solo-humanize

📁 fortunto2/solo-factory 📅 8 days ago
10
总安装量
10
周安装量
#29884
全站排名
安装命令
npx skills add https://github.com/fortunto2/solo-factory --skill solo-humanize

Agent 安装分布

opencode 10
gemini-cli 10
claude-code 10
github-copilot 10
codex 10
kimi-cli 10

Skill 文档

/humanize

Strip AI writing patterns from user-facing text. Takes a file or pasted text and rewrites it to read like a human wrote it, without losing meaning or structure.

Why this exists

LLM output has recognizable tells — em dashes, stock phrases, promotional inflation, performed authenticity. Readers (and Google) notice. This skill catches those patterns and rewrites them.

When to use

  • After /content-gen, /landing-gen, /video-promo — polish the output
  • Before publishing any user-facing prose (blog posts, landing pages, emails)
  • When editing CLAUDE.md or docs that will be read by humans
  • Standalone: /humanize path/to/file.md

Input

  • File path from $ARGUMENTS — reads and rewrites in place
  • No argument — asks to paste text, outputs cleaned version
  • Works on .md, .txt, and text content in .tsx/.html (string literals only)

Pattern Catalog

1. Em Dash Overuse (—)

The most obvious AI tell. Replace with commas, periods, colons, or restructure the sentence.

Before After
“The tool — which is free — works great” “The tool (which is free) works great”
“Three features — speed, security, simplicity” “Three features: speed, security, simplicity”
“We built this — and it changed everything” “We built this. It changed everything.”

Rule: Max 1 em dash per 500 words. Zero is better.

2. Stock Phrases

Phrases that signal “AI wrote this.” Remove or replace with specific language.

Filler phrases (delete entirely):

  • “it’s worth noting that” → (just state the thing)
  • “at the end of the day” → (cut)
  • “in today’s world” / “in the modern landscape” → (cut)
  • “without further ado” → (cut)
  • “let’s dive in” / “let’s explore” → (cut)

Promotional inflation (replace with specifics):

  • “game-changer” → what specifically changed?
  • “revolutionary” → what’s actually new?
  • “cutting-edge” → describe the technology
  • “seamless” → “works without configuration” (or whatever it actually does)
  • “leverage” → “use”
  • “robust” → “handles X edge cases” (specific)
  • “streamline” → “cut steps from N to M”
  • “empower” → what can the user now do?
  • “unlock” → what’s the actual capability?

Performed authenticity (rewrite):

  • “to be honest” → (if you need to say this, the rest wasn’t honest?)
  • “let me be frank” → (just be frank)
  • “I have to say” → (just say it)
  • “honestly” → (cut)
  • “the truth is” → (cut, state the truth directly)

3. Rule of Three

AI loves triplets: “fast, secure, and scalable.” Real writing varies list length.

Before After
“Fast, secure, and scalable” “Fast and secure” (if scalable isn’t proven)
“Build, deploy, and iterate” “Build and ship” (if that’s what you mean)
Three bullet points that all say the same thing One clear bullet

Rule: If you find 3+ triplet lists in one document, break at least half of them.

4. Structural Patterns

Every section has the same shape: AI tends to write: heading → one-sentence intro → 3 bullets → transition sentence. Real writing varies section length and structure.

Hedging sandwich: “While X has limitations, it offers Y, making it Z.” → Pick a side. State it.

False balance: “On one hand X, on the other hand Y.” → If one side is clearly better, say so.

5. Sycophantic Openers

  • “Great question!” → (cut)
  • “That’s a fantastic idea!” → (cut, or say what’s specifically good about it)
  • “Absolutely!” → (cut if not genuine agreement)
  • “I’d be happy to help!” → (just help)

6. Passive Voice / Weak Verbs

  • “It should be noted that” → (cut, just note it)
  • “There are several factors that” → name the factors
  • “It is important to” → say why
  • “This can be achieved by” → “Do X”

Process

  1. Read the input — file path or pasted text.

  2. Scan for patterns — check each category above. Count violations per category.

  3. Rewrite — fix each violation while preserving:

    • Technical accuracy (don’t change code, commands, or technical terms)
    • Structure (headings, lists, code blocks stay)
    • Tone intent (if the original was casual, keep it casual)
    • Length (aim for same or shorter, never longer)
  4. Report what changed:

    Humanized: {file or "pasted text"}
    
    Changes:
      Em dashes:  {N} removed
      Stock phrases: {N} replaced
      Inflation: {N} deflated
      Triplets: {N} broken
      Sycophancy: {N} cut
      Total: {N} patterns fixed
    
    Before: {word count}
    After:  {word count}
    
  5. If file path: write the cleaned version back. Show a diff summary. If pasted text: output the cleaned version directly.

What NOT to change

  • Code blocks and inline code
  • Technical terms, library names, CLI commands
  • Quotes from other people (attributed quotes stay verbatim)
  • Numbers, dates, URLs
  • Headings structure (don’t merge or split sections)
  • Content meaning — only rephrase, never add or remove ideas

Edge Cases

  • Short text (<50 words): just apply stock phrase filter, skip structural analysis
  • Already clean: report “No AI patterns found. Text looks human.”
  • Code-heavy docs: skip code blocks entirely, only process prose sections
  • Non-English text: apply em dash and structural rules (they’re universal), skip English stock phrases