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i18n

76.0
C

Internationalization with i18next and react-i18next. Covers translation setup, namespaces, pluralization, and language detection. Triggers on i18n, i18next, translation, t().

Commands Agents Marketplace
#pluralization#Implement internationalization#file structure#translation#namespaces#language#Internationalization#interpolation

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Installation for Agentic Skill

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skilz install settlemint/agent-marketplace/i18n
skilz install settlemint/agent-marketplace/i18n --agent opencode
skilz install settlemint/agent-marketplace/i18n --agent codex
skilz install settlemint/agent-marketplace/i18n --agent gemini

First time? Install Skilz: pip install skilz

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Download Agent Skill ZIP

Extract and copy to ~/.claude/skills/ then restart Claude Desktop

1. Clone the repository:
git clone https://github.com/settlemint/agent-marketplace
2. Copy the agent skill directory:
cp -r agent-marketplace/devtools/skills/i18n ~/.claude/skills/

Need detailed installation help? Check our platform-specific guides:

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Agentic Skill Details

Type
Other
Meta-Domain
N/A
Primary Domain
N/A
Market Score
76.0

Agent Skill Grade

C
Score: 76/100 Click to see breakdown

Score Breakdown

Spec Compliance
14/15
PDA Architecture
18/30
Ease of Use
22/25
Writing Style
8/10
Utility
17/20
Modifiers: -3

Areas to Improve

  • 470 lines in single file with no references; all content loads for every query regardless of complexity
  • File exceeds 100 lines (470) without table of contents for navigation
  • 174 lines of examples always load; simple queries don't need full pluralization example

Recommendations

  • Address 1 high-severity issues first
  • Add trigger phrases to description for discoverability
  • Add table of contents for files over 100 lines

Graded: 1/18/2026

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 (i18n with 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.) here
  • references/examples.md — move the two detailed few-shot examples (262-436 lines)
  • Keep SKILL.md under 150 lines with just quick_start, constraints, and pointers to references

Point bump: This alone gets you +8 points, pushing you to 84/100.

Other Things Worth Fixing

  1. Add a table of contents — At 470 lines, users need navigation. Add ## Contents near the top listing: Quick Start, Patterns, Examples, Research, Constraints. (+2 points)

  2. Number your workflow steps in patterns — Right now you show code blocks with headers like "Namespaces:" but no step numbers. Add: "1. Add keys to JSON 2. Use hook with namespace 3. Call t() with options" for each pattern. (+2 points)

  3. XML tags in metadata — Minor thing, but your frontmatter uses <usage> and <notes> tags. Strip those out; keep frontmatter as clean YAML. (-5 penalty you're currently taking, easy to fix)

Quick Wins

  • High impact: Split into references/ directory (+8 points, fixes the main PDA issue)
  • Medium impact: Add TOC and numbered workflow steps (+4 points combined)
  • Quick fix: Remove XML tags from frontmatter (no point cost, just cleanup)
  • Result: You'd hit 88/100 with these changes

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AI-Detected Topics

Extracted using NLP analysis

pluralization Implement internationalization file structure translation namespaces language Internationalization interpolation structure Trans

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