Regime

Averaging in check

averaging_in_check

Read-onlyIdempotent

Whether spreading the entry would have helped, measured. One amount into a coin over a window (90, 365 or 730 days): all of it on day one, or equal instalments weekly or monthly. Both start the same day, move the same money and are valued on the same day, started on every day of the history. You get how often spreading ended ahead, the middle result of each, and the worst start day of each — which is what spreading actually buys and the half nobody shows. Spot tape, no fees, dead coins included.

Use for dollar-cost averaging versus lump sum on one coin. For claims about particular days or months use best_days_check or calendar_check; for the fall after a single buy, drawdown_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	The window, in days: 90, 365 or 730.
`instalments`	Yes	How often a slice goes in: weekly or monthly. Defaults to weekly.	weekly

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: cash not yet in earns nothing (against spreading), no fees (in favour of spreading).
`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.
`instalments`	No	How many slices fit in the window.
`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.
`spreading_won`	No	Start days on which spreading it out ended ahead. A count, not a rate: «100%» is only said when it was all of them.
`p05_spread_pct`	No	The same for spreading.
`p05_lump_sum_pct`	No	Fifth percentile of starts, lump sum: one worst day is an anecdote.
`worst_spread_pct`	No	The same for spreading. This pair is the whole argument for averaging in, and it is the one that never appears next to the advice.
`median_spread_pct`	No	Middle start, spread out.
`spreading_won_pct`	No	The same as a share of starts.
`median_edge_points`	No	Percentage points spreading made over lump sum in the middle case. Negative means lump sum won.
`worst_lump_sum_pct`	No	The single worst start day, all in on day one.
`median_lump_sum_pct`	No	Middle start, all in on day one.
`share_in_profit_spread_pct`	No	The same for spreading.
`share_in_profit_lump_sum_pct`	No	Share of starts that ended up, lump sum.

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedOct 15, 2026

addedInput schema / examples

Added value: +[
+  {
+    "coin": "btc",
+    "days": 365
+  }
+]

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"
+}

Changed3 schema fields changedOct 2, 2026
- addedInput schema / properties / days / enum
```
Added value: +[
+  90,
+  365,
+  730
+]
```
- addedInput schema / properties / instalments / default
```
Added value: +"weekly"
```
- addedInput schema / properties / instalments / enum
```
Added value: +[
+  "weekly",
+  "monthly"
+]
```
First observedOct 1, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, so safety is covered; the description adds real method context beyond that — 'Spot tape, no fees, dead coins included' and 'started on every day of the history' — which materially affects how results should be interpreted. It stops short of stating limits or caveats on the statistics themselves.

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?

The routing paragraph is tight and earns its place, but the first paragraph is bloated with editorializing ('which is what spreading actually buys and the half nobody shows') and dense compound sentences. The genuinely useful constraints could be stated in far fewer words.

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

Completeness4/5

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

With an output schema present, return values needn't be explained, and the description still adds the valuation methodology and sibling routing. Combined with 100% schema coverage and full annotations, an agent has what it needs; only the statistical caveats are unaddressed.

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 both enums are documented inline (days: 90/365/730; instalments: weekly/monthly with default). The description adds essentially no parameter meaning beyond what the schema already provides, so baseline 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?

States a specific, checkable operation: measuring whether spreading an entry (weekly/monthly DCA) beats lump sum on a single coin over a fixed window. The scope ('One amount into a coin over a window') distinguishes it cleanly from sibling checks without needing to open the 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?

Explicit when-to-use ('dollar-cost averaging versus lump sum on one coin') plus concrete routing to alternatives: best_days_check/calendar_check for particular days or months, drawdown_check for a single-buy fall. Covers both the positive case and the exclusion conditions.

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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