Best use case
# Skill Name is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
text-cleaner-lite
Teams using # Skill Name 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/text-cleaner-lite/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How # Skill Name Compares
| Feature / Agent | # Skill Name | 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?
text-cleaner-lite
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
# Skill Name
text-cleaner-lite
## Function Description
Normalize whitespace, remove duplicated blank lines, and trim leading/trailing spaces.
## Input Parameters
- raw_text (string), keep_newlines (boolean, optional)
## Output Result
- cleaned_text (string)
## Usage Example
`ash
python main.py --input sample.txt --mode clean
`
## Risk Statement
- Risk level: L1
- This skill may perform actions matching category $(@{skill_id=skill_001; name=text-cleaner-lite; category=text-processing; risk_level=L1; source_template=skillsmp_download/1/SKILL.md; description=Normalize whitespace, remove duplicated blank lines, and trim leading/trailing spaces.; input=raw_text (string), keep_newlines (boolean, optional); output=cleaned_text (string); tags=System.Object[]; example=python main.py --input sample.txt --mode clean}.category) and should be reviewed before production use.
## Category Tags
- text-processing, normalization, safeRelated Skills
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