← Mathematical compendium

Published equation contexts

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

Why this formula appears here

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…

Read the full article-specific guide →

Read the representative guide

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.

Read this term in its guide →
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.

Read this term in its guide →
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.

Read this term in its guide →
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.

Read this term in its guide →

How to interpret it

Read it with the definitions, units, and assumptions supplied by the article.

Research cited beside this formula

Published contexts (1)

A symbol can carry a different meaning in another article. Each occurrence keeps its own guide and term definitions.

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

Equation 4 · AI Infrastructure

The Token Tax of Giving a Model More Tools

This equation states an equality: the expressions on both sides have the same value under the article’s assumptions.

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…

Meanings in this article

Equation guide → · Article →