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JWhiteUXJWhiteUX/ClaudeSkills-Library/humanizer/SKILL.md

humanizer

Skill4 starsChanged 7 months agoNo licenceView on GitHub

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, passive voice, negative parallelisms, and filler phrases. Scores each rewrite against a 0-100 rubric and loops until it clears threshold; matches a user-supplied voice sample via an extracted style profile when one is given.

188 other projects use a version of this, 103 of them edited.

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Used with

Projects with it also use economy-mode, personal-voice and 10 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • Microsoft AzureSkill

    economy-mode

    Shifts Layer 3 model selection to cost-optimized alternatives when economy mode is active.

    Also in 4 projects that use this

  • petermuirurithuoSkill

    personal-voice

    Captures the user's personality, communication style, and values. Use this skill whenever responding to the user, drafting anything on their behalf (emails, CVs, messages, opinions, explanations), or whenever tone, word choice, or how an opinion is delivered matters. Apply it by default for any prompt, not only when the user explicitly asks for "my style" or "my voice.

    Also in 3 projects that use this

  • Microsoft AzureSkill

    architectural-proposals

    How to write comprehensive architectural proposals that drive alignment before code is written

    Also in 3 projects that use this

  • +9 more from Azure

The file

Show its rules and text

We split this skill into the rules it gives an agent

22 rules. 0 are common, 21 are distinctive, and 1 is very specific to this project.

  • 0

    Common

    Most of the 175 edited versions we read keep these.

  • 21

    Distinctive

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.

“Common” is measured: kept by at least 6 in 10 of the 175 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

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What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

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