by conorbronsdon · Codex Skill · ★ 5.5k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
Featured in: Humanizer & Anti-Slop Skills
git clone https://github.com/conorbronsdon/avoid-ai-writing ~/.claude/skills/avoid-ai-writing
git clone https://github.com/conorbronsdon/avoid-ai-writing ~/.openclaw/skills/avoid-ai-writingTaken from the project's README on GitHub. Check the security audit before running it.
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
One of 23 tools we ran end to end on the same task for our Humanizer & Anti-Slop Skills page (2026-10-07).
Result: flagged 7 (0 about structure) · 2 min
| Stars | 5,462 |
| Forks | 473 |
| Language | JavaScript |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 70/100 |
| Open Issues | 17 |
| Last Updated | 2026-11-07 |
| Created | 2026-03-06 |
| Platforms | claude-code, codex, node |
| Est. Tokens | ~16k |
avoid-ai-writing A portable writing skill for Claude Code, OpenClaw, and any agentskills.io-compatible agent. Audits and rewrites content to remove AI writing patterns ("AI-isms"). Paste any text or run against a file, get back a clean version with every AI tell identified, fixed, and explained. A built-in second pass re-reads the rewrite to catch patterns that survived the first edit.
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Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: