Dividing the budget by the toolbox shows why the default is not a ceiling you can just nudge. Eight thousand characters spread across 112 skills [1] gives each about 71 characters, names included [4], while his descriptions average around 307 [3]. The measured listing ran 4.3 times over [2]. The per-skill cap makes the same point from the other end: five skills written up to the 1536-character maximum [8] consume 7,680 characters, about 96 percent of a 200K window's allowance [5].
That is why trimming alone does not clear it. Rewriting every description to under 250 characters [17] still leaves 26,342 characters of listing, roughly 3.3 times the default [7]. The escape hatch is `SLASH_COMMAND_TOOL_CHAR_BUDGET`, which replaces the fraction calculation outright [9], and the author set it to 45,000 across two config files [15].
At that point the listing becomes a standing cost. Work backwards from the published equivalence, 8,000 characters for 1 percent of a 200K-token window, and the implied conversion is about four characters per token [8]. A 45,000-character listing is therefore near 11,250 tokens, roughly 5.6 percent of a 200K context, sitting in the system prompt of every session [9]. Trimming is what keeps that figure from climbing.
The verification step is the part I would copy. He opened a headless sub-session and forced it to quote, verbatim, the description of a skill that had previously been name-only, then compared the words to the file [15]. That separates a config value you edited from text the model can actually see. A skill that can only be reached by typing its name functions as a slash command with a folder around it [4].
Which leaves the A/B. He cut 10,400 characters and reports no systematic decline in trigger rate, while explicitly refusing to claim an improvement, because two cases either way is noise at his sample size [18]. Read it as a result about his 41 tools. For the number to transfer, your descriptions would need a comparable share of what he cut: the same sentence written twice in two languages, long enumerations, and restatements of the SKILL.md body [21]. Your invocations would also need to hinge on the identifiers and symptom phrases he kept, since the description is the entire basis for the model's decision to reach for a skill, and a deleted trigger word simply stops working, with no error and no warning [19]. His first pass, cutting whatever felt redundant, was abandoned for the honest reason: he had no way to prove he had not removed something load-bearing [20].
