humanize

name	humanize
description	Identify and remove AI writing patterns to make text sound natural and human-written. Use when humanizing commit messages, PR descriptions, review comments, docs, changelogs, or release notes. Also for de-slopping text that sounds robotic, has AI vibes, or reads like ChatGPT output.
argument-hint	[file-path] [--score-only] [--dry-run]
allowed-tools	AskUserQuestion, Edit, Read, Task, Write
user-invocable	true
context	fork
agent	general-purpose

Humanize

Remove AI writing patterns from text and replace them with natural, human-sounding alternatives. Uses two complementary sources:

• Detection: Wikipedia's "Signs of AI writing" guide (WikiProject AI Cleanup) - what to remove
• Composition: Strunk & White's "The Elements of Style" (1918) - how to write the replacement well

Scope

Designed for prose text: commit messages, PR descriptions, docs, changelogs, blog posts, review comments. Not for code, structured data (JSON/YAML), or text where AI patterns are intentional.

Arguments

Parse from $ARGUMENTS:

Flag	Default	Purpose
(positional)	—	File path to humanize. Prompt user if omitted
--score-only	off	Report detected patterns without rewriting
--dry-run	off	Output to chat instead of editing in-place

Default: edit the file in-place, fixing all detected patterns regardless of severity (including faint ones). Use --dry-run to preview changes without modifying the file.

Pattern categories

The skill detects 24 AI writing patterns organized into five categories:

1. Content patterns (1-6): significance inflation, notability claims, superficial -ing analyses, promotional language, vague attributions, formulaic challenges sections
2. Language and grammar (7-12): AI vocabulary words, copula avoidance, negative parallelisms, rule-of-three, synonym cycling, false ranges
3. Style (13-18): em dash overuse, boldface overuse, inline-header lists, title case headings, emoji decoration, curly quotes
4. Communication artifacts (19-21): chatbot correspondence phrases, knowledge-cutoff disclaimers, sycophantic tone
5. Filler and hedging (22-24): filler phrases, excessive hedging, generic positive conclusions

Read references/patterns.md for full pattern descriptions with words-to-watch lists and before/after examples (used in Phase 2 scan and Phase 5 verification).

Read references/elements-of-style.md for composition principles used during the Phase 4 rewrite (active voice, concrete language, omitting needless words, sentence variety, emphasis placement).

Workflow

Phase 1: Input discovery

1. Parse $ARGUMENTS for file path and flags.
2. If no file path provided, use AskUserQuestion to get the target file or text.
3. Read the target file. If the input is raw text (not a file path), store it for processing.
4. Determine the text's intended tone and audience from context (technical docs, blog post, PR description, commit message, etc.).

Phase 2: Pattern scan (spawned agent)

Spawn a general-purpose agent to isolate the 280+ line pattern catalog from the main context. The agent reads the full catalog, scans the input, and returns only compact results.

1. Use TaskCreate to spawn the agent with this prompt:

   You are a pattern-detection agent. Your job: scan the provided text against
   every pattern in the catalog and return ONLY the hits.
   
   CATALOG: Read the file at {absolute path to references/patterns.md}
   
   TEXT TO SCAN:
   <input>
   {paste the full input text here}
   </input>
   
   INSTRUCTIONS (ultrathink — systematically check every pattern, do not skip any):
   1. Read the catalog file in full.
   2. Check the input text against all 24 AI writing patterns.
   3. For each match, record: pattern ID, pattern name, quoted offending text,
      severity (faint | clear | glaring).
   4. Return ONLY a fenced code block with one JSON array of hit objects:
      [{"id": "P01", "name": "...", "quote": "...", "severity": "..."}]
   5. If no patterns detected, return an empty array: []
   6. Do NOT rewrite anything. Do NOT add commentary outside the code block.
   

   Set the agent description to "humanize: pattern scan".

2. Poll the agent with TaskGet until it completes.

3. Parse the JSON array from the agent's output. This is the hit list - store it for Phase 4.

4. If --score-only, skip to Phase 6 (Report) using the hit list directly.

Phase 3: Voice assessment

Read references/voice-guide.md in full before starting this phase.

1. Assess the text for signs of soulless writing:
   • Uniform sentence length and structure
   • No opinions, perspective, or personality
   • No acknowledgment of uncertainty or mixed feelings
   • Reads like a press release or generic Wikipedia article
2. Note sections that need voice injection, not just pattern removal.

