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token-cost

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Measure before optimizing — estimate token counts locally with stated heuristics, price them at your model's rates, and quantify before/after savings, because token optimization without measurement is vibes. Use when asked how many tokens is this, what does this context cost per call, is this optimization worth it, or compare these two versions' cost. Produces the estimate with both heuristics shown, the cost math at your prices across your call volume, and the before/after comparison that decides whether an optimization earned its complexity.

skills/token-cost/SKILL.md

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# Token Cost Skill

Every token optimization should start and end with the same question: *how many, at what price, how often?* — and most skip all three. This skill is the measurement layer: local token estimates (two stated heuristics, averaged, no tokenizer dependencies), cost math at *your* model's prices (supplied, never baked in — prices change faster than repos), and the before/after comparison that turns "this feels smaller" into "saves 4,200 tokens, $1.26 per hundred calls." The honest core: a 40% saving on something sent once is a rounding error; 8% on something sent every call is real money — the `--calls` flag is the whole insight.

## What This Skill Produces

- **The estimate** — chars/4 and words×4/3, both shown, averaged, with the ±15% honesty label
- **The cost math** — per call and across the stated call volume, at supplied prices
- **The comparison** — before vs. after any optimization: tokens saved, percent, dollars at volume
- **The verdict frame** — worth-it / not-worth-it, decided by volume × savings vs. the optimization's own complexity

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