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SKILL verified MIT Self-run

Humanize Writing

skill-s-choung-research-skills-humanizer-kor · by s-choung

Revise AI-generated or mechanical-sounding text so it reads like a specific person wrote it. Use this skill when the user asks to "humanize", "make natural", "remove AI feel", "rewrite like a person wrote it", fix "AI-sounding" or "기계적인" text, or pass AI detection. Also trigger when the user pastes text and asks for a more natural or human tone, in either English or Korean. Do NOT use for summari…

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Install

$ agentstack add skill-s-choung-research-skills-humanizer-kor

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

Security review passed
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3mo ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

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About

Human Writing Revision

Revise text so it reads as if a specific person wrote it for a specific reader.

Three Rules (in priority order)

  1. Don't fabricate. Never invent facts, quotes, sources, personal experience, numbers, named actors, or emotions that aren't in the original. If the original is vague, make it honestly vague — don't fill the gap with plausible fiction.
  2. Remove mechanical signals. Cut banned vocabulary, fix uniform sentence rhythm, break formulaic structure, restore contractions where natural.
  3. Restore specificity. Where the original contains a real claim buried under abstraction, surface it. Where it contains nothing specific, leave the gap visible rather than decorating it.

Process

Step 1: Identify audience and edit depth

Infer the audience from three signals in the text:

  • Terms used without definition → assumed reader knowledge
  • Consequences stated without explanation → assumed reader stakes
  • Pronoun pattern (you/we/one) → assumed relationship

Then choose the lightest sufficient edit:

| Signal | Action | |---|---| | Structure sound, surface awkward | Light polish — vocabulary, rhythm, contractions | | Multiple paragraphs with no actor, event, or consequence | Rewrite — rebuild those paragraphs from their intended claim | | User asks "what's wrong with this?" | Diagnostic — explain problems, don't rewrite unless asked |

If more than half the paragraphs need rebuilding, tell the user the text needs rewriting, not polishing, and confirm before proceeding.

Step 2: Edit

Opening. If the first sentence could open any piece on the same general topic, replace it with the first specific claim, finding, event, or problem.

Second paragraph. Must advance the opening, not retreat to context or methodology. Context goes third or later.

Sentences. Each sentence needs: a named actor doing something, or a specific claim that could be wrong. If a sentence has neither and removing it doesn't break the paragraph, remove it.

Rhythm. Vary sentence length to reflect emphasis. Short after long lands harder. Don't vary for its own sake.

Counter-arguments. If the text dismisses a counter-argument with "both perspectives have merit" or equivalent, either engage it honestly (state the strongest objection, bring evidence, say what the evidence can't settle) or remove the false engagement entirely.

Endings. End when the point has landed. No summaries of what was just said, no generic forward-looking statements, no invitations to continue.

Sources. If a source is cited, it needs author, work, year, and specific claim. If any of these are missing and can't be found, flag it as unverified or remove it. Never present an unverifiable source with the confidence of a verified one.

Step 3: Check for over-correction

Read the result and ask: is every specific detail earned by the original text, or was it inserted because this skill said to be specific? If a detail feels performed rather than observed — if the specificity announces itself — remove it. The goal is writing that could only come from someone who thought about this subject, not writing that demonstrates awareness of humanization techniques.

Language-Specific References

  • For Korean text: read references/korean-patterns.md before editing.
  • For difficult judgment calls or calibration: read references/examples.md.
  • For deeper principles behind any rule above: read references/guide.md.

Output

Return the revised text first, without preamble. Add a brief note on what changed only if the user asked for explanation. Do not describe your process or mention this skill.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.