Regime

Copy trading check

copy_trading_check

Read-onlyIdempotent

Whether copying the top traders works, measured. Accounts in the top 10% or 1% of Hyperliquid one month, by return or by dollar profit: how many were in the top again the next month, next to chance, how many fell to the bottom instead, and how many made money the month you would have copied them for, next to every active account. 4,000 accounts sampled at random, not today's leaders; about 30 month pairs.

Use when someone proposes copying top traders, a leaderboard or signal leaders. Takes no account address. To place one specific return on the leaderboard use leaderboard_rank_check; to ask whether luck explains a record, overfitting_odds.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`top_pct`	Yes	10 (default) or 1. 0.1 is read as 10.
`ranked_by`	Yes	return (default) or profit.	return

Output Schema

TableJSON 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.
`reason`	No	Why, in one sentence, and what we do have instead.
`source`	No	The public file these numbers come from.
`repeated`	No	Of those, times it was in the top again next month.
`chance_pct`	No	What picking accounts at random gives. The alternative, always.
`repeated_pct`	No	The same as a share.
`times_in_top`	No	Times an account finished a month in the top group.
`stopped_trading`	No	Counted as not repeating.
`fell_to_bottom_pct`	No	Share that fell to the bottom group instead: the size control.
`in_profit_next_month_pct`	No	Share that made money the next month.
`in_profit_next_month_all_accounts_pct`	No	The same for every active account.

Schema Changelog

Changes observed during successful MCP inspections.

Changed4 schema fields changedOct 2, 2026
- addedInput schema / properties / ranked_by / default
```
Added value: +"return"
```
- addedInput schema / properties / ranked_by / enum
```
Added value: +[
+  "return",
+  "profit"
+]
```
- addedInput schema / properties / top_pct / default
```
Added value: +10
```
- addedInput schema / properties / top_pct / enum
```
Added value: +[
+  10,
+  1
+]
```
First observedOct 1, 2026

TDQS

A4.6/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so the safety profile is covered. The description adds genuinely useful scope context the annotations cannot: no account address is required, the sample is 4,000 random accounts rather than today's leaders, and the horizon is ~30 month pairs. It stops short of describing return format or pagination, but the output schema likely covers results.

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?

Structure is correct — what it measures first, then the use-when and alternatives in a clearly separated paragraph. The opening sentence and the run-on enumeration of metrics are dense and slightly redundant given an output schema exists, but each clause carries real information.

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?

For a statistical-analysis tool with a full annotation set and an output schema, the description supplies everything the agent needs: the exact question answered, the data scope, the no-address constraint, the trigger condition, and the two sibling alternatives. Return values are correctly left to the output schema.

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

Parameters4/5

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

Schema coverage is 100% and both params are enums with descriptions, so the baseline is 3. The description modestly enriches meaning by spelling out the semantics behind the choices ('top 10% or 1%', 'by return or by dollar profit'), but adds no format or edge-case detail beyond that.

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?

The description names the specific analytic question (does copying top traders persist?) and the exact population measured (Hyperliquid top 10%/1% by return or dollar profit, 4,000 random accounts, ~30 month pairs). It explicitly distinguishes itself from leaderboard_rank_check and overfitting_odds, so an agent can route correctly without opening a schema.

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?

It gives a concrete trigger ('Use when someone proposes copying top traders, a leaderboard or signal leaders') and names two alternatives with the conditions that select them (a single return -> leaderboard_rank_check; is luck the explanation -> overfitting_odds). When-to-use, when-not, and alternatives are all present.

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

All Regime tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources

Need Help?