Phase 4: Rewrite

Read references/elements-of-style.md in full before starting this phase.

This phase requires ultrathink. Reason through competing constraints (pattern removal, voice injection, composition principles, meaning preservation) before rewriting each section.

Use the hit list from the Phase 2 agent to fix every detected pattern regardless of severity. Even faint tells get fixed. Apply fixes in this order:

1. Strip communication artifacts: chatbot phrases, disclaimers, sycophantic openings.
2. Fix content patterns: deflate significance claims, replace vague attributions with specifics, remove formulaic sections.
3. Fix language patterns: replace AI vocabulary, restore simple copulas (is/are/has), remove negative parallelisms and forced triads.
4. Fix style patterns: replace em dashes with commas or periods where appropriate, remove mechanical boldface and emoji, use sentence case in headings, straighten curly quotes.
5. Cut filler: remove filler phrases, reduce hedging, replace generic conclusions with specifics.
6. Add voice: vary sentence rhythm, inject appropriate perspective, let some imperfection in. Match tone and register to the text's audience.
7. Apply composition principles from references/elements-of-style.md:
   • Convert passive constructions to active voice where the actor is known.
   • Replace negative hedging ("was not very often on time") with positive assertions ("usually came late").
   • Swap abstract language for concrete specifics ("a period of unfavorable weather" becomes "it rained every day for a week").
   • Cut needless words: "the fact that", "who is/which was" padding, "in order to", wordy "he is a man who" constructions.
   • Break monotonous sentence patterns - if three consecutive sentences use the same structure, recast at least one.
   • Move the most important word or phrase to the end of each sentence.
   • Keep one topic per paragraph. End paragraphs with the strongest point, not a trailing detail.

Preserve the original meaning. Never add information the source text does not contain because invented facts undermine trust even when the prose sounds better. Keep technical accuracy intact - style improvements that sacrifice correctness make the text worse, not better.

Phase 5: Verification

Re-read the hit list from Phase 2 and the composition principles from references/elements-of-style.md before checking. This anchors verification against the same criteria used during the rewrite.

Check the rewritten text:

• No AI patterns from references/patterns.md remain.
• Core meaning is preserved (no information lost or invented).
• Sentence structure varies naturally (not uniform length or identical clause patterns).
• Active voice used where the actor is known. No stacked passives.
• Statements are positive and definite, not hedged with negatives.
• Language is concrete and specific, not abstract and general.
• No needless words: no "the fact that", no "who is/which was" padding, no filler expressions.
• Emphatic words land at the end of sentences, not buried in the middle.
• Each paragraph covers one topic and ends with its strongest point.
• Tone matches the original audience and intent.
• Text sounds natural when read aloud.

If any check fails, revise the affected sections and re-verify.

Error handling

• If the file path does not exist or is unreadable, report the error and stop.
• If the pattern scan agent returns an empty array, skip Phase 4 rewrite and report "no patterns detected."
• If the text is under 50 characters, warn the user that meaningful pattern detection needs more content.

Phase 6: Report

Output a pattern report:

Column	Content
#	Sequential number
Pattern	Pattern name from the catalog
Instance	Quoted offending text from the original
Fix	What replaced it (or "removed" if stripped)

Include a summary line: patterns detected count, category count, and overall severity (Minor, Moderate, Heavy).

If --score-only, stop here.

Phase 7: Output

1. If --dry-run: output the rewritten text to chat.
2. Otherwise: apply edits to the file in-place. Use the Edit tool for targeted fixes. Use the Write tool to replace the file when the majority of its content changed.
3. Append the pattern report after the output.

Example

**Input:** > Additionally, this groundbreaking framework serves as a testament to the team's commitment to fostering innovation, showcasing how modern tools can enhance developer productivity in today's rapidly evolving landscape.

Output:

The framework speeds up common tasks like scaffolding and test generation. The team built it after noticing developers spent 40% of sprint time on boilerplate.

Patterns fixed: AI vocabulary (Additionally, groundbreaking, enhance), significance inflation (testament, commitment to fostering), copula avoidance (serves as), superficial -ing (showcasing), promotional language (rapidly evolving landscape)

Score-only mode (no rewriting):

/humanize docs/architecture.md --score-only

Dry-run preview:

/humanize CHANGELOG.md --dry-run