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Equation 4 · The Token Tax of Giving a Model More Tools

What does this equation mean?

T(n)=τ0+∑i=1nsiT(n) = \tau_0 + \sum_{i=1}^{n} s_i

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Inputs and operationstau_0 + sum_i=1^n s_i
Result or conditionT(n)
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This equation states an equality: the expressions on both sides have the same value under the article’s assumptions. Read the equation part by part below; each part has a contextual explanation and a link to its mathematical background.

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TT

Symbol T

T is part of the quantity the equation computes from the expression on the right.

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nn

Symbol n

n appears in the bound of this sum. The bound states where the repeated operation starts, ends, or which values it includes.

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τ0\tau_0

Symbol tau_0

the tool-independent charge.

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ii

Symbol i

i appears in the bound of this sum. The bound states where the repeated operation starts, ends, or which values it includes.

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sis_i

Symbol s_i

the number of tokens.

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=

=

The expressions on both sides represent the same quantity under the stated assumptions.

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addition

addition

Add the term after the plus sign to the term or group before it.

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subscript

subscript

The lower label selects a particular version, component, or indexed member of the quantity. For example, x₀ and xₜ can be values at different positions.

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superscript

superscript

A raised number can be a power. When it is a label or bound, it selects a case or the upper limit of a sum; the formula’s structure distinguishes these uses.

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i=1i=1

Starting index or lower bound: i=1

This label says where the repeated addition, multiplication, or accumulation starts. Read its value or condition together with the article’s description of the index.

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nn

Ending index or upper bound: n

This label says where the repeated addition, multiplication, or accumulation stops. It sets the last term or end of the range.

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How to interpret it

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What the article says around this equation

Call this fixed, tool-independent charge τ0\tau_0 . On top of it sits the actual content of the catalogue: for n tools attached to a request, each with a schema costing sis_i tokens for its name, description, and JSON Schema of parameters, the tool-visibility component of a single request’s input is T(n)=τ0+∑i=1nsiT(n) = \tau_0 + \sum_{i=1}^{n} s_i. which, if schemas run at roughly a uniform average size sˉ\bar{s} , simplifies to T(n) ≈\approx τ0\tau_0 + nsˉ\bar{s} . Nothing about this term depends on whether the model calls any tool at all; it is the price of the menu, not the price of the order. And critically, because a stateless inference API resends its full input on every request, T(n) is not paid once at the start of a…
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Call this fixed, tool-independent charge τ0\tau_0 . On top of it sits the actual content of the catalogue: for n tools attached to a request, each with a schema costing sis_i tokens for its name, description, and JSON Schema of parameters, the tool-visibility component of a single request’s input is T(n)=τ0+∑i=1nsiT(n) = \tau_0 + \sum_{i=1}^{n} s_i. which, if schemas run at roughly a uniform average size sˉ\bar{s} , simplifies to T(n) ≈\approx τ0\tau_0 + nsˉ\bar{s} . Nothing about this term depends on whether the model calls any tool at all; it is the price of the menu, not the price of the order. And critically, because a stateless inference API resends its full input on every request, T(n) is not paid once at the start of a session — it is paid again, in full, on every single turn for as long as tools remain attached to the request.

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