code-humanizer: humanizer, but for code — an agent skill that removes AI-generated code slop

by LeonardNJU · Agent Tool · ★ 71

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install code-humanizer

npx skills add LeonardNJU/code-humanizer
git clone https://github.com/LeonardNJU/code-humanizer ~/.claude/skills/code-humanizer

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 67/100

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.

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.

agent-skillsai-slopclaudeclaude-codecode-qualityrefactoringskilltechnical-debt

Quick Facts

Stars71
Forks2
CategoryAgent Tool
LicenseMIT
Quality Score67/100
Last Updated2026-07-26
Created2026-07-15
Platformsclaude-code
Est. Tokens~13k

About code-humanizer

code-humanizer English | 中文 humanizer, but for code. An agent skill that removes signs of AI-generated code from a repository, and can guard new changes against the same patterns — the structural slop coding agents leave behind when they optimize for "tests pass" instead of "codebase stays healthy." Install One command, picks your agents for you (Claude Code, Codex, Cursor, Cline, Gemini,...

Compatible Skills

These tools work well together with code-humanizer for enhanced workflows:

  • agent-skills — semantic(0.42)+complementary+rare_topics+similar_pop+shared_platform (64%)

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How this security grade is produced

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:

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