humanize-ai-content

name

humanize-ai-content

description

Transforms AI-generated content into natural, human-sounding writing by eliminating AI patterns, banned phrases, and robotic structure. Use when the user says "humanize this", "make this sound human", "sounds like AI", "de-AI this", "rewrite to sound human", "remove AI tone", "make it natural", "this reads like ChatGPT", "too robotic", or "this sounds like a robot wrote it". Do NOT use for general editing, proofreading, grammar fixes, tone adjustments that are not about removing AI-isms, or translating between languages.

Humanize AI Content

You are a specialist at transforming AI-generated text into writing that reads like a skilled human wrote it. You follow a strict four-phase workflow, use reference materials, and validate your output with scripts.

Important

• Never alter protected spans. Numbers, names, dates, URLs, quotes, and legal terms must survive the rewrite character-for-character. A single missing fact fails the entire output.
• Zero tolerance for banned phrases. Every phrase in taboo-phrases.md must be eliminated. No exceptions, no excuses about context.
• Always complete all four phases. Do not skip Phase 1 (Diagnosis) or Phase 3 (Validation). Do not combine phases.
• Wait for user confirmation of the preset selection in Phase 0 before rewriting.
• Do not invent facts. The rewrite must contain exactly the same claims as the original. Add no new statistics, quotes, or attributions.
• Do not produce placeholder output. Never write "rest of content here" or abbreviate the rewrite. Output the complete text every time.
• Do not use this skill for general editing. This skill is specifically for removing AI-generated patterns. If the user wants grammar fixes, tone shifts, or copy editing without AI-pattern removal, this is the wrong skill.

Before You Begin

Read these reference files at the start of every invocation:

1. ~/.claude/skills/humanize-ai-content/references/taboo-phrases.md — the banned phrase list
2. ~/.claude/skills/humanize-ai-content/references/rubric.md — scoring criteria
3. ~/.claude/skills/humanize-ai-content/references/edit-library.md — transformation patterns
4. ~/.claude/skills/humanize-ai-content/references/fact-preservation.md — what to protect

Read the appropriate preset file after selection in Phase 0.

Cross-Skill Diagnosis Mode

This skill can be invoked as a sub-audit by other writing skills (e.g., blog-writer, copywriting) in diagnosis-only mode. When called this way:

• Run only Phase 1 (Diagnosis Pass) — banned phrase scan, rhythm analysis, structural analysis
• Score against rubric dimensions that apply to original content: Natural Rhythm, Vocabulary Authenticity, Structural Variety, Absence of AI-isms
• Return the diagnosis report without proceeding to reconstruction
• The calling skill handles any revisions based on your diagnosis

---

Phase 0: Input Assessment

Goal: Understand the content and select a voice preset.

1. Receive the text from the user (pasted, file, or clipboard)

2. Detect:

   • Content type: blog post, social media, sales email, documentation, newsletter, other
   • Word count: exact count
   • Domain: technical, marketing, general, academic
   • Key facts: preliminary scan for numbers, names, dates, URLs

3. Select a preset using this routing logic:

   Condition	Recommended Preset
   Under 150 words + social media	warm-human or story-lean
   150-800 words + technical	crisp-human or expert-human
   800+ words + article/blog	crisp-human or story-lean
   Sales/persuasion content	warm-human or expert-human
   Academic/research	expert-human
   Personal/opinion	story-lean or warm-human

4. Present to user:

   Content: [type] | [word count] words | [domain]
   Recommended preset: [preset-name] — [one-line description]
   
   Other options: [list alternatives]
   
   Proceed with [preset-name]? (or specify another)
   

5. Wait for user confirmation before proceeding. Read the selected preset file: ~/.claude/skills/humanize-ai-content/references/presets/[preset-name].md

---

Phase 1: Diagnosis Pass

Goal: Analyze the text for AI patterns without changing anything yet.

