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Folionomiq

by com.folionomiq
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Sensitivity to common return patterns

factor_exposure
Read-onlyIdempotent

How a portfolio's daily moves line up with four common patterns: the market, small versus large, value versus growth, momentum. Out: each sensitivity, whether it can be told from zero, and how much of the movement the four explain. Typical questions: 'Am I a growth investor without knowing it?'; 'What style is my portfolio really exposed to?'; 'Is this tilted to small caps?'. Instead: for the number of independent bets, portfolio_structure. It does not recommend, predict or calculate tax.

Input Schema

NameRequiredDescriptionDefault
baseNoCurrency code every figure is expressed in: USD, EUR, GBP, CAD… Default USD.
unitsNoWhat the holdings' numbers are: 'money' (amounts in the base currency) or 'weights' (percentages or fractions). Omitted: holdings adding up to 1 or 100 are read as percentages, anything else as money, and the answer says so.
holdingsYesWhat is held: {ticker: number}, 1 to 100 holdings. Weights in any scale (60/20/20 or 0.6/0.2/0.2) or money amounts in the base currency (60000/20000/20000): `units` says which; without it, holdings adding up to 1 or 100 are read as percentages, anything else as money, which makes the falls come out in money. Tickers as the exchange lists them (VOO, VWCE.DE, EQQQ.DE, XAW.TO; 'CASH.USD' for cash). Example: {"VTI": 60, "VXUS": 20, "BND": 20}.

Output Schema

NameRequiredDescriptionDefault
dataNoWhere the prices came from and what was missing or repaired.
betasNoSensitivity per factor: mkt_rf (market), smb (small minus big), hml (value minus growth), mom (momentum).
modelNoFactor model used.
yearsNoYears of history used.
_fenceYesWhat these figures are and are not: descriptive, no forecast, no advice. Repeat its sense when presenting the result.
t_statsNot-statistic per factor; below about 2 in size, not distinguishable from zero.
poor_fitNoTrue when the factors explain little.
frequencyNoData frequency.
r_squaredNoShare of the daily movement the factors explain, 0 to 1.
fit_caveatNoWhy the fit is poor, when it is.
alpha_annualNoReturn not explained by the factors, per year (estimated, not a skill measure).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / holdings / description
      Previous value: -"What is held: {ticker: number}, 1 to 100 holdings. Weights in any scale (60/20/20 or 0.6/0.2/0.2) or money amounts in the base currency (60000/20000/20000): holdings adding up to 1 or 100 are read as percentages, anything else as money, which makes the falls come out in money. Tickers as the exchange lists them (VOO, VWCE.DE, EQQQ.DE, XAW.TO; 'CASH.USD' for cash). Example: {\"VTI\": 60, \"VXUS\": 20, \"BND\": 20}."New value: +"What is held: {ticker: number}, 1 to 100 holdings. Weights in any scale (60/20/20 or 0.6/0.2/0.2) or money amounts in the base currency (60000/20000/20000): `units` says which; without it, holdings adding up to 1 or 100 are read as percentages, anything else as money, which makes the falls come out in money. Tickers as the exchange lists them (VOO, VWCE.DE, EQQQ.DE, XAW.TO; 'CASH.USD' for cash). Example: {\"VTI\": 60, \"VXUS\": 20, \"BND\": 20}."
    • addedInput schema / properties / units
      Added value: +{
+  "anyOf": [
+    {
+      "enum": [
+        "money",
+        "weights"
+      ],
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "What the holdings' numbers are: 'money' (amounts in the base currency) or 'weights' (percentages or fractions). Omitted: holdings adding up to 1 or 100 are read as percentages, anything else as money, and the answer says so.",
+  "title": "Units"
+}
  2. Changed2 schema fields changed
    • changedInput schema / properties / base / description
      Previous value: -"Currency every figure is expressed in (USD, EUR, GBP, CAD…). Default USD."New value: +"Currency code every figure is expressed in: USD, EUR, GBP, CAD… Default USD."
    • changedInput schema / properties / holdings / description
      Previous value: -"What is held: {ticker: weight or amount}. Weights need not sum to one; amounts in the base currency are also accepted (then the crises are shown in money). 1 to 100 holdings. Tickers as the exchange lists them (VOO, VWCE.DE, XAW.TO; 'CASH.USD' for cash)."New value: +"What is held: {ticker: number}, 1 to 100 holdings. Weights in any scale (60/20/20 or 0.6/0.2/0.2) or money amounts in the base currency (60000/20000/20000): holdings adding up to 1 or 100 are read as percentages, anything else as money, which makes the falls come out in money. Tickers as the exchange lists them (VOO, VWCE.DE, EQQQ.DE, XAW.TO; 'CASH.USD' for cash). Example: {\"VTI\": 60, \"VXUS\": 20, \"BND\": 20}."
  3. Added

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already establish that this is a read-only, idempotent, non-destructive operation. The description adds useful behavioral context by describing the outputs (sensitivities, significance versus zero, explanatory power) and stating that it does not recommend, predict, or calculate tax.

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?

The description is front-loaded with the core measurement and then adds examples, an alternative tool, and limitations. It is somewhat longer than strictly necessary due to three sample questions, but each part remains relevant.

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, the description does not need to explain return values in full, and it already summarizes the key outputs and limitations. It could say more about the estimation window or method, but overall it is complete enough for correct tool selection and invocation.

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%, so the schema already documents base, units, and holdings in detail. The description does not add parameter-specific semantics beyond referring generally to portfolio daily moves, so the baseline score of 3 is appropriate.

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 precisely what the tool measures: a portfolio's daily return sensitivity to four named common patterns (market, size, value, momentum). It also clearly distinguishes this from the sibling portfolio_structure tool, which handles independent-bet counts.

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 provides concrete typical questions that indicate when to use it, such as checking unintended growth or small-cap tilts. It also explicitly names an alternative, portfolio_structure, and the condition under which that alternative is more appropriate.

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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