How do I install the Text skill?

Run npx skillmds@latest add dvcrn/text in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: docs only. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Text?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

dvcrn (@dvcrn) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Text by dvcrn — Agent Skill

Name: Text
Rating: 4.2 (5 reviews)
Author: dvcrn

File contents

Quick Reference

Task	Load
Creative writing (voice, dialogue, POV)	`writing.md`
Data processing (CSV, regex, encoding)	`data.md`
Academic/citations (APA, MLA, Chicago)	`academic.md`
Marketing copy (headlines, CTA, email)	`copy.md`
Translation/localization	`localization.md`

Universal Text Rules

Encoding

Always verify encoding first: file -bi document.txt
Normalize line endings: tr -d '\r'
Remove BOM if present: sed -i '1s/^\xEF\xBB\xBF//'

Whitespace

Collapse multiple spaces: sed 's/[[:space:]]\+/ /g'
Trim leading/trailing: sed 's/^[[:space:]]*//;s/[[:space:]]*$//'

Common Traps

Smart quotes (" ") break parsers → normalize to "
Em/en dashes (– —) break ASCII → normalize to -
Zero-width chars invisible but break comparisons → strip them
String length ≠ byte length in UTF-8 ("café" = 4 chars, 5 bytes)

Format Detection

# Detect encoding
file -I document.txt

# Detect line endings
cat -A document.txt | head -1
# ^M at end = Windows (CRLF)
# No ^M = Unix (LF)

# Detect delimiter (CSV/TSV)
head -1 file | tr -cd ',;\t|' | wc -c

Quick Transformations

Task	Command
Lowercase	`tr '[:upper:]' '[:lower:]'`
Remove punctuation	`tr -d '[:punct:]'`
Count words	`wc -w`
Count unique lines	`sort -u \| wc -l`
Find duplicates	`sort \| uniq -d`
Extract emails	`grep -oE '[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}'`
Extract URLs	`grep -oE 'https?://[^[:space:]<>"{}

Before Processing Checklist

Encoding verified (UTF-8?)
Line endings normalized
Delimiter identified (for structured text)
Target format/style defined
Edge cases considered (empty, Unicode, special chars)

---name: textdescription: Transform, format, and process text with patterns for writing, data cleaning, localization, citations, and copywriting.---## Quick Reference| Task | Load ||------|------|| Creative writing (voice, dialogue, POV) | `writing.md` || Data processing (CSV, regex, encoding) | `data.md` || Academic/citations (APA, MLA, Chicago) | `academic.md` || Marketing copy (headlines, CTA, email) | `copy.md` || Translation/localization | `localization.md` |---## Universal Text Rules### Encoding- **Always verify encoding first:** `file -bi document.txt`- **Normalize line endings:** `tr -d '\r'`- **Remove BOM if present:** `sed -i '1s/^\xEF\xBB\xBF//'`### Whitespace- **Collapse multiple spaces:** `sed 's/[[:space:]]\+/ /g'`- **Trim leading/trailing:** `sed 's/^[[:space:]]*//;s/[[:space:]]*$//'`### Common Traps- **Smart quotes** (`"` `"`) break parsers → normalize to `"`- **Em/en dashes** (`–` `—`) break ASCII → normalize to `-`- **Zero-width chars** invisible but break comparisons → strip them- **String length ≠ byte length** in UTF-8 (`"café"` = 4 chars, 5 bytes)---## Format Detection```bash# Detect encodingfile -I document.txt# Detect line endingscat -A document.txt | head -1# ^M at end = Windows (CRLF)# No ^M = Unix (LF)# Detect delimiter (CSV/TSV)head -1 file | tr -cd ',;\t|' | wc -c```---## Quick Transformations| Task | Command ||------|---------|| Lowercase | `tr '[:upper:]' '[:lower:]'` || Remove punctuation | `tr -d '[:punct:]'` || Count words | `wc -w` || Count unique lines | `sort -u \| wc -l` || Find duplicates | `sort \| uniq -d` || Extract emails | `grep -oE '[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}'` || Extract URLs | `grep -oE 'https?://[^[:space:]<>"{}|\\^`\[\]]+'` |---## Before Processing Checklist- [ ] Encoding verified (UTF-8?)- [ ] Line endings normalized- [ ] Delimiter identified (for structured text)- [ ] Target format/style defined- [ ] Edge cases considered (empty, Unicode, special chars)

Frequently asked questions

Text