ai-humanizer

Humanize AI-generated text by detecting and removing patterns typical of LLM output. Rewrites text to sound natural, specific, and human. Uses 24 pattern det...

This skill appears to be a local text humanizer/analyzer and the code in the bundle matches the described functionality, but there are a few things to check before installing or running it: - Packaging mismatch: the skill is labeled 'instruction-only' and lists no required binaries, yet the repository includes a Node.js CLI (package.json) and scripts that require node >= 18. Confirm whether the runtime will provide Node or whether the SKILL.md will be accompanied by the code at runtime. If you expect to run the included CLI, ensure you have Node 18+ installed. - Review the remaining source files (src/*) for any network activity or unexpected behaviors before executing on sensitive systems. The sampled files show no obvious external endpoints, but a full review is prudent. - When using the tool, be cautious with the file flag (-f): the CLI can read any file path you pass. Don’t pass sensitive system paths unless you intend to analyze them. - Verify the author/repository (package.json points to a GitHub URL) if provenance matters to you. If you need stronger assurance, run the tests locally (npm test) in a sandboxed environment before giving the skill access to real data. Given the mismatch between 'instruction-only' metadata and included Node.js code, treat this as suspicious until the author clarifies intended installation/runtime semantics or until you run the code in a controlled environment.

Type: OpenClaw Skill Name: peng-ai-humanizer Version: 2.1.0 The 'peng-ai-humanizer' bundle is a legitimate text analysis tool designed to detect and rewrite AI-generated content. The code implements a comprehensive scoring engine based on 24 linguistic patterns and statistical metrics (burstiness, type-token ratio, and Flesch-Kincaid readability) across files like src/analyzer.js and src/stats.js. Analysis of the logic and instructions in SKILL.md confirms that the tool operates entirely locally with zero external dependencies, no network access, and no dangerous execution sinks (like eval or child_process). The instructions provided for the AI agent are strictly stylistic, aimed at improving writing quality rather than subverting security or exfiltrating data.