Text

What This Skill Does

The Text skill is a versatile, command-line driven utility for OpenClaw AI agents, designed to handle the complexities of text manipulation. It streamlines the lifecycle of text processing—from initial ingestion and sanitization to stylistic transformation and structured data extraction. Whether you are normalizing messy CSV data, formatting academic citations, or fine-tuning marketing copy, this skill provides the necessary patterns to ensure high-quality output. It bridges the gap between raw, potentially malformed input and clean, professional-grade text.

Installation

To integrate this skill into your environment, use the OpenClaw hub command: clawhub install openclaw/skills/skills/ivangdavila/text

Use Cases

This skill is highly effective for several core workflows:

• Data Engineering: Automatically detecting encoding, normalizing line endings, and cleaning whitespace in large datasets.
• Content Creation: Adjusting dialogue or tone for creative writing tasks while maintaining structural integrity.
• Academic Research: Generating consistent citations and ensuring bibliography formats meet standards like APA, MLA, or Chicago.
• Content Marketing: Rapidly iterating on headlines, call-to-actions, and professional email drafting.
• Legacy Cleanup: Removing invisible characters, normalizing smart quotes, and stripping Byte Order Marks (BOM) from older documents that break modern parsers.

Example Prompts

1. "Check the encoding of my document.csv, remove the BOM, normalize the line endings to LF, and convert the entire document to lowercase."
2. "Extract all unique email addresses and URLs from the provided research notes and save the result as a sorted list."
3. "Help me rewrite this draft email to sound more professional and concise, ensuring all smart quotes are replaced with standard ones for the final output."

Tips & Limitations

• Safety First: Always perform a dry run on critical data using the file and head commands before applying destructive transformations like sed -i.
• UTF-8 Awareness: Always remember that byte length and character length are not synonymous. If you are writing custom regex for specific character counts, verify your logic against UTF-8 encoding rules.
• The Trap of Formatting: Be wary of 'smart' punctuation generated by word processors, as these will often cause errors in downstream code parsers or database imports. Use the normalization patterns provided to ensure data consistency. Avoid processing massive multi-gigabyte files entirely in-memory; use the provided stream-friendly command-line patterns where possible to save system resources.