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Get Started Free →Detects the project language and runs appropriate linters and formatters. Reports style violations, potential bugs, and security issues. With `--fix`, auto-corrects fixable issues.
.claude/skills/miosa-osa-lint/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-12 | ✗→✓ | ▲ Improved | 220% | 0% |
| case-21 | ✗→✓ | ▲ Improved | 57% | 0% |
| case-23 | ✗→✓ | ▲ Improved | -30% | 0% |
| case-04 | ✓→✗ | ▼ Worse | -31% | 0% |
| case-05 | ✓→✗ | ▼ Worse | -81% | 0% |
> Run linters and formatters, report issues, auto-fix where possible.
/lint [path] [--fix] [--strict] [--format <format>]Detects the project language and runs appropriate linters and formatters. Reports style violations, potential bugs, and security issues. With --fix, auto-corrects fixable issues.
mix format --check-formatted + mix credo --stricteslint + prettier --checkgolangci-lint runruff check + black --checkcargo clippy--fix) -- run formatters and auto-fixable rules.bash# Check for lint issues /lint # Auto-fix all fixable issues /lint --fix # Strict mode (warnings become errors) /lint --strict # Lint specific directory /lint lib/optimal_engine/
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 6,950 | 7,200 | +4% | 1 | 1 | 0% | 243 | 661 | +172% | 0 | 0 | — |
case-02 | fail→fail | 10,300 | 5,868 | -43% | 1 | 1 | 0% | 1,701 | 503 | -70% | 0 | 0 | — |
case-03 | fail→fail | 11,209 | 24,675 | +120% | 1 | 1 | 0% | 1,524 | 2,106 | +38% | 0 | 0 | — |
case-04 | pass→fail | 5,138 | 6,943 | +35% | 1 | 1 | 0% | 720 | 500 | -31% | 0 | 0 | — |
case-05 | pass→fail | 12,647 | 5,428 | -57% | 1 | 1 | 0% | 2,333 | 441 | -81% | 0 | 0 | — |
case-06 | pass→pass | 8,694 | 6,660 | -23% | 1 | 1 | 0% | 1,397 | 610 | -56% | 0 | 0 | — |
case-07 | fail→fail | 10,647 | 6,115 | -43% | 1 | 1 | 0% | 1,730 | 611 | -65% | 0 | 0 | — |
case-08 | fail→fail | 11,163 | 21,087 | +89% | 1 | 1 | 0% | 1,825 | 561 | -69% | 0 | 0 | — |
case-09 | fail→fail | 7,142 | 5,109 | -28% | 1 | 1 | 0% | 1,013 | 534 | -47% | 0 | 0 | — |
case-10 | fail→fail | 15,572 | 7,226 | -54% | 1 | 1 | 0% | 2,634 | 594 | -77% | 0 | 0 | — |
case-11 | fail→fail | 10,410 | 2,971 | -71% | 1 | 1 | 0% | 1,538 | 593 | -61% | 0 | 0 | — |
case-12 | fail→pass | 5,309 | 12,411 | +134% | 1 | 1 | 0% | 614 | 1,966 | +220% | 0 | 0 | — |
case-13 | fail→fail | 9,560 | 6,172 | -35% | 1 | 1 | 0% | 1,519 | 597 | -61% | 0 | 0 | — |
case-14 | pass→fail | 24,314 | 5,749 | -76% | 1 | 1 | 0% | 2,087 | 461 | -78% | 0 | 0 | — |
case-15 | fail→fail | 11,438 | 4,664 | -59% | 1 | 1 | 0% | 1,903 | 524 | -72% | 0 | 0 | — |
case-16 | fail→fail | 7,583 | 5,889 | -22% | 1 | 1 | 0% | 1,252 | 512 | -59% | 0 | 0 | — |
case-17 | pass→pass | 11,387 | 6,324 | -44% | 1 | 1 | 0% | 1,880 | 1,218 | -35% | 0 | 0 | — |
case-18 | fail→fail | 8,335 | 7,026 | -16% | 1 | 1 | 0% | 1,341 | 700 | -48% | 0 | 0 | — |
case-19 | pass→fail | 16,739 | 3,175 | -81% | 1 | 1 | 0% | 2,311 | 635 | -73% | 0 | 0 | — |
case-20 | pass→fail | 7,149 | 6,088 | -15% | 1 | 1 | 0% | 1,259 | 560 | -56% | 0 | 0 | — |
case-21 | fail→pass | 9,008 | 11,097 | +23% | 1 | 1 | 0% | 1,365 | 2,139 | +57% | 0 | 0 | — |
case-22 | fail→fail | 6,631 | 12,547 | +89% | 1 | 1 | 0% | 1,042 | 1,999 | +92% | 0 | 0 | — |
case-23 | fail→pass | 9,932 | 22,196 | +123% | 1 | 1 | 0% | 1,456 | 1,017 | -30% | 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. 23 cases were attempted, and 13 counted toward the lift figure. The other 10 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 -9 percentage points is the difference between those two pass rates over the 13 comparable cases. 7 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.