Best use case
language-detect is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Detect the language of text using AI
Teams using language-detect should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/expanso-language-detect/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How language-detect Compares
| Feature / Agent | language-detect | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Detect the language of text using AI
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# language-detect Detect the language of text using AI ## Requirements - Expanso Edge installed (`expanso-edge` binary in PATH) - Install via: `clawhub install expanso-edge` ## Usage ### CLI Pipeline ```bash # Run standalone echo '<input>' | expanso-edge run pipeline-cli.yaml ``` ### MCP Pipeline ```bash # Start as MCP server expanso-edge run pipeline-mcp.yaml ``` ### Deploy to Expanso Cloud ```bash expanso-cli job deploy https://skills.expanso.io/language-detect/pipeline-cli.yaml ``` ## Files | File | Purpose | |------|---------| | `skill.yaml` | Skill metadata (inputs, outputs, credentials) | | `pipeline-cli.yaml` | Standalone CLI pipeline | | `pipeline-mcp.yaml` | MCP server pipeline |
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