Equation 22 · The Token Tax of Giving a Model More Tools
What does this equation mean?
Read the formula alongside the article passage below. Each part has a deeper page with its role in the equation, the supporting passage and nearby citations.
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.
Read it piece by piece
Symbol ρ
ρ is part of the quantity the equation computes from the expression on the right.
Symbol n
n occurs below the fraction bar. The quantity above the bar is divided by this expression; zero is excluded as a denominator.
Symbol bars
bars is one of the signed contributions combined to compute the quantity on the left.
Symbol tau_0
ta occurs below the fraction bar. The quantity above the bar is divided by this expression; zero is excluded as a denominator.
=
The expressions on both sides represent the same quantity under the stated assumptions.
See an illustrated explanation →subtraction
Subtract the following term or group from the preceding one. A leading minus marks a negative quantity.
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.
Denominator: tau_0 + nbars
The complete quantity below the fraction bar; it must be nonzero for this division.
How to interpret it
With a fixed numerator, increasing a nonzero denominator reduces the fraction. Read it with the definitions, units, and assumptions supplied by the article.
What the article says around this equation
Anthropic’s Tool Search Tool is a direct, documented implementation of that idea. The mechanism is described plainly: “You provide all your tool definitions to the API, but mark tools with defeoading: true to make them discoverable on-demand,” with a lightweight search tool — built-in options include BM25-based and regex-based search — querying an index of names and descriptions, and the full definition of a matching tool injected into context only once the model actually requests it [ 5 ] . The search tool itself is not free, but its overhead is small and fixed rather than proportional to catalogue size: “Only the Tool Search Tool loaded upfront (~500 tokens)” [ 5 ] . Applied to the same…
Read the full surrounding passage
Anthropic’s Tool Search Tool is a direct, documented implementation of that idea. The mechanism is described plainly: “You provide all your tool definitions to the API, but mark tools with defeoading: true to make them discoverable on-demand,” with a lightweight search tool — built-in options include BM25-based and regex-based search — querying an index of names and descriptions, and the full definition of a matching tool injected into context only once the model actually requests it [ 5 ] . The search tool itself is not free, but its overhead is small and fixed rather than proportional to catalogue size: “Only the Tool Search Tool loaded upfront (~500 tokens)” [ 5 ] . Applied to the same 58-tool, roughly 55,000-token example described above, that reframes the earlier formula: instead of the full T(n) + n , a session that only ever actually needs m of the n available tools pays approximately + + m , where is the search tool’s own fixed overhead. The fraction of the original tax avoided is . which grows toward its ceiling as m shrinks relative to n . Anthropic reports a measured outcome consistent with that shape at their own scale: “Tool Search Tool preserves 191,300 tokens of context compared to 122,800 with Claude’s traditional approach,” described as an “85% reduction in token usage while maintaining access to your full tool library” [ 5 ] . Against a standard 200,000-token context window, those two preserved-context figures imply roughly 8,700 tokens actually consumed by tool definitions with search enabled against roughly 77,200 tokens without it — an arithmetic inference this article draws from the published figures, not one stated as such in the source. The same documentation reports the mechanism also improved accuracy rather than only cost, on internal MCP evaluations: Opus 4 rose from 49% to 74%, and Opus 4.5 from 79.5% to 88.1%, with Tool Search Tool enabled [ 5 ] .
Sources cited in the surrounding passage
These citations give research context. Read each source to check which claims it supports.
Return to The Token Tax of Giving a Model More Tools