Individual skill
avoid-ai-writing
Audit and rewrite prose so it stops reading as machine-generated. Use this skill when asked to remove AI-isms, clean up AI writing, edit a draft for AI tells, audit a README, changelog, release note, PR description, or blog post for machine-sounding prose, or make text sound less like AI. Supports a detect-only mode, a rewrite mode, and an edit-in-place mode, with optional voice and context profiles.
plugins/avoid-ai-writing/skills/avoid-ai-writing/SKILL.md
Source commit 4bde3168b43c0655c4d00ea2726e631719908a6d
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- Matches the observed repository HEAD
- Yes
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- No
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- Observed behavior
- Not checked yet
- Last checked
- Nov 7, 2026
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Repository context
- Repository stars (not skill ratings)
- 42,324
- Repository last updated
- Nov 5, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- anthropic Repository topic
- agent-skills Repository topic
- agentic-ai Repository topic
- ai-agents Repository topic
- cursor Repository topic
- cursor-rules Repository topic
- mcp Repository topic
- multi-agent Repository topic
- opencode Repository topic
- claude-code Repository topic
- writing Derived category
- security Derived category
- docs Derived category
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SKILL.mdcore · 7,666 bytesSKILL.mdcore · 7,666 bytesSKILL.mdcore · 7,666 bytesSKILL.mdcore · 7,666 bytesSKILL.mdcore · 7,666 bytesreferences/pattern-catalog.mddoc · 17,313 bytesreferences/profiles.mddoc · 7,671 bytesreferences/word-tiers.mddoc · 11,710 bytes
Read excerpt
# Avoid AI Writing
Find the patterns that make text read as machine-generated, then fix them without sanding off the author's voice.
## What a flag proves
These patterns are more common in model output, and people produce them too, especially under deadline, in an unfamiliar genre, or in a second language. The evidence on machine detection cuts both ways. A Stanford audit found seven detectors flagged 61% of TOEFL essays by non-native English writers as AI-generated, against roughly 5% of essays by native writers (Liang et al., *Patterns*, 2023). A 2025 audit found open-source detection unsuitable for high-stakes use, with false-positive rates around 30% to 78% depending on the scenario, while the strongest commercial detector it tested approached zero error on medium and long passages (Jabarian and Imas, BFI Working Paper 2025-116). Adversarial paraphrasing still degrades the detectors it targets, averaging an 87.9% drop in true-positive rate at a 1% false-positive threshold, ranging from 64% to 99% by detector (arXiv:2506.07001).
Treat every flag here as a writing-quality signal. This skill classifies nothing, and no flag it raises should decide an academic-integrity, hiring, or attribution question.
## Modes
**rewrite** (default): flag the patterns, return a clean version with every editable AI-ism removed, summarize what changed.