| name | tool-humanizer |
| description | Remove AI-generated writing patterns and restore natural human voice. Detects and fixes 50+ AI tells: inflated symbolism, promotional language, hedging, corporate buzzwords, robotic structure, em dash overuse, rule of three, vague attributions, negative parallelisms, conjunctive phrase abuse. Three modes: quick (obvious patterns), standard (full scan + score), deep (voice-matched using brand_context/voice-profile.md). Called automatically by execution skills as a post-processing step. Also invoked standalone: "humanize this", "de-AI this", "make this sound human", "remove AI patterns", "clean up this copy". Does NOT trigger for brand voice extraction, positioning, or ICP work. Does NOT trigger for content that is intentionally formal or academic.
|
Humanizer
Strip AI-generated patterns from text. Make it sound like a person wrote it.
Outcome
Input text returned with AI patterns removed, scored before and after on a 0-10 human-ness scale. Change log shows exactly what was fixed. Output either replaces the original or is saved alongside it.
Context Needs
| File | Load level | How it shapes this skill |
|---|
brand_context/voice-profile.md | full | Replacements use the brand's actual vocabulary, rhythm, and connectors instead of generic "human" phrasing |
brand_context/samples.md | tone refs | Reference for what on-brand sounds like |
context/learnings.md | ## tool-humanizer section | Patterns the user cares about most, false positives to skip |
Load if they exist. Works standalone with generic replacements.
Instructions
Step 1: Detect Mode
Choose from context or ask: "Quick pass, full cleanup, or voice-matched?"
| Mode | What happens | Best for |
|---|
quick | Remove obvious AI cliches + buzzwords. Single pass, no scoring. | Fast social edits, internal docs |
standard | Full pattern scan (50+ detections) + human-ness score + change log | Any content going public |
deep | Full scan + replace with voice-profile patterns. Loads brand_context/voice-profile.md | Blog posts, landing pages, emails — anything that must sound like the brand |
Default: standard. When called by another skill as a post-processing step, use deep if voice-profile exists, standard if not.
Step 2: Load Context
If mode is deep, load brand_context/voice-profile.md. Extract:
- Preferred vocabulary (use these as replacements)
- Avoided words (flag these as AI tells even if not in pattern library)
- Linguistic habits (connectors, intensifiers, rhythm patterns)
- Samples for tone reference
Read context/learnings.md → ## tool-humanizer for known false positives or priority patterns.
Step 3: Score Original
Rate the input text 0-10 on the human-ness scale:
| Score | Meaning |
|---|
| 0-3 | Obviously AI — multiple cliches, robotic structure, hedging everywhere |
| 4-5 | AI-heavy — some human touches but needs major work |
| 6-7 | Mixed — could go either way, lacks distinctive voice |
| 8-9 | Human-like — natural voice, minimal AI patterns |
| 10 | Indistinguishable from a skilled human writer |
Scoring factors:
- AI pattern count per 500 words (fewer = better)
- Sentence length variance (higher variance = more human)
- Specificity ratio (concrete terms vs vague qualifiers)
- Structural variety (not every paragraph same shape)
Step 4: Apply Pattern Detection + Removal
Read references/pattern-library.md for the full detection list. Categories:
- AI cliches & openers — "In today's fast-paced world", "Let's dive in", "It's no secret"
- Hedging language — "It's important to note", "arguably", "one might argue"
- Corporate buzzwords — "leverage", "utilize", "facilitate", "optimize"
- Robotic structure — rhetorical Q+A, obsessive parallelism, always-three lists, "Here are the top X"
- Overused transitions — "Moreover", "Furthermore", "Additionally", "Nevertheless"
- Promotional inflation — "transformative", "game-changer", "unprecedented"
- Wikipedia AI tells — inflated symbolism, em dash overuse, rule of three, vague attributions, negative parallelisms, superficial -ing analyses, excessive conjunctive phrases
- Vocabulary tells — "delve", "tapestry", "multifaceted", "landscape", "nuanced", "foster", "realm"
Read references/replacement-guide.md for what to replace with.
Step 5: Enhance Human Markers
After removing AI patterns, add natural voice signals:
- Varied sentence rhythm — break up same-length sentences
- Contractions — "it's" not "it is" (unless formal context)
- Active voice — flip passive constructions
- Confident assertions — remove hedging unless genuinely uncertain
- Specific examples — flag vague references for the user to make specific
In deep mode, apply voice-profile patterns:
- Insert brand-preferred connectors and transitions
- Match sentence length patterns from samples
- Use brand vocabulary as replacements for generic terms
Step 6: Score Revised + Output
Score the revised text. Show the change summary:
ORIGINAL: 4.2/10
REVISED: 8.4/10
Changes:
[N] AI cliches removed
[N] buzzwords replaced
[N] hedging phrases cut
[N] structural patterns fixed
[N] voice markers added
Flags for review:
[paragraph/line] — [what needs manual attention]
If called standalone, present the cleaned text directly.
If called as a post-processing step by another skill, return the cleaned text silently (the calling skill handles output).
Step 7: Log Learnings
If the user gives feedback ("that was too aggressive", "keep the em dashes", "good catch on X"), log to context/learnings.md → ## tool-humanizer.
Pipeline Mode
When called by another skill (not standalone), this skill:
- Receives text as input
- Runs Steps 2-6 silently
- Returns cleaned text
- Only shows the score summary if the change was significant (delta > 2 points)
The calling skill is responsible for saving the final output.
Rules
Updated automatically when the user flags issues. Read before every run.
Self-Update
If the user flags an issue — too aggressive, missed a pattern, false positive — update the ## Rules section immediately with the correction and today's date. Also log to context/learnings.md under ## tool-humanizer.
Scoring Thresholds
| Score | Label | Action |
|---|
| 90-100 | Clean | No changes needed |
| 70-89 | Light | Fix flagged patterns only |
| 50-69 | Moderate | Rewrite flagged sentences |
| 0-49 | Heavy | Full rewrite recommended |