SimpleEnglish: Agent skill: make LLMs write docs in ASD-STE100 Simplified Technical

by AminBlg · Agent Tool · ★ 3.8k

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

How to install SimpleEnglish

npx skills add AminBlg/SimpleEnglish

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 62/100

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. 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.

Quick Facts

Stars3,770
Forks144
LanguagePython
CategoryAgent Tool
LicenseMIT
Quality Score62/100
Open Issues4
Last Updated2026-10-05
Created2026-07-21
Platformspython
Est. Tokens~15k

About SimpleEnglish

✈️ your AI writes like a LinkedIn post. make it write like a Boeing manual. An agent skill that makes LLMs write plain English with the discipline of ASD-STE100 Simplified Technical English, the controlled language aerospace has used since 1983 so that a tired mechanic cannot misread an instruction. Layman-readable by default, STE-strict on request. <a href="https://trendshift.

Compatible Skills

These tools work well together with SimpleEnglish for enhanced workflows:

  • asd-ste100-skill — semantic(0.20)+complementary+same_lang+similar_pop+shared_platform (57%)
  • pivotnacci — semantic(0.20)+complementary+same_lang+similar_pop+shared_platform (57%)
  • mingli-master — semantic(0.16)+complementary+same_lang+similar_pop+shared_platform (56%)
  • seo-audit-skill — semantic(0.16)+complementary+same_lang+similar_pop+shared_platform (56%)
  • amazon-sorftime-research-MCP-skill — semantic(0.16)+complementary+same_lang+similar_pop+shared_platform (55%)

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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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