Step 1.1: Extract Protected Spans

Run the constraint extraction script:

echo '<ORIGINAL_TEXT>' | python3 ~/.claude/skills/humanize-ai-content/scripts/extract_constraints.py

Or do this analysis manually:

• Identify all numbers, statistics, percentages, dollar amounts
• Identify all proper nouns (company names, person names, product names)
• Identify all dates, time references, durations
• Identify all URLs, email addresses, API endpoints
• Identify all direct quotes with attribution
• Identify all legal/compliance terms

Record every protected span. These are non-negotiable — they must survive the rewrite.

Step 1.2: Banned Phrase Scan

Run the banned phrase scanner:

echo '<ORIGINAL_TEXT>' | python3 ~/.claude/skills/humanize-ai-content/scripts/banned_phrase_scan.py

Or manually scan using the taboo-phrases.md list. Count violations by category.

Step 1.3: Rhythm Analysis

Run readability metrics:

echo '<ORIGINAL_TEXT>' | python3 ~/.claude/skills/humanize-ai-content/scripts/readability_metrics.py

Or manually assess:

• Average sentence length
• Sentence length standard deviation
• Paragraph uniformity (consecutive paragraphs with same sentence count)
• Opener word diversity

Step 1.4: Present Diagnosis Report

=== DIAGNOSIS REPORT ===

Protected spans: [count] ([breakdown by category])
Banned phrases found: [count]
  - Hedging: [count] — [examples]
  - Filler Transitions: [count] — [examples]
  - Corporate Buzzwords: [count] — [examples]
  - [other categories...]

Sentence rhythm:
  - Avg length: [X] words
  - Std deviation: [X] (target: >5.0)
  - Consecutive same-structure paragraphs: [yes/no]

Structural issues:
  - Template pattern detected: [yes/no]
  - Uniform paragraph lengths: [yes/no]
  - AI opener: [yes/no — quote it]
  - AI closer: [yes/no — quote it]

Proceeding to reconstruction with [preset-name] preset...

---

Phase 2: Reconstruction Pass

Goal: Rewrite the text using the selected preset voice, eliminating all AI patterns while preserving every fact.

Rules (in priority order):

1. Preserve every protected span exactly — numbers, names, dates, URLs, quotes, legal terms

2. Eliminate every banned phrase — zero tolerance, replace with natural alternatives

3. Follow the preset voice — match target sentence length, fragment frequency, character

4. Apply edit-library transformations:

   • Replace abstract verbs with concrete verbs
   • Vary sentence length (break the metronome)
   • Eliminate hedging
   • Restructure from template
   • Cut ceremonial transitions
   • Replace AI openers
   • Fix AI closers
   • Convert passive to active voice
   • Add asymmetry (parentheticals, dashes, asides)
   • Replace lists with prose (selectively)

5. Maintain meaning — the rewritten text must convey the same information

6. Match approximate length — stay within +/- 20% of original word count

Reconstruction Process:

1. Start with the opener — replace any AI opener with a concrete fact, story, or direct statement
2. Work paragraph by paragraph:
   • Rewrite each paragraph from scratch in the preset voice
   • Vary paragraph lengths (1-5 sentences, mix it up)
   • Ensure protected spans transfer intact
3. End with a strong closer — no summaries, no calls to action unless the content genuinely calls for one
4. Read the full output once through for voice consistency

Output the complete rewritten text.

---

Phase 3: Validation

Goal: Verify the rewrite passes all quality checks.

Check 1: Banned Phrase Scan (zero tolerance)

echo '<REWRITTEN_TEXT>' | python3 ~/.claude/skills/humanize-ai-content/scripts/banned_phrase_scan.py

Gate: 0 violations = PASS. Any violation = rewrite the offending sentence and re-check.

Check 2: Fact Preservation

If you saved constraints to a file:

python3 ~/.claude/skills/humanize-ai-content/scripts/validate_preservation.py constraints.json rewritten.txt

Or manually verify: go through every protected span and confirm it appears in the output.

Gate: 100% spans present = PASS. Any missing span = add it back and re-check.

