natural-text-corrector

majiayu000's avatarfrom majiayu000

Corrects English text by removing AI-generated patterns (excessive em dashes, formal phrases), fixing speech-to-text errors (homophones, punctuation, capitalization), and improving natural flow while preserving the author's original voice and intent. Use when user asks to correct, fix, naturalize, or de-AI-ify text from any source.

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When & Why to Use This Skill

The Natural Text Corrector is a sophisticated Claude skill designed to enhance the readability and authenticity of English text. It specializes in 'de-AI-ifying' content by removing recognizable machine patterns, such as excessive em dashes and stilted formal phrasing, while simultaneously correcting speech-to-text (STT) errors like homophones and punctuation. Unlike standard grammar checkers, this skill prioritizes the preservation of the author's unique voice and intent, making it an essential tool for humanizing AI-generated drafts and polishing raw transcriptions into professional, natural-sounding prose.

Use Cases

  • Humanizing AI-Generated Content: Transform robotic or repetitive AI drafts into natural, engaging text by removing 'telltale' patterns like the rule-of-three and overused transition words.
  • Cleaning Up Voice Transcriptions: Automatically fix homophone errors (e.g., their/there), missing punctuation, and capitalization issues in raw speech-to-text outputs from meetings or voice notes.
  • Professional Document Polishing: Refine business emails and reports by replacing overly formal or 'stuffy' phrases with clear, concise, and modern professional language.
  • Improving Sentence Flow and Rhythm: Enhance the overall readability of rough drafts by varying sentence structures and removing redundant transitions without losing the original context.
  • Preserving Technical Voice: Correct grammatical and flow issues in technical documentation while ensuring that industry-specific jargon and the author's expertise remain untouched.
namenatural-text-corrector
descriptionCorrects English text by removing AI-generated patterns (excessive em dashes, formal phrases), fixing speech-to-text errors (homophones, punctuation, capitalization), and improving natural flow while preserving the author's original voice and intent. Use when user asks to correct, fix, naturalize, or de-AI-ify text from any source.

Natural Text Corrector

Purpose

This skill corrects English text from any source - AI-generated content, speech-to-text transcriptions, or human-written text with errors. It applies intelligent, context-aware corrections while preserving the author's original meaning, tone, and voice.

Core Correction Types

1. AI Pattern Removal ("De-AI-ifying")

Excessive Em Dashes (—)

  • AI models overuse em dashes where humans use commas, parentheses, or colons
  • Replace with appropriate punctuation based on sentence flow
  • Example: "The project—which started last year—has been successful" → "The project, which started last year, has been successful"

Formal/Stilted Phrases

  • "It is important to note that" → "Note that" or remove entirely
  • "One must consider" → "Consider" or "Think about"
  • "In light of this information" → "So" or "Therefore"
  • "It is worth mentioning" → "Also" or integrate naturally
  • "As a matter of fact" → "In fact" or "Actually"

Rule of Three Overuse

  • AI creates artificial comprehensiveness with "adjective, adjective, adjective" patterns
  • Simplify to natural expression: "innovative, groundbreaking, transformative solution" → "innovative solution"

Generic Transitions

  • "Furthermore," "Moreover," "Additionally," at start of consecutive sentences
  • Vary with natural flow or remove when unnecessary

2. Speech-to-Text Error Correction

Homophone Disambiguation (Context-Based)

  • their/there/they're - analyze sentence structure and possessives
  • to/too/two - check for direction, excess, or counting
  • your/you're - possessive vs. contraction
  • its/it's - possessive vs. "it is"
  • hear/here - auditory vs. location
  • weather/whether - conditions vs. choice
  • affect/effect - verb vs. noun (usually)
  • then/than - sequence vs. comparison

Missing Punctuation

  • Add periods for sentence boundaries in run-ons
  • Insert commas for natural pauses and clarity
  • Add question marks for interrogative sentences
  • Fix missing apostrophes in contractions

Capitalization

  • Proper nouns, sentence starts, "I"
  • Remove unnecessary mid-sentence capitals (unless proper nouns)

Run-on Sentences

  • Split lengthy, unclear sentences
  • Maintain natural speaking rhythm where appropriate

3. Natural Flow Improvements

Sentence Variety

  • Mix short and long sentences for rhythm
  • Avoid starting multiple consecutive sentences the same way
  • Vary sentence structures (simple, compound, complex)

