How Humanizer Removes Chatbot-Specific Phrases: Greetings, Offers, and Disclaimers

Humanizer strips chatbot-specific phrases by applying dedicated patterns 20 and 21 in SKILL.md to detect and remove conversational filler like "I hope this helps" and knowledge-limit disclaimers such as "as of my last update," rewriting the text to read as natural human prose.

The blader/humanizer repository provides an open-source skill that transforms AI-generated text into authentic human prose. When processing content from chatbots or large language models, the tool specifically targets conversational scaffolding and uncertainty markers that signal artificial origin. Understanding how Humanizer handles chatbot-specific phrases ensures you can produce clean, standalone content free of robotic greetings and speculative disclaimers.

How Humanizer Detects Chatbot Patterns

Humanizer identifies conversational artifacts through two specific patterns defined in SKILL.md.

Pattern 20: Chatbot Text and Conversational Filler

Located at lines 236-244 in SKILL.md, this pattern scans for typical chatbot closing phrases and offers. The skill flags segments containing phrases like "I hope this helps", "Let me know if you need anything else", or "Would you like me to expand on that?" Once detected, Humanizer removes the entire conversational segment and rewrites surrounding text so the factual content stands alone without artificial hooks.

Pattern 21: Knowledge-Limit Disclaimers

Defined at lines 245-252 in SKILL.md, this pattern catches phrases exposing model limitations or uncertainty. It targets temporal markers like "as of [date]", hedging language such as "based on available information", and speculative constructions like "it is believed that" or "it appears to have been". The skill strips these disclaimers entirely, either removing unsupported statements or rephrasing them as definitive observations about source availability.

The Four-Step Rewrite Process

When Humanizer processes text containing these markers, it executes a systematic transformation:

1. Detection: The skill scans input against the "words to watch" list compiled from patterns 20 and 21.
2. Marking: Identified segments are flagged as AI patterns requiring removal.
3. Rewriting: Surrounding paragraphs are reconstructed to flow naturally without conversational transitions or uncertainty qualifiers.
4. Verification: The system validates that no facts were added or lost during the transformation, ensuring factual integrity while removing artificial phrasing.

Practical Code Examples

The following examples demonstrate how Humanizer transforms chatbot-style input into clean prose.

Removing Greetings and Offers

**Input (chatbot-style)**
Here is an overview of the French Revolution. I hope this helps! Let me know if you'd like me to expand on any section.

**Humanizer Output**
The French Revolution began in 1789 when financial crisis and food shortages led to widespread unrest.

In this transformation, Pattern 20 identifies the conversational bookends ("I hope this helps" and "Let me know") and removes them entirely, while reconstructing the opening sentence to deliver factual information directly.

Stripping Knowledge-Limit Disclaimers

**Input (knowledge-limit disclaimer)**
While specific details about the company's founding are not extensively documented, it appears to have been established sometime in the 1990s.

**Humanizer Output**
The company's founding date is not documented in the available sources.

Here Pattern 21 eliminates the speculative hedge ("it appears to have been established sometime") and replaces it with a definitive statement about documentation gaps, removing the AI's uncertainty while preserving factual accuracy.

Source File Architecture

Humanizer's chatbot phrase handling operates through three key files in the repository:

• SKILL.md: Contains the core skill definition with all 35 detection patterns, including the chatbot-specific implementations at lines 236-252 for patterns 20 and 21.
• README.md: Provides overview documentation and installation instructions for running the humanization skill.
• AGENTS.md: Defines compatibility guidelines for agents working with the skill patterns to ensure consistent behavior.

These files implement the transformation logic that converts AI conversational markup into standalone human prose.

Summary

• Humanizer uses Pattern 20 in SKILL.md to detect and remove chatbot greetings, offers, and closings like "I hope this helps."
• Pattern 21 targets knowledge-limit disclaimers including temporal markers ("as of") and speculative hedging ("it appears").
• The rewrite process follows four stages: detection, marking, rewriting, and verification to ensure factual integrity.
• Located at lines 236-252 of SKILL.md, these patterns automatically transform conversational AI output into direct, factual prose.

Frequently Asked Questions

How does Humanizer identify chatbot-specific phrases?

Humanizer references specific "words to watch" defined in Pattern 20 (chatbot text) and Pattern 21 (knowledge-limit disclaimers) within SKILL.md. The skill scans input text for exact and partial matches of conversational phrases like "Let me know" or "as of my knowledge cutoff," flagging them for removal during the rewrite process.

What happens to information contained within knowledge-limit disclaimers?

Rather than preserving speculative language, Humanizer either removes unsupported claims entirely or rephrases them as definitive statements about documentation gaps. For example, "it appears to have been established in the 1990s" becomes "The company's founding date is not documented," eliminating AI uncertainty while maintaining factual accuracy.

Can Humanizer handle multiple chatbot patterns in the same text?

Yes. The skill processes all 35 patterns simultaneously during the detection phase, marking every instance of chatbot-specific phrasing before executing a comprehensive rewrite. This ensures texts containing both conversational fillers and knowledge disclaimers receive complete transformation in a single pass.

Where are the chatbot detection rules defined in the source code?

The specific regex patterns and keyword lists for chatbot phrase detection reside in SKILL.md at lines 236-244 (Pattern 20) and 245-252 (Pattern 21). The README.md and AGENTS.md files provide implementation context and agent compatibility guidelines.

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