Regime

Drawdown check

drawdown_check

Read-onlyIdempotent

Drawdown check: what it cost to collect the return you were shown. The coin is bought at the close of every day of its history and held for the period you name: you get the drawdown from the entry before the period was out, the share of starts that fell 30% and 50%, the days spent under water, how it ended — and, among the starts that ended in profit, the drawdown they sat through first. Spot tape, no fees, coins that died included.

Use when a return is quoted for holding a coin ("BTC did +150% in a year") and you want the fall endured on the way. With leverage use leverage_survival; to test a stop that cuts the fall, stop_loss_check.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`coin`	Yes	Ticker or full pair. An unknown one comes back with the list we hold and the ones left out.
`days`	Yes	How long it is held: 30, 90, 365 or 730.

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 assumptions, stated.
`reason`	No	Why, in one sentence, and what we do have instead.
`source`	No	The public file these numbers come from.
`starts`	No	Start days tested. Fewer than 120 and we refuse to give a percentage.
`median_return_pct`	No	How the middle start ended.
`share_fell_30_pct`	No	Share of starts that fell 30% or more from entry first.
`share_fell_50_pct`	No	Same, 50% or more.
`asset_max_drawdown`	No	The coin's own biggest top-to-bottom fall, with dates and days to recover, for comparison.
`share_in_profit_pct`	No	Share of starts that ended up.
`median_worst_fall_pct`	No	The middle start's worst fall from its own entry price within the hold.
`median_days_under_water`	No	Days of the hold spent below the entry price, middle start.
`share_never_recovered_pct`	No	Starts that never closed back at their entry price within the hold.
`median_worst_fall_among_winners_pct`	No	Among the starts that ended in profit, the median fall they sat through first. The price of the number you were shown. A return without this is advertising.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 2, 2026
- addedInput schema / properties / days / enum
```
Added value: +[
+  30,
+  90,
+  365,
+  730
+]
```
First observedOct 1, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already establish readOnly/idempotent/non-destructive, so the safety profile is covered. The description adds genuinely useful scope context beyond them: 'Spot tape, no fees, coins that died included' tells the agent what data is and isn't in the result, plus it enumerates the computed metrics. It stops short of discussing rate limits or auth, but those are marginal for a local read-only computation.

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

Conciseness3/5

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

It is front-loaded and free of filler sentences, but the first paragraph enumerates output metrics ('share of starts that fell 30% and 50%, days spent under water...') that the existing output schema already delivers, and the prose is dense and stylized rather than tight. Some of the length duplicates structured data.

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 two-parameter read-only tool with a full schema, complete enum coverage, annotations, and an output schema, the description supplies the remaining needed context: what is computed, the trigger condition, the data-scope caveats, and the alternatives. An agent has everything required to call it correctly.

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 description coverage is 100% and the enum of allowed hold lengths (30/90/365/730) is documented in the schema itself. The description only restates the hold concept, adding no format or syntax detail beyond the schema, so the baseline of 3 applies.

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 concrete computation on a specific resource: buy at every daily close across a coin's history, hold for the named period, and return drawdown statistics. It is immediately distinguishable from siblings like leverage_survival and stop_loss_check, which it names explicitly.

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 an explicit trigger ('when a return is quoted for holding a coin ... and you want the fall endured on the way') and names two alternatives with the conditions that select them: leverage_survival for leverage and stop_loss_check for stop-cut falls. Nothing is left to inference.

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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