turkce-humanizer
Enables teams producing Turkish-language content to mask AI generation artifacts and maintain authenticity in communications, reducing detection risk and imp…
Türkçe metinlerden yapay zekâ yazım imzalarını temizleyen Claude skill'i. YZ üretimi Türkçe'yi doğal, insan-sesli Türkçe'ye dönüştürür. | A Claude skill that removes AI writing signatures from Turkish text.
- Generate natural-sounding Turkish content by removing AI writing patterns from model outputs
- Transform formal Turkish text into conversational, human-like language for customer communications
- Clean up Turkish documents to hide AI generation before sharing with stakeholders
Enables teams producing Turkish-language content to mask AI generation artifacts and maintain authenticity in communications, reducing detection risk and improving user trust in documentation or customer-facing materials.
Content teams and localization managers working with Turkish-language outputs requiring natural-sounding, human-authored voice.
https://github.com/bushrabeg/turkce-humanizer
By bushrabeg
How to Get It
claude plugins install bushrabeg/turkce-humanizer
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
After installing, paste this into Claude:
Help me generate natural-sounding Turkish content by removing AI writing patterns from model outputs
Trust Signals Auto-scanned
Community Pulse New
No community discussions found yet. This doesn't mean the tool isn't good — it may be new or serve a niche use case.
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 56 GitHub stars; contributors unknown; last commit 0d ago; license MIT.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
How to evaluate tools before deploying →
Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.
Evaluation
Scored from trust signals (evidence-eval-v1): 56 GitHub stars; contributors unknown; last commit 0d ago; license MIT.