qmreader-ios: 专注中文长文、翻译与乔木改写的原生 iOS 阅读器 | Native iOS reader for Chinese long-form reading, translation

by joeseesun · AI Tool · ★ 76

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

How to install qmreader-ios

git clone https://github.com/joeseesun/qmreader-ios.git

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 66/100

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.

chineseiosopen-sourceqiaomureader-apprss-readerswiftuitranslation

Quick Facts

Stars76
Forks7
LanguageSwift
CategoryAI Tool
LicenseMIT
Quality Score66/100
Last Updated2026-09-07
Created2026-08-23
Est. Tokens~16k

About qmreader-ios

QMReader iOS 中文 | English 专注中文长文、翻译与乔木改写的原生 SwiftUI 阅读器。 A native SwiftUI reader for Chinese long-form reading, translation, and Qiaomu rewrites. 已验证: ;Xcode 26.2 模拟器构建、Apple Development 真机安装与 App Store Distribution Archive/IPA 导出通过。App Store 提交正在进行中。 这是什么 QMReader iOS 是 QMReader 的轻量原生客户端。它把 RSS 文章、中文翻译和“乔木改写”放进一个安静、快速、可离线回看的阅读界面,重点解决三件事: 先看到可读的中文改写,而不是先闪出英文原文。 用原生导航、缓存、下拉刷新和频道历史缩短等待。...

Compatible Skills

These tools work well together with qmreader-ios for enhanced workflows:

  • gemini-rss-app — semantic(0.33)+complementary+rare_topics+similar_pop (56%)
  • Pepper — semantic(0.25)+complementary+same_lang+similar_pop (54%)

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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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