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

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

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.
`try_instead`	No	When ok is false: the closest call that does answer, ready to send (tool, arguments, and what changed).
`repeated_pct`	No	The same as a share.
`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.
`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.

Changed3 schema fields changedOct 15, 2026

addedInput schema / examples
```
Added value: +[
+  {}
+]
```

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"
+}

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 cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the description's added value is methodology: 4,000 randomly sampled accounts, not today's leaders, ~30 month pairs, and the comparison baselines (chance, bottom bucket, all active accounts). That tells the agent what the result actually represents and guards against misreading it as a live-leaderboard query. It does not mention cost/latency or caching, so a 4 rather than 5.

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-loaded with the core question, then methodology, then usage and alternatives in a clearly separated second paragraph. The methodology sentence is long and packs several clauses, but each clause (sample size, sampling frame, month pairs, comparison groups) carries distinct meaning rather than filler.

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?

An output schema exists, so return-shape explanation is unnecessary; what the agent does need — the analytical question, the sampling basis, the comparison baselines, when to invoke, and which siblings to use instead — is all present. Nothing required to call this correctly is missing.

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 enums are self-documented, so the baseline is 3. The description adds meaning beyond the schema by clarifying the negative space ('takes no account address') and by enumerating the analytical cut the parameters select (by return or by dollar profit). No parameter-specific edge cases are added beyond schema, hence not a 5.

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 states a specific, measurable question — whether top-decile/per-centile Hyperliquid traders persist into the next month — and names the exact ranking dimensions (return, dollar profit). It is clearly distinguishable from siblings leaderboard_rank_check (single-return placement) and overfitting_odds (luck explanation), so an agent can route without opening schemas.

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?

Explicit trigger ('Use when someone proposes copying top traders, a leaderboard or signal leaders') plus explicit alternatives with the condition that selects each ('To place one specific return ... use leaderboard_rank_check; to ask whether luck explains a record, overfitting_odds'). It also states the negative constraint 'Takes no account address', preventing a common wrong invocation.

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?