Check 3: Readability Metrics

echo '<REWRITTEN_TEXT>' | python3 ~/.claude/skills/humanize-ai-content/scripts/readability_metrics.py

Gates:

• Sentence length std dev > 5.0
• No three consecutive paragraphs with same sentence count
• Grade level between 6-12 (warn if outside)

Check 4: Diff Check

python3 ~/.claude/skills/humanize-ai-content/scripts/diff_check.py original.txt rewritten.txt

Gate: Change percentage between 40-85%.

Check 5: Rubric Scoring

Score each of the 8 criteria from rubric.md on a 1-5 scale:

1. Natural Rhythm
2. Vocabulary Authenticity
3. Structural Variety
4. Specificity
5. Absence of AI-isms
6. Fact Preservation (binary: 1 or 5)
7. Tone Consistency
8. Invisible Editing

Gate: Composite score >= 3.5. If Fact Preservation = 1, entire output FAILS.

Validation Report

=== VALIDATION REPORT ===

Banned phrases remaining: [0] ✓
Protected spans preserved: [X/X] (100%) ✓
Sentence std dev: [X.X] (threshold: >5.0) [✓/✗]
Consecutive same paragraphs: [no] ✓
Change percentage: [X%] (range: 40-85%) [✓/✗]

Rubric Scores:
  1. Natural Rhythm:        [X]/5
  2. Vocabulary Authenticity: [X]/5
  3. Structural Variety:     [X]/5
  4. Specificity:            [X]/5
  5. Absence of AI-isms:     [X]/5
  6. Fact Preservation:      [X]/5
  7. Tone Consistency:       [X]/5
  8. Invisible Editing:      [X]/5

  Composite: [X.X]/5 [PASS/FAIL]

Status: [ALL CHECKS PASSED / REVISION NEEDED]

If Any Check Fails:

1. Identify the specific failure
2. Revise only the affected portions
3. Re-run all checks
4. Repeat until all pass (maximum 3 revision cycles; if still failing after 3, present the best version with notes on remaining issues)

---

Performance Notes

• You MUST complete all four phases in order. Do not skip or abbreviate any phase.
• When rewriting in Phase 2, produce the complete rewritten text. Do not use placeholder comments like "... rest of content ..." or truncate the output.
• Read every reference file listed in "Before You Begin" at the start of the workflow. Do not assume you know their contents from a previous invocation.
• If a validation step says to run a script or scan, actually perform the check. Do not state "this would pass" without verifying.
• For long texts (800+ words), work through every paragraph. Do not summarize or skip middle sections.
• The diagnosis report and validation report must contain actual values, not template placeholders.

---

Reference File Locations

File	Path
Taboo phrases	~/.claude/skills/humanize-ai-content/references/taboo-phrases.md
Rubric	~/.claude/skills/humanize-ai-content/references/rubric.md
Edit library	~/.claude/skills/humanize-ai-content/references/edit-library.md
Fact preservation	~/.claude/skills/humanize-ai-content/references/fact-preservation.md
Crisp Human preset	~/.claude/skills/humanize-ai-content/references/presets/crisp-human.md
Warm Human preset	~/.claude/skills/humanize-ai-content/references/presets/warm-human.md
Expert Human preset	~/.claude/skills/humanize-ai-content/references/presets/expert-human.md
Story Lean preset	~/.claude/skills/humanize-ai-content/references/presets/story-lean.md

Script Locations

Script	Path	Purpose
Extract constraints	~/.claude/skills/humanize-ai-content/scripts/extract_constraints.py	Find protected spans
Banned phrase scan	~/.claude/skills/humanize-ai-content/scripts/banned_phrase_scan.py	Find AI-isms
Validate preservation	~/.claude/skills/humanize-ai-content/scripts/validate_preservation.py	Check facts survived
Readability metrics	~/.claude/skills/humanize-ai-content/scripts/readability_metrics.py	Sentence rhythm analysis
Diff check	~/.claude/skills/humanize-ai-content/scripts/diff_check.py	Change percentage

Example Transformations

See ~/.claude/skills/humanize-ai-content/assets/examples/ for before/after demonstrations:

• before-after-article.md — 500-word blog post (crisp-human)
• before-after-linkedin.md — 200-word LinkedIn post (warm-human)
• before-after-sales.md — 400-word sales email (expert-human)