Word Choice

  • Replace overly formal words in casual contexts
  • Remove redundancies ("past history" → "history")
  • Simplify complex constructions when simpler is clearer

Paragraph Structure

  • Ensure logical flow between ideas
  • Add transitions only when needed for clarity

Correction Process

When correcting text, follow this approach:

  1. Read for Context: Understand the overall tone, audience, and purpose before making changes

  2. Identify Error Types: Scan for AI patterns, speech-to-text errors, and flow issues

  3. Apply Contextual Fixes:

    • For homophones: Check surrounding words and sentence meaning
    • For punctuation: Consider natural pauses and clarity
    • For AI patterns: Replace with how a human would naturally express it
  4. Preserve Voice:

    • Keep the author's personality and style
    • Maintain technical terms and jargon when appropriate
    • Don't over-polish informal or conversational text
  5. One-Pass Correction: Apply all fixes in a single pass, showing the corrected version

Examples

Example 1: AI-Generated Text

Before:

It is important to note that our innovative, groundbreaking, transformative solution—which leverages cutting-edge technology—provides comprehensive, robust, scalable functionality. Moreover, it is worth mentioning that the platform delivers exceptional results. Furthermore, one must consider the significant impact on operational efficiency.

After:

Note that our innovative solution leverages cutting-edge technology to provide scalable functionality. The platform delivers exceptional results and significantly impacts operational efficiency.

Example 2: Speech-to-Text Transcription

Before:

so i was thinking about there presentation and weather or not they should include more data too make it clear your right that its important but i dont no if thats the write approach hear

After:

So I was thinking about their presentation and whether or not they should include more data to make it clear. You're right that it's important, but I don't know if that's the right approach here.

Example 3: Mixed Errors (AI + Speech-to-text)

Before:

It is important to note that—when considering there approach—one must acknowledge the innovative, comprehensive, transformative nature of the solution and weather its going too meet they're needs

After:

When considering their approach, acknowledge the innovative nature of the solution and whether it's going to meet their needs.

Example 4: Run-on Sentence from Speech

Before:

we went to the store and bought some groceries and then we went home and made dinner and after that we watched a movie it was really good

After:

We went to the store and bought some groceries. Then we went home and made dinner. After that, we watched a movie. It was really good.

Example 5: Excessive Formality

Before:

As a matter of fact, in light of the aforementioned circumstances, one must endeavor to ascertain the optimal course of action. It is imperative that we proceed with utmost caution.

After:

Given these circumstances, we need to figure out the best course of action. We should proceed carefully.

Example 6: Technical Content (Preserve Jargon)

Before:

It is important to note that the API endpoint—which utilizes REST architecture—returns a JSON payload. Moreover, the authentication mechanism implements OAuth 2.0 protocol.

After:

The API endpoint utilizes REST architecture and returns a JSON payload. The authentication mechanism implements OAuth 2.0 protocol.

Guidelines

What to Fix:

  • ✓ AI telltale patterns (em dashes, formal phrases, rule of three)
  • ✓ Homophones used incorrectly based on context
  • ✓ Missing or incorrect punctuation
  • ✓ Capitalization errors
  • ✓ Run-on sentences that hurt clarity
  • ✓ Awkward or overly formal phrasing
  • ✓ Redundant transitions

What to Preserve:

  • ✗ Author's tone (casual, formal, technical, creative)
  • ✗ Intentional style choices (fragments, emphasis, repetition)
  • ✗ Technical terminology and domain-specific jargon
  • ✗ Proper nouns, brand names, specific references
  • ✗ Dialectical or regional speech patterns (when clearly intentional)
  • ✗ Creative writing choices (unless they're errors)

Output Format

When correcting text:

  1. Provide the corrected version directly
  2. If requested, briefly explain major changes made
  3. Maintain original formatting (paragraphs, line breaks) unless fixing structural issues

Special Considerations

  • Informal/Conversational Text: Don't over-correct casual language; preserve contractions and colloquialisms
  • Professional/Formal Text: Ensure appropriate formality without AI stuffiness
  • Technical Documentation: Preserve precision and terminology while removing AI patterns
  • Creative Writing: Be extra cautious; preserve style unless errors are clear
  • Lists and Bullet Points: Check for parallel structure and clarity

This skill emphasizes context over rules - always prioritize meaning and natural expression over rigid grammatical perfection.

natural-text-corrector – AI Agent Skills | Claude Skills