Token audit

Skill Vix0007/vixero-skills/skills/token-audit

Token-efficient Agent Skills for Claude — Pillar 1: meta-skills ≤650t, Pillar 1.5: coding discipline

Install

npx -y skills add Vix0007/vixero-skills --skill token-audit

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Score a SKILL.md, prompt, or system message for token waste. Use when the user asks to audit, measure, benchmark, score, or evaluate token efficiency of a skill, prompt, or agent instruction. Returns a 0-100 score, six-axis breakdown, and ranked specific cuts with token-savings estimates.

SKILL.md

2.0 KB, as published. Nobody here has run it

token-audit

Audit input. Return structured waste report. No rewrites — invoke skill-compress for that.

Trigger on

"audit this skill / prompt / SKILL.md"
"is this efficient"
"score my skill"
User pastes a SKILL.md or system prompt with audit intent

Process

Count tokens. Rule: English prose ≈ 4 chars/token, code ≈ 3 chars/token, YAML ≈ 3.5 chars/token.
Score six axes, 0–10 each, deductions below:

axis	deduction
preamble-bloat	−3 per "I'll help" / "Certainly" / "Sure" / "Of course" / "Let me"
passive-voice	−1 per "is recommended" / "should be done" / "can be performed"
prose-over-table	−5 if any list / table / matrix would cut 30%+ tokens
redundant-examples	−2 per duplicate-purpose example
ceremonial	−1 per "please" / "kindly" / "feel free" / "if you'd like"
desc-quality	−10 if frontmatter description < 40 chars, > 300 chars, or missing when to use

Total = sum clamped ≥ 0. Score = (total / 60) × 100.

Output

tokens: {n}
score: {0-100}

breakdown:
  preamble-bloat:     {n}/10
  passive-voice:      {n}/10
  prose-over-table:   {n}/10
  redundant-examples: {n}/10
  ceremonial:         {n}/10
  desc-quality:       {n}/10

top cuts (ranked by savings):
1. "{before}" → "{after}"  (−{n} tokens)
2. ...

projected savings: {n} tokens ({pct}%)
verdict: {lean | cut 20-40% | rewrite from scratch}

Hard rules

No softening. "Wastes 40 tokens" — not "may waste some tokens."
No rewrites here. Report only.
Always include absolute token count AND percentage.
If score < 40 say "rewrite from scratch" — do not recommend incremental fixes.
Fit output under 300 tokens for inputs under 2000 tokens.