Hermes continues to self-evolve into a super body!

Humanizer removes AI traces, Obsidian identity layer, Taste style memory, AutoShorts short video factory, Creative Brain interview brain… Programmers across the internet have turned Hermes into the next-gen Agent: a real human writer + private eternal knowledge + style memory master + viral short video factory + creative soul engine.

humanizer(https://github.com/blader/humanizer…)

29 patterns automatically remove AI traces, and can be calibrated to your personal writing style. “It finally writes real human text that doesn’t look like AI” — confirmed!

obsidian-skills(https://github.com/kepano/obsidian-skills…)

Turn your Obsidian vault into an Agent identity layer in 30 seconds. Personal notes directly become a “self-awareness” context — a privacy lover’s dream!

taste-skill(https://github.com/Leonxlnx/taste-skill…)

The Agent interviews you first, automatically extracts taste/voice/references, and generates a structured style file. From now on, your creations will always carry your soul!

skill-autoshorts(https://github.com/mutonby/skill-autoshorts…)

Automatically clip long videos → highlight clips daily → approve on phone + weekly engagement self-evolution. The Agent edits TikTok/Reels on its own.

creative-brain(https://github.com/prathamcreates/creative-brain…)

The Agent interviews you to extract taste, generates a “self-awareness” file, and creations always carry personal style. Creative brainstorms take off instantly!

blader/humanizer

Source: https://github.com/blader/humanizer

Humanizer

A skill for Claude Code and OpenCode that removes signs of AI-generated writing from text, making it sound more natural and human.

Installation

Claude Code

Clone directly into Claude Code’s skills directory:

mkdir -p ~/.claude/skills
git clone https://github.com/blader/humanizer.git ~/.claude/skills/humanizer

Or copy the skill file manually if you already have this repo cloned:

mkdir -p ~/.claude/skills/humanizer
cp SKILL.md ~/.claude/skills/humanizer/

OpenCode

Clone directly into OpenCode’s skills directory:

mkdir -p ~/.config/opencode/skills
git clone https://github.com/blader/humanizer.git ~/.config/opencode/skills/humanizer

Or copy the skill file manually if you already have this repo cloned:

mkdir -p ~/.config/opencode/skills/humanizer
cp SKILL.md ~/.config/opencode/skills/humanizer/

Note: OpenCode also scans ~/.claude/skills/ for compatibility, so a single clone into ~/.claude/skills/humanizer/ works for both tools.

Usage

Claude Code

/humanizer

[paste your text here]

OpenCode

/humanizer

[paste your text here]

Or ask the model to humanize text directly in either tool:

Please humanize this text: [your text]

Voice Calibration

To match your personal writing style, provide a sample of your own writing:

/humanizer

Here's a sample of my writing for voice matching:
[paste 2-3 paragraphs of your own writing]

Now humanize this text:
[paste AI text to humanize]

The skill will analyze your sentence rhythm, word choices, and quirks, then apply them to the rewrite instead of producing generic “clean” output.

Overview

Based on Wikipedia’s “Signs of AI writing” (https://en.wikipedia.org/wiki/Wikipedia:Signs_of_AI_writing) guide, maintained by WikiProject AI Cleanup. This comprehensive guide comes from observations of thousands of instances of AI-generated text.

The skill also includes a final “obviously AI generated” audit pass and a second rewrite, to catch lingering AI-isms in the first draft.

Key Insight from Wikipedia

“LLMs use statistical algorithms to guess what should come next. The result tends toward the most statistically likely result that applies to the widest variety of cases.”

29 Patterns Detected (with Before/After Examples)

Content Patterns

Language Patterns

Style Patterns

Communication Patterns

Filler and Hedging

Full Example

Before (AI-sounding):

Great question! Here is an essay on this topic. I hope this helps!

AI-assisted coding serves as an enduring testament to the transformative potential of large language models, marking a pivotal moment in the evolution of software development. In today’s rapidly evolving technological landscape, these groundbreaking tools—nestled at the intersection of research and practice—are reshaping how engineers ideate, iterate, and deliver, underscoring their vital role in modern workflows.

At its core, the value proposition is clear: streamlining processes, enhancing collaboration, and fostering alignment. It’s not just about autocomplete; it’s about unlocking creativity at scale, ensuring that organizations can remain agile while delivering seamless, intuitive, and powerful experiences to users. The tool serves as a catalyst. The assistant functions as a partner. The system stands as a foundation for innovation.

Industry observers have noted that adoption has accelerated from hobbyist experiments to enterprise-wide rollouts, from solo developers to cross-functional teams. The technology has been featured in The New York Times, Wired, and The Verge. Additionally, the ability to generate documentation, tests, and refactors showcases how AI can contribute to better outcomes, highlighting the intricate interplay between automation and human judgment.

• 💡 Speed: Code generation is significantly faster, reducing friction and empowering developers.
• 🚀 Quality: Output quality has been enhanced through improved training, contributing to higher standards.
• ✅ Adoption: Usage continues to grow, reflecting broader industry trends.

While specific details are limited based on available information, it could potentially be argued that these tools might have some positive effect. Despite challenges typical of emerging technologies—including hallucinations, bias, and accountability—the ecosystem continues to thrive. In order to fully realize this potential, teams must align with best practices.

In conclusion, the future looks bright. Exciting times lie ahead as we continue this journey toward excellence. Let me know if you’d like me to expand on any section!

After (Humanized):

AI coding assistants can speed up the boring parts of the job. They’re great at boilerplate: config files and the little glue code you don’t want to write. They can also help you sketch a test, but you still have to read it.

The dangerous part is how confident the suggestions look. I’ve accepted code that compiled and passed lint, then discovered later it missed the point because I stopped paying attention.

If you treat it like autocomplete and review every line, it’s useful. If you use it to avoid thinking, it will help you ship bugs faster.

The only real backstop is tests. Without them, you’re mostly judging vibes.

References

• Wikipedia: Signs of AI writing (https://en.wikipedia.org/wiki/Wikipedia:Signs_of_AI_writing) - Primary source
• WikiProject AI Cleanup (https://en.wikipedia.org/wiki/Wikipedia:WikiProject_AI_Cleanup) - Maintaining organization

Version History

• 2.5.1 - Added a passive-voice / subjectless-fragment rule, raising the total to 29 patterns
• 2.5.0 - Added patterns for persuasive framing, signposting, and fragmented headers; expanded negative parallelisms to cover tailing negations; tightened wording around em dash overuse; fixed frontmatter wording to use “filler phrases”
• 2.4.0 - Added voice calibration: match the user’s personal writing style from samples
• 2.3.0 - Added pattern #25: hyphenated word pair overuse
• 2.2.0 - Added a final “obviously AI generated” audit + second-pass rewrite prompts
• 2.1.1 - Fixed pattern #18 example (curly quotes vs straight quotes)
• 2.1.0 - Added before/after examples for all 24 patterns
• 2.0.0 - Complete rewrite based on raw Wikipedia article content
• 1.0.0 - Initial release

License

MIT

GitTrend (@GitTrend0x): Hermes is a versatile all-in-one app!

One-click full-stack deployment, Docker sandbox, Nix reproducible installation, professional weather plugin, persistent execution plans… Programmers across the internet have turned Hermes into the next-gen Agent: zero-pain deployment tool + isolated sandbox + geeky clean environment + personal weather station + persistence expert:

1️⃣ evey-setup