An open-source set of go-to-market skills for solo technical founders — positioning, first users, launch and pricing, sequenced into a roadmap your agent works with you.
Humanizer
Summary
Editing skill that strips the tells of AI-generated prose — filler transitions, hedging, inflated vocabulary and rhetorical padding — while preserving the author's meaning.
Features
- Removes formulaic transitions, hedging and inflated vocabulary
- Catalogue of specific AI-writing patterns with the concrete edit for each
- Preserves argument, structure and factual content while changing register
- Works on documentation, release notes, memos and marketing copy
- Runs on the open Agent Skills standard in Claude Code, Codex and Cursor
- Plain skill directory install with no runtime dependencies
Install This Skill
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Skill Content
Description
Humanizer is an editing pass for text that reads as machine-written. It targets the recognisable habits of LLM prose: formulaic transitions, symmetrical tricolons, hedged qualifiers, needlessly elevated vocabulary, the "it's not X, it's Y" construction, empty summarising paragraphs and the general tendency to use forty words where fifteen would do.
The distinction that matters is that it is a rewriting skill, not a paraphraser. It works from a detailed catalogue of specific patterns and the concrete edit each one calls for, so the output keeps the original argument, structure and factual content while losing the cadence that makes readers stop trusting a document. That makes it useful on anything drafted or part-drafted with a model — documentation, release notes, internal memos, marketing copy, commit messages — where the substance is right but the register is off.
It is one of the most widely adopted single-purpose agent skills published, and it runs anywhere the Agent Skills standard is supported, including Claude Code, Codex and Cursor. Installation is a skill directory drop with no runtime dependencies. MIT licensed.
A note on scope: this is a prose-quality tool aimed at readability and voice. It is not a way to misrepresent authorship, and it does not defeat disclosure obligations where those apply.
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