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Get Started Free →Performs arbitrary-precision arithmetic calculations including addition, subtraction, multiplication, division, and exponents. Use when the user asks to calculate, compute, or evaluate math expressions, or when precise decimal arithmetic is needed to avoid floating-point errors.
.claude/skills/code-and-sorts-calculator/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-02 | ✗→✓ | ▲ Improved | 111% | 0% |
| case-04 | ✗→✓ | ▲ Improved | 510% | 0% |
| case-09 | ✗→✓ | ▲ Improved | 238% | 0% |
| case-13 | ✗→✓ | ▲ Improved | -60% | 0% |
| case-20 | ✗→✓ | ▲ Improved | -32% | 0% |
Evaluate arithmetic expressions with arbitrary-precision decimal math using big.js.
0.1 + 0.2 = 0.30000000000000004)| Operator | Description | Precedence | | -------- | ----------- | ---------- | | + | Addition | 1 | | - | Subtraction | 1 | | * | Multiplication | 2 | | / | Division | 2 | | ^ | Exponent (right-associative) | 3 | | () | Parentheses | Highest |
bashcd scripts npm ci || npm install npm run build npm run calculate "<expression>"
| Input | Output | | ----- | ------ | | "3 + 2" | 5 | | "10 / 4" | 2.5 | | "2 ^ 10" | 1024 | | "(2 + 3) * 4" | 20 | | "1 + 4.5 * (3-6) / 5" | -1.7 | | "-5 + 3" | -2 | | "2 ^ 3 ^ 2" | 512 (right-associative: 2^9) |
.pow() requires integer exponents| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-21 | pass→fail | 1,813 | 3,932 | +117% | 1 | 1 | 0% | 191 | 647 | +239% | 0 | 0 | — |
case-01 | fail→fail | 3,637 | 5,026 | +38% | 1 | 1 | 0% | 727 | 707 | -3% | 0 | 0 | — |
case-02 | fail→pass | 7,059 | 11,755 | +67% | 1 | 1 | 0% | 1,410 | 2,973 | +111% | 0 | 0 | — |
case-03 | fail→fail | 2,055 | 6,230 | +203% | 1 | 1 | 0% | 377 | 822 | +118% | 0 | 0 | — |
case-04 | fail→pass | 1,641 | 6,157 | +275% | 1 | 1 | 0% | 227 | 1,385 | +510% | 0 | 0 | — |
case-05 | pass→fail | 6,132 | 4,520 | -26% | 1 | 1 | 0% | 1,090 | 761 | -30% | 0 | 0 | — |
case-06 | pass→fail | 3,545 | 4,756 | +34% | 1 | 1 | 0% | 634 | 742 | +17% | 0 | 0 | — |
case-07 | pass→fail | 5,233 | 6,336 | +21% | 1 | 1 | 0% | 795 | 805 | +1% | 0 | 0 | — |
case-08 | pass→fail | 5,419 | 4,602 | -15% | 1 | 1 | 0% | 878 | 659 | -25% | 0 | 0 | — |
case-09 | fail→pass | 5,364 | 16,331 | +204% | 1 | 1 | 0% | 935 | 3,160 | +238% | 0 | 0 | — |
case-10 | pass→pass | 2,861 | 10,207 | +257% | 1 | 1 | 0% | 493 | 2,137 | +333% | 0 | 0 | — |
case-11 | pass→fail | 3,048 | 4,223 | +39% | 1 | 1 | 0% | 416 | 600 | +44% | 0 | 0 | — |
case-12 | pass→fail | 4,148 | 4,022 | -3% | 1 | 1 | 0% | 716 | 646 | -10% | 0 | 0 | — |
case-13 | fail→pass | 10,991 | 1,634 | -85% | 1 | 1 | 0% | 1,655 | 667 | -60% | 0 | 0 | — |
case-14 | pass→fail | 3,322 | 9,426 | +184% | 1 | 1 | 0% | 450 | 628 | +40% | 0 | 0 | — |
case-15 | pass→fail | 6,861 | 3,795 | -45% | 1 | 1 | 0% | 1,067 | 626 | -41% | 0 | 0 | — |
case-16 | pass→fail | 4,142 | 4,393 | +6% | 1 | 1 | 0% | 712 | 716 | +1% | 0 | 0 | — |
case-17 | pass→fail | 4,941 | 4,415 | -11% | 1 | 1 | 0% | 911 | 643 | -29% | 0 | 0 | — |
case-18 | pass→fail | 3,107 | 4,146 | +33% | 1 | 1 | 0% | 528 | 660 | +25% | 0 | 0 | — |
case-19 | pass→fail | 2,402 | 4,044 | +68% | 1 | 1 | 0% | 421 | 603 | +43% | 0 | 0 | — |
case-20 | fail→pass | 7,257 | 1,627 | -78% | 1 | 1 | 0% | 1,092 | 738 | -32% | 0 | 0 | — |
case-22 | pass→fail | 3,874 | 4,087 | +5% | 1 | 1 | 0% | 657 | 639 | -3% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted, and 7 counted toward the lift figure. The other 15 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of -41 percentage points is the difference between those two pass rates over the 7 comparable cases. 15 cases got worse with the skill loaded, and they are included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.