Humanize – two LLM-agnostic skills to rewrite and detect AI text
The article discusses two new LLM-agnostic skills designed for rewriting and detecting AI-generated text. These skills, named 'humanize' and 'ai-check', can be installed across various LLM agents with a single command. They utilize a rule-based approach to enhance text humanization and conduct forensic analysis of AI-generated signals.
- ▪The 'humanize' skill rewrites text to sound more human by applying nine humanization levers.
- ▪The 'ai-check' skill analyzes text for AI-generation signals and provides a confidence score along with evidence.
- ▪Both skills are static and do not require runtime dependencies, making them easy to install across multiple agents.
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| Original publisher | GitHub |
| Canonical URL | https://github.com/harshaneel/humanize |
| Publication time | Tue, 26 May 2026 18:29:48 +0000 |
| Retrieval time | 2026-05-26T18:37:53.470Z |
| Last seen | 2026-05-26T18:37:53.470Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | Trfiv8tTtfH7 |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
humanize LLM-agnostic skills for static AI text humanization and detection. Grounded in 50+ peer-reviewed sources through April 2026. Works in any LLM agent: Claude Code, Codex CLI, ChatGPT, Gemini, Cursor, Aider, OpenCode, Continue, Copilot. The install paths differ; the skill content is identical. Contents Get started What's inside — the two skills, at a glance Installation — one command for Claude Code, Codex CLI, ChatGPT desktop, or any agent Usage — how to invoke each skill Benchmark — 25 inputs, two independent scorers Why the skills work Background — the gap between AI and human writing The detection literature — perplexity, burstiness, stylometry, discourse Detection methodology taxonomy — zero-shot, classifier, watermarking, hybrid Adversarial findings — what evasion techniques…
Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.