i18n
Internationalization with i18next and react-i18next. Covers translation setup, namespaces, pluralization, and language detection. Triggers on i18n, i18next, translation, t().
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Installation for Agentic Skill
View all platforms →skilz install settlemint/agent-marketplace/i18nskilz install settlemint/agent-marketplace/i18n --agent opencodeskilz install settlemint/agent-marketplace/i18n --agent codexskilz install settlemint/agent-marketplace/i18n --agent geminiFirst time? Install Skilz: pip install skilz
Works with 14 AI coding assistants
Cursor, Aider, Copilot, Windsurf, Qwen, Kimi, and more...
Extract and copy to ~/.claude/skills/ then restart Claude Desktop
git clone https://github.com/settlemint/agent-marketplacecp -r agent-marketplace/devtools/skills/i18n ~/.claude/skills/Need detailed installation help? Check our platform-specific guides:
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Agentic Skill Details
- Owner
- settlemint (GitHub)
- Repository
- agent-marketplace
- Type
- Other
- Meta-Domain
- Primary Domain
- Market Score
- 0
Agent Skill Grade
C Score: 76/100 Click to see breakdown
Score Breakdown
Areas to Improve
- No Progressive Disclosure Structure
- Missing TOC for Long File
- Large Examples Block Token Budget
Recommendations
- Address 1 high-severity issues first
- Add trigger phrases to description for discoverability
- Add table of contents for files over 100 lines
Graded: 2026-01-19
Developer Feedback
I took a look at your i18n skill and wanted to share some thoughts.
Links:
The TL;DR
You're at 76/100, solidly in C territory — that's "adequate with gaps." The skill has strong fundamentals (Spec Compliance scores 14/15), but it's being weighed down by Progressive Disclosure Architecture (18/30). The core issue: everything lives in one 470-line file, so users pay the token cost even for simple queries. Fix that and you're looking at 84-86/100 range.
What's Working Well
- Spec compliance is tight — your YAML frontmatter is valid, naming convention is correct (
i18nwith proper kebab-case), and your description nails the trigger patterns. You've got 33 different activation patterns covering i18next, locale, RTL/LTR, pluralization — that's comprehensive discoverability. - Your examples hit the mark — the two detailed input/output samples (pluralization and context-aware translations) show real-world problems and solutions. Users can see exactly what they're getting.
- Terminology is consistent — "i18next," "namespace," "translation" throughout. No confusion about what you're talking about.
The Big One: File Size Architecture
Here's the thing that's holding you back: 470 lines in a single SKILL.md with no progressive disclosure structure. Every query loads the entire file — including those two hefty few-shot examples (174 lines total) — even if someone just needs a quick syntax pattern.
Why it matters: Users asking "how do I set up i18next?" shouldn't load your full pluralization examples. You're burning tokens on content that isn't relevant to that query.
The fix: Create a references/ directory:
references/patterns.md— move your 8 patterns (namespaces, pluralization, contexts, etc....
AI-Detected Topics
Extracted using NLP analysis
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