How the Humanizer Agent Skill Rewrites AI‑Sounding Text: A Complete Technical Breakdown

Humanizer removes robotic "AI‑telling" patterns through a four‑stage pipeline that marks suspicious phrases, drafts a rewrite, validates the result, and produces final natural‑sounding prose—without adding or removing any facts.

The open‑source blader/humanizer repository provides a pure‑Markdown agent skill designed to strip artificiality from machine‑generated text. Unlike traditional text‑processing libraries, Humanizer contains no runtime code—its entire behavior lives in SKILL.md, making it portable across any agent platform that supports Markdown‑based skills.

How Humanizer Detects and Removes AI Patterns

The core innovation of Humanizer lies in its pattern‑driven detection system. According to SKILL.md, the skill maintains a curated list of 25 "tells" derived from Wikipedia's research into signs of AI writing. Each pattern specifies a watch phrase, the problem it causes, and before/after examples that guide the rewrite.

The Four‑Stage Processing Pipeline

Humanizer processes every input through these sequential steps:

1. Mark the tells — Scans input for all 25 patterns (e.g., "not‑X‑but‑Y" constructions, one‑line closers, forced triads, dash abuse, overused AI words). Strongest matches are prioritized.

2. Draft the rewrite — Generates a new version that may shorten dull passages, merge or split paragraphs, and restructure sentences. New facts are never introduced—only existing information is reshaped.

3. Check the draft — The draft is conceptually "read aloud" and re‑scanned against the pattern list. Remaining AI‑sounding fragments are removed, and factual integrity is verified.

4. Write the final version — Delivers natural‑sounding prose that retains the original information and voice.

This workflow is documented in the "How to work" section of SKILL.md【SKILL.md – How to work】.

Key AI‑Telling Patterns Humanizer Targets

The pattern list addresses recurring artifacts of large language model output. While the full 25 patterns reside in SKILL.md, representative categories include:

• Structural tells: Forced triads ("first, second, third"), predictable paragraph rhythms, one‑line closing statements
• Rhetorical tells: "Not X but Y" framing, unnecessary hedging, excessive signposting
• Stylistic tells: En‑dash and em‑dash abuse, overused AI vocabulary ("delve," "leverage," "tapestry")
• Pacing tells: Uniform sentence lengths, mechanical transitions, absence of natural variation

Each pattern includes concrete before/after examples that train the underlying agent on what to eliminate and how to reconstruct the thought.

Operating Modes and Usage Patterns

Humanizer adapts to three distinct workflows, as documented in README.md【README.md – Usage】:

Mode	Trigger	Output
Interactive	/humanizer command with pasted text	Draft → critique → final rewrite
File mode	Humanize the prose in [filepath]	Rewritten prose only; code, YAML, and links preserved
Embedded	API call from another tool	Final text only, no intermediate steps

File Mode Preserves Technical Content

When processing documents, Humanizer distinguishes prose from structured content. In docs/launch-post.md or similar files, the skill rewrites only natural‑language passages while leaving code blocks, front‑matter, URLs, and data structures intact.

Voice Matching for Consistent Tone

Humanizer supports adaptive voice calibration. As described in README.md【README.md – Match your voice】, users can supply a writing sample to align the rewrite with their established rhythm, word choice, punctuation habits, and dash usage.

Voice Matching Workflow

/humanizer

Here's a sample of my writing for voice matching:
[2–3 paragraphs demonstrating your style]

Now humanize this text:
[AI‑sounding content to rewrite]

The output mirrors the supplied sample's cadence rather than defaulting to generic "human‑like" prose.

Practical Implementation Examples

Basic Interactive Session

/humanizer

The rapid advancement of artificial intelligence technologies has 
fundamentally transformed numerous industries, not merely enhancing 
efficiency but redefining the very nature of work itself.

Result: Humanizer returns the draft rewrite, a bullet list of removed tells (e.g., "not‑X‑but‑Y construction," "abstract triad"), and the finalized version.

Embedded API Integration

curl -X POST https://api.agent.com/execute \
  -d '{"skill":"humanizer","input":"..."}'

When called programmatically, the skill returns only the final rewritten text—suitable for automated PR descriptions, commit messages, or documentation pipelines.

Architectural Characteristics

Aspect	Implementation
Runtime	None—pure Markdown prompt
Configuration	SKILL.md contains patterns and logic
Portability	Any agent loading Markdown skills
Extensibility	Pattern list editable in SKILL.md

The entire behavior is expressed through the Markdown specification in SKILL.md. This eliminates dependency management, version conflicts, or environment‑specific failures common to traditional software libraries.

Source File Reference

File	Purpose
SKILL.md	Core prompt with 25‑pattern list, four‑stage pipeline, and rewrite logic
README.md	Installation, usage modes, and voice‑matching instructions
AGENTS.md	Platform integration metadata for Claude, OpenAI, and other agents

Summary

• Humanizer operates as a pure‑Markdown skill with no executable code—behavior is defined entirely in SKILL.md.

• The four‑stage pipeline (mark tells → draft → check → finalize) systematically strips AI artifacts while preserving factual content.

• 25 detection patterns target structural, rhetorical, stylistic, and pacing tells common to machine‑generated text.

• Three operating modes (interactive, file, embedded) adapt the skill to manual editing, document processing, and automated workflows.

• Voice matching enables style‑consistent rewrites aligned to user‑provided writing samples.

Frequently Asked Questions

What makes Humanizer different from other AI text detectors?

Unlike classifiers that merely flag AI‑generated content, Humanizer actively rewrites the text to remove robotic patterns. It operates entirely through prompt engineering in SKILL.md rather than trained models or heuristics, making it inspectable and modifiable.

Can Humanizer change the meaning of my text?

No. The skill is explicitly constrained to never add new facts during rewriting. The "check the draft" stage verifies factual integrity before producing the final version. Only structure, rhythm, and word choice are modified.

How do I customize which patterns Humanizer targets?

Edit the pattern list in SKILL.md. Each pattern includes a watch phrase, problem description, and before/after examples. Adding, removing, or adjusting these entries changes the skill's detection and rewrite behavior across all modes.

Does Humanizer work with code or only prose?

Humanizer processes natural‑language prose only. In file mode, it automatically preserves code blocks, YAML front‑matter, links, and data structures—rewriting only the human‑readable text surrounding them.

{
  "mcpServers": {
    "instagit": {
      "command": "npx",
      "args": ["-y", "instagit@latest"]
    }
  }
}