sepia
Helps teams detect and remediate AI-generated text in documentation, content, and code comments—critical for maintaining authenticity, compliance, and user t…
De-AI writing skill for any Agent Skills-compatible agent (77+ via the Skills CLI), with native plugins for Claude Code, Codex, Grok Build, and Antigravity. Narrative-architecture repair for fiction, venue-matched rules for professional prose. Based on StoryScope (arXiv:2604.03136).
- Ask Claude to remove AI-generated patterns from a draft novel chapter and restore authentic narrative voice.
- Generate professional email or report prose that matches your company's communication style and tone guidelines.
- Find and fix inconsistencies in character voice or narrative perspective across multiple fiction document sections.
Helps teams detect and remediate AI-generated text in documentation, content, and code comments—critical for maintaining authenticity, compliance, and user trust in enterprise communications.
Content teams and compliance officers managing mixed human-AI writing workflows requiring de-AI detection across documents and professional prose.
https://github.com/Nanako0129/sepia
By Nanako0129
How to Get It
claude plugins install Nanako0129/sepia
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:
Remove AI-generated patterns from a draft novel chapter and restore authentic narrative voice
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): 2,171 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.
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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): 2,171 GitHub stars; contributors unknown; last commit 0d ago; license MIT.