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Get Started Free →Internationalization and localization patterns. Detecting hardcoded strings, managing translations, locale files, RTL support.
.claude/skills/sickn33-i18n-localization/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | -33% | 0% |
| case-19 | ✗→✓ | ▲ Improved | -59% | 0% |
| case-16 | ✓→✓ | = Same ✓ | 24% | 0% |
| case-02 | ✓→✓ | = Same ✓ | 23% | 0% |
| case-03 | ✓→✓ | = Same ✓ | 22% | 0% |
> Internationalization (i18n) and Localization (L10n) best practices.
| Term | Meaning | |------|---------| | i18n | Internationalization - making app translatable | | L10n | Localization - actual translations | | Locale | Language + Region (en-US, tr-TR) | | RTL | Right-to-left languages (Arabic, Hebrew) |
| Project Type | i18n Needed? | |--------------|--------------| | Public web app | ✅ Yes | | SaaS product | ✅ Yes | | Internal tool | ⚠️ Maybe | | Single-region app | ⚠️ Consider future | | Personal project | ❌ Optional |
tsximport { useTranslation } from 'react-i18next'; function Welcome() { const { t } = useTranslation(); return <h1>{t('welcome.title')}</h1>; }
tsximport { useTranslations } from 'next-intl'; export default function Page() { const t = useTranslations('Home'); return <h1>{t('title')}</h1>; }
pythonfrom gettext import gettext as _ print(_("Welcome to our app"))
locales/
├── en/
│ ├── common.json
│ ├── auth.json
│ └── errors.json
├── tr/
│ ├── common.json
│ ├── auth.json
│ └── errors.json
└── ar/ # RTL
└── ...| Issue | Solution | |-------|----------| | Missing translation | Fallback to default language | | Hardcoded strings | Use linter/checker script | | Date format | Use Intl.DateTimeFormat | | Number format | Use Intl.NumberFormat | | Pluralization | Use ICU message format |
css/* CSS Logical Properties */ .container { margin-inline-start: 1rem; /* Not margin-left */ padding-inline-end: 1rem; /* Not padding-right */ } [dir="rtl"] .icon { transform: scaleX(-1); }
Before shipping:
| Script | Purpose | Command | |--------|---------|---------| | scripts/i18n_checker.py | Detect hardcoded strings & missing translations | python scripts/i18n_checker.py <project_path> |
This skill is applicable to execute the workflow or actions described in the overview.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-16 | pass→pass | 15,705 | 14,324 | -9% | 1 | 1 | 0% | 2,587 | 3,204 | +24% | 0 | 0 | — |
case-01 | fail→pass | 23,623 | 12,766 | -46% | 1 | 1 | 0% | 4,219 | 2,837 | -33% | 0 | 0 | — |
case-02 | pass→pass | 16,968 | 15,326 | -10% | 1 | 1 | 0% | 3,155 | 3,894 | +23% | 0 | 0 | — |
case-03 | pass→pass | 13,093 | 11,561 | -12% | 1 | 1 | 0% | 2,651 | 3,228 | +22% | 0 | 0 | — |
case-04 | pass→pass | 8,388 | 3,921 | -53% | 1 | 1 | 0% | 1,554 | 1,567 | +1% | 0 | 0 | — |
case-05 | pass→pass | 17,924 | 7,510 | -58% | 1 | 1 | 0% | 3,701 | 2,333 | -37% | 0 | 0 | — |
case-06 | pass→pass | 10,982 | 6,457 | -41% | 1 | 1 | 0% | 1,920 | 2,219 | +16% | 0 | 0 | — |
case-07 | pass→pass | 15,741 | 16,324 | +4% | 1 | 1 | 0% | 3,228 | 4,359 | +35% | 0 | 0 | — |
case-08 | pass→pass | 5,494 | 4,941 | -10% | 1 | 1 | 0% | 1,022 | 1,881 | +84% | 0 | 0 | — |
case-09 | pass→pass | 7,128 | 3,067 | -57% | 1 | 1 | 0% | 1,256 | 1,453 | +16% | 0 | 0 | — |
case-10 | pass→pass | 12,642 | 9,620 | -24% | 1 | 1 | 0% | 2,168 | 2,541 | +17% | 0 | 0 | — |
case-11 | pass→pass | 9,410 | 6,045 | -36% | 1 | 1 | 0% | 1,570 | 2,049 | +31% | 0 | 0 | — |
case-12 | pass→pass | 14,562 | 10,318 | -29% | 1 | 1 | 0% | 2,342 | 2,648 | +13% | 0 | 0 | — |
case-13 | pass→pass | 15,519 | 12,529 | -19% | 1 | 1 | 0% | 2,585 | 3,057 | +18% | 0 | 0 | — |
case-14 | pass→pass | 11,005 | 9,911 | -10% | 1 | 1 | 0% | 1,919 | 2,641 | +38% | 0 | 0 | — |
case-15 | pass→pass | 20,987 | 19,067 | -9% | 1 | 1 | 0% | 3,312 | 4,039 | +22% | 0 | 0 | — |
case-17 | pass→pass | 13,812 | 8,990 | -35% | 1 | 1 | 0% | 2,506 | 2,567 | +2% | 0 | 0 | — |
case-18 | pass→pass | 18,623 | 8,669 | -53% | 1 | 1 | 0% | 2,679 | 2,301 | -14% | 0 | 0 | — |
case-19 | fail→pass | 17,543 | 1,966 | -89% | 1 | 1 | 0% | 2,958 | 1,223 | -59% | 0 | 0 | — |
case-20 | pass→pass | 12,536 | 12,155 | -3% | 1 | 1 | 0% | 2,370 | 3,325 | +40% | 0 | 0 | — |
case-21 | pass→pass | 12,345 | 10,765 | -13% | 1 | 1 | 0% | 2,403 | 2,911 | +21% | 0 | 0 | — |
case-22 | pass→pass | 33,802 | 27,074 | -20% | 1 | 1 | 0% | 7,081 | 6,572 | -7% | 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. The headline lift of +9 percentage points is the difference between those two pass rates over the 22 comparable cases.
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.