Start with the arithmetic, since that is the part anyone can check. Roughly 46 tool schemas [7] against more than 275,000 characters [1] works out to just under 6,000 characters per tool [1]. That is an upper bound, because the file also carries search policy, memory rules, copyright handling, computer interaction and interface presentation [2]. The order of magnitude is the useful part. Tool definitions are measured in thousands of characters, not dozens.
That is the real price of a tool. Per the dev.to writeup, exposing one means telling the model what it does, which arguments it accepts, when it should be called, what comes back, and what restrictions apply [9]. Routing sits on top of that: a request for current information triggers web search, a question about an earlier turn goes to a history tool, another produces a chart or previews a page [12]. None of it is clever, and all of it is text resident in the context on every request.
The number reads less like a 275,000-character act of prompt engineering and more like a product stack that got flattened into a single context. The dev.to reading is that the surrounding stack got compressed this way [14], with the model running inside a temporary environment the application assembles: which tools exist, what may be retained, when to search, how the answer is displayed [13]. A 275,000-character policy document that nobody reads end to end will be familiar to anyone who has worked near a compliance team.
Which is why 46 is someone else's number. A runtime prompt can differ by product, by account, by enabled features, by conversation state and by deployment environment [10], and dev.to notes that Anthropic has not confirmed the tool count and the file cannot be verified as complete or universally active [8]. For that count to be your count, your account would need the same features switched on and the same conversation state at the same point. Read it the way you read a vendor benchmark table: a claim about a configuration you cannot see.
The comparison worth making is with Anthropic's own published Fable 5.1 system prompt, which dev.to says is substantially smaller than the third-party file [6]. That gap tracks product surface layered on top of the model, not a difference in what the model itself can do.
The design conclusion is unglamorous, and dev.to gets it right: permissions, privacy, provenance and safety belong in application code rather than in prompt text [11]. A prompt is a request to a probabilistic system, while a check in your handler runs regardless of whether the model cooperated. If your only copyright rule is a paragraph in the system prompt, and a third party can reconstruct that paragraph closely enough to publish it [4], what you have is a record of intent rather than a control.
