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jta杰塔

Agent Skill

jta 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

321

周安装

13

GitHub Stars

22

下载量

101
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:jta(杰塔)
来源仓库:https://github.com/hikanner/agent-skills
仓库路径:skills/jta
安装命令:
npx skills add https://github.com/hikanner/agent-skills --skill jta
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/hikanner/agent-skills --skill jta

简介

jta 用于查找、检索和筛选相关信息。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。
  • 可结合来源仓库和原始 README 继续核验具体用法。
  • 安装前建议确认权限范围、维护状态,以及是否会触发联网或命令执行。
  • 使用时需注意其功能边界,避免过度依赖自动化结果。

SKILL.md

Jta Translation

AI-powered JSON internationalization file translator with Agentic reflection mechanism.

When to Use This Skill

  • User asks to translate JSON i18n/locale files
  • User mentions "internationalization", "i18n", "l10n", or "locale"
  • User wants to add new languages to their project
  • User needs to update existing translations
  • User mentions specific languages like "translate to Chinese/Japanese/Korean"

Core Capabilities

  1. Agentic Translation: AI translates, evaluates, and improves its own work (3x API calls per batch)
  2. Smart Terminology: Automatically detects and maintains consistent terms (brand names, technical terms)
  3. Format Protection: Preserves {variables}, {{placeholders}}, HTML tags, URLs, Markdown
  4. Incremental Mode: Only translates new/changed content (saves 80-90% API cost on updates)
  5. 27 Languages: Including RTL languages (Arabic, Hebrew, Persian, Urdu)

Instructions

Step 1: Check if jta is installed

# Check if jta exists
if ! command -v jta &> /dev/null; then
  echo "jta not found, will install"
fi

Step 2: Install jta if needed

# Detect OS and install jta
OS="$(uname -s)"
ARCH="$(uname -m)"

if [[ "$OS" == "Darwin"* ]]; then
  # macOS - try Homebrew first
  if command -v brew &> /dev/null; then
    brew tap hikanner/jta
    brew install jta
  else
    # Download binary
    if [[ "$ARCH" == "arm64" ]]; then
      curl -L https://github.com/hikanner/jta/releases/latest/download/jta-darwin-arm64 -o jta
    else
      curl -L https://github.com/hikanner/jta/releases/latest/download/jta-darwin-amd64 -o jta
    fi
    chmod +x jta
    sudo mv jta /usr/local/bin/
  fi
elif [[ "$OS" == "Linux"* ]]; then
  # Linux
  curl -L https://github.com/hikanner/jta/releases/latest/download/jta-linux-amd64 -o jta
  chmod +x jta
  sudo mv jta /usr/local/bin/
fi

# Verify installation
jta --version

Step 3: Check for API key and set provider

Jta requires an AI provider API key. Check in this order and set the provider flag:

# Detect API key and set provider flag
if [[ -n "$ANTHROPIC_API_KEY" ]]; then
  echo "✓ Anthropic API key found"
  PROVIDER_FLAG="--provider anthropic"
elif [[ -n "$GEMINI_API_KEY" ]]; then
  echo "✓ Gemini API key found"
  PROVIDER_FLAG="--provider gemini"
elif [[ -n "$OPENAI_API_KEY" ]]; then
  echo "✓ OpenAI API key found"
  PROVIDER_FLAG=""  # OpenAI is default, no flag needed
else
  echo "✗ No API key found. Please set one of:"
  echo "  export OPENAI_API_KEY=sk-..."
  echo "  export ANTHROPIC_API_KEY=sk-ant-..."
  echo "  export GEMINI_API_KEY=..."
  exit 1
fi

Important: Save the PROVIDER_FLAG value to use in translation commands.

Step 4: Identify source file

# Find JSON files in common i18n/locale directories
find . -type f -name "*.json" \
  \( -path "*/locales/*" -o \
     -path "*/locale/*" -o \
     -path "*/i18n/*" -o \
     -path "*/lang/*" -o \
     -path "*/translations/*" \) \
  | head -20

Ask user to confirm which file to translate if multiple found.

Step 5: Determine translation requirements

Ask user (if not specified in their request):

  • Target languages (e.g., "zh,ja,ko")
  • Whether to use incremental mode (recommended for updates)
  • Output location preference

Step 6: Execute translation

Always use $PROVIDER_FLAG from Step 3 to ensure the correct AI provider is used:

# Basic translation with detected provider
jta <source-file> --to <target-langs> $PROVIDER_FLAG

# Examples:
# Single language
jta en.json --to zh $PROVIDER_FLAG

# Multiple languages
jta en.json --to zh,ja,ko $PROVIDER_FLAG

# Incremental mode (for updates)
jta en.json --to zh --incremental $PROVIDER_FLAG

# With custom output
jta en.json --to zh --output ./locales/zh.json $PROVIDER_FLAG

# Non-interactive mode (for multiple languages)
jta en.json --to zh,ja,ko,es,fr -y $PROVIDER_FLAG

# Override with specific model for quality
jta en.json --to zh --provider anthropic --model claude-sonnet-4-5

# Translate specific keys only
jta en.json --to zh --keys "settings.*,user.*" $PROVIDER_FLAG

# Exclude certain keys
jta en.json --to zh --exclude-keys "admin.*,internal.*" $PROVIDER_FLAG

Step 7: Verify results

After translation completes:

