have instead.
`source`	No	The public file these numbers come from.
`percentile`	No	Share of accounts below it.
`try_instead`	No	When ok is false: the closest call that does answer, ready to send (tool, arguments, and what changed).
`same_coin_in`	No	When ok is false because this tool lacks the coin: the other tools that hold it, each with arguments ready to send.
`same_or_better`	No	Accounts at that return or above.
`median_return_pct`	No	The middle account, same window.
`share_in_profit_pct`	No	Accounts in profit, same window.
`accounts_that_traded`	No	The denominator.

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedOct 15, 2026

addedInput schema / examples

Added value: +[
+  {
+    "return_pct": 340
+  }
+]

addedOutput schema / properties / same_coin_in

Added value: +{
+  "description": "When ok is false because this tool lacks the coin: the other tools that hold it, each with arguments ready to send.",
+  "type": "array"
+}

addedOutput schema / properties / try_instead

Added value: +{
+  "description": "When ok is false: the closest call that does answer, ready to send (tool, arguments, and what changed).",
+  "type": "object"
+}

Changed2 schema fields changedOct 2, 2026
- addedInput schema / properties / window / default
```
Added value: +"month"
```
- addedInput schema / properties / window / enum
```
Added value: +[
+  "day",
+  "week",
+  "month",
+  "allTime"
+]
```
First observedOct 1, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Annotations already cover the read-only/idempotent/non-destructive profile, yet the description adds substantial context beyond them: the data source is the exchange's own full public table, refreshed daily, and the denominator is accounts that traded rather than idle ones. These are exactly the behavioral facts an agent cannot infer from annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loads the core computation and keeps the usage guidance in a separate paragraph. The opening fragment 'How much company a return has' is slightly cryptic and the parentheticals make it denser than necessary, but there is little outright waste.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present the description needn't enumerate return values, yet it still conveys source, freshness, denominator semantics, and sibling boundaries. Nothing an agent needs to select or invoke the tool correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, and the schema already documents both parameters including the '+340%' example and the window enum, so the description's '+340%' and window list add little beyond what the schema provides. Baseline 3 is appropriate when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific computation (given a return and window, how many leaderboard accounts did the same or better, out of how many traded, plus percentile and median) rather than restating the name. It explicitly differentiates from siblings by naming copy_trading_check and overfitting_odds as different questions.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives an explicit trigger ('Use when a trader or an ad quotes a return and you want to know how rare it is') and routes the agent away from two named alternatives. The scope limit ('Hyperliquid accounts only') further constrains correct use.

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

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