humanize_skill

Overview

This skill transforms AI-generated text into natural, human-like writing that aims to bypass common AI detectors such as GPTZero, Turnitin, and Originality.ai. It uses a credit system based on word count and offers adjustable intensity levels to balance fidelity and detection avoidance. Results include before/after detection scores and remaining credits. The default intensity is medium for balanced rewrites.

How this skill works

When invoked, the skill parses the input text and an optional --intensity flag (light, medium, aggressive). It sends a humanization request to the HumanizerAI service, receives the rewritten text and score changes, then presents a summary with words processed and credits remaining. The skill also handles common errors like insufficient credits, invalid API keys, and rate limits and provides guidance to resolve them.

When to use it

• You have AI-origin content that must read as natural human writing.
• You need lower AI-detection scores for submission to detectors or similarity checks.
• You want control over rewrite strength via light, medium, or aggressive modes.
• You need a quick before/after comparison including detection scores and credit usage.
• You need to audit credit consumption on a per-request basis.

Best practices

• Start with default medium intensity; escalate to aggressive only when detectors flag the text repeatedly.
• Provide focused input (single piece of content per call) to minimize credit waste and improve quality.
• Check the before/after scores and tweak intensity rather than re-running multiple times.
• Keep an eye on credits: 1 word consumes 1 credit, detection checks are free.
• Use light intensity to preserve author voice and aggressive for strict detector environments.

Example use cases

• Humanize an essay draft before submission to a university similarity check.
• Rewrite marketing copy to sound more conversational and evade automated patterning.
• Adjust AI-written technical documentation to match a team’s tone while lowering detector signals.
• Prepare content for publications that flag high AI-generation scores.
• Batch-process student assignments with credit-aware transformations and score reporting.