# Check output files exist
ls -lh <output-files>

# Validate JSON structure
for file in <output-files>; do
  if jq empty "$file" 2>/dev/null; then
    echo "✓ $file is valid JSON"
  else
    echo "✗ $file has invalid JSON"
  fi
done

Step 8: Report to user

Show the user:

  • Translation statistics (total items, success rate, API calls, duration)
  • Location of output files
  • Any errors or warnings
  • Cost implications if significant (e.g., "Used 15 API calls, estimated $0.30")

Terminology Management

Jta automatically creates a .jta/ directory to store terminology:

.jta/
├── terminology.json       # Source language terms (preserve + consistent)
├── terminology.zh.json    # Chinese translations
├── terminology.ja.json    # Japanese translations
└── terminology.ko.json    # Korean translations

terminology.json structure:

{
  "version": "1.0",
  "sourceLanguage": "en",
  "preserveTerms": ["API", "OAuth", "GitHub"],
  "consistentTerms": ["credits", "workspace", "prompt"]
}

Users can manually edit these files for custom terminology.

Common Patterns

Note: Always include $PROVIDER_FLAG (from Step 3) in your commands.

Pattern 1: First-time translation

# User: "Translate my en.json to Chinese and Japanese"
jta locales/en.json --to zh,ja -y $PROVIDER_FLAG

Pattern 2: Update existing translations

# User: "I added new keys to en.json, update the translations"
jta locales/en.json --to zh,ja --incremental -y $PROVIDER_FLAG

Pattern 3: Translate specific sections

# User: "Only translate the settings and user sections"
jta en.json --to zh --keys "settings.**,user.**" $PROVIDER_FLAG

Pattern 4: High-quality translation

# User: "Use the best model for highest quality"
jta en.json --to zh --provider anthropic --model claude-sonnet-4-5

Pattern 5: RTL languages

# User: "Translate to Arabic and Hebrew"
jta en.json --to ar,he -y $PROVIDER_FLAG
# Jta automatically handles bidirectional text markers

Error Handling

Error: "jta: command not found"

  • Run the installation script from Step 2
  • Verify with jta --version

Error: "API key not set"

Prompt user:

Jta requires an AI provider API key. Please set one of:

For OpenAI (recommended):
  export OPENAI_API_KEY=sk-...
  Get key at: https://platform.openai.com/api-keys

For Anthropic:
  export ANTHROPIC_API_KEY=sk-ant-...
  Get key at: https://console.anthropic.com/

For Google Gemini:
  export GEMINI_API_KEY=...
  Get key at: https://aistudio.google.com/app/apikey

Error: "Rate limit exceeded"

# Reduce batch size and concurrency
jta en.json --to zh --batch-size 10 --concurrency 1

Error: "Invalid JSON"

# Validate source file
jq . source.json

Error: Translation quality issues

  1. Try a better model: jta en.json --to zh --provider anthropic --model claude-sonnet-4-5
  2. Check terminology files in .jta/ and edit if needed
  3. Use verbose mode to debug: jta en.json --to zh --verbose

Performance Tips

  • Small files (<100 keys): Use default settings
  • Large files (>500 keys): Use --batch-size 10 --concurrency 2
  • Frequent updates: Always use --incremental to save cost
  • Quality priority: Use --provider anthropic --model claude-sonnet-4-5
  • Speed priority: Use --provider openai --model gpt-3.5-turbo (if available)
  • Cost priority: Use incremental mode + larger batch sizes

Supported Languages

27 languages with full support:

Left-to-Right (LTR):

  • European: en, es, fr, de, it, pt, ru, nl, pl, tr
  • Asian: zh, zh-TW, ja, ko, th, vi, id, ms, hi, bn, si, ne, my

Right-to-Left (RTL):

  • Middle Eastern: ar, fa, he, ur

View all supported languages:

jta --list-languages

Output Format

Jta produces:

  1. Translated JSON files: Same structure as source, with translations
  2. Statistics: Printed to console
  3. Terminology files: In .jta/ directory for consistency

Always inform the user of:

  • Number of items translated
  • Success/failure count
  • Output file locations
  • Any errors or warnings
  • API usage and estimated cost (if significant)

Advanced Options

Note: Remember to include $PROVIDER_FLAG in your commands.

# Skip terminology detection (use existing)
jta en.json --to zh --skip-terminology $PROVIDER_FLAG

# Disable terminology management completely
jta en.json --to zh --no-terminology $PROVIDER_FLAG

# Re-detect terminology (when source language changes)
jta en.json --to zh --redetect-terms $PROVIDER_FLAG

# Custom terminology directory (for shared terms)
jta en.json --to zh --terminology-dir ../shared-terms/ $PROVIDER_FLAG

# Specify source language explicitly
jta myfile.json --source-lang en --to zh $PROVIDER_FLAG

# Custom batch size and concurrency
jta en.json --to zh --batch-size 20 --concurrency 3 $PROVIDER_FLAG

# Verbose output for debugging
jta en.json --to zh --verbose $PROVIDER_FLAG

Examples

See examples/ directory for detailed, step-by-step use cases.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

28.97%
按下载量换算29

Gemini CLI

20.08%
按下载量换算20

Antigravity

16.14%
按下载量换算16

windsurf

12.72%
按下载量换算13

OpenCode

7.61%
按下载量换算8

Codex

3.39%
按下载量换算3

安全审计

Gen Agent Trust Hub

未通过

Socket

通过

Snyk

未通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。

来源信息

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