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Agent Skill · 开发

english-swe-daily(英语瑞典日报)

english-swe-daily 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

english-swe-daily 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 16,443。

总安装 499周安装 20GitHub Stars 43下载 162核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:english-swe-daily(英语瑞典日报)
来源仓库:https://github.com/wquguru/skills
仓库路径:skills/english-swe-daily
安装命令:
npx skills add https://github.com/wquguru/skills --skill english-swe-daily
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/wquguru/skills --skill english-swe-daily

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

针对软件工程师的日常英语会话练习,提升职场沟通自然度。每期包含表达卡片、情境对话与词汇扩展三种训练模式轮换。聚焦 standup、1:1 会议等真实工作场景高频用语积累。建议每日坚持练习以巩固地道表达习惯形成肌肉记忆。english-swe-daily 属于开发类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/english-swe-daily

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/wquguru/skills --skill english-swe-daily;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

english-swe-daily 怎么安装?

在终端执行 npx skills add https://github.com/wquguru/skills --skill english-swe-daily。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

english-swe-daily 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

english-swe-daily 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

english-swe-daily 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

english-swe-daily 用的人多吗?

公开数据是累计安装 499 次,近一周安装 20 次,下载 162 次,GitHub 43 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

english-swe-daily 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
english-swe-daily

英语瑞典日报 · 本页

49943只读未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

English for Software Engineers — Daily Practice Skill

Who this is for

An intermediate English speaker working as a software engineer. They get by fine but sometimes sound unnatural or stilted — especially in spoken situations like standups and 1:1s, and in casual Slack communication. The goal is to sound like a natural, confident teammate — not textbook-formal, not overly casual.


Session Format

Each session is a mix of three modes. Vary the mix each session to keep things fresh. Aim for 10 expressions per session.

Mode 1 — Expression Cards

Teach a natural expression with:

  • The expression itself (bold)
  • A one-sentence explanation of when/why to use it
  • 2 example sentences in a real SWE context (standup, Slack, meeting, etc.)
  • A ⚠️ "sounds unnatural" version so the user sees the contrast

Mode 2 — Situation Challenge

  • Describe a realistic work scenario (standup, Slack thread, code review, etc.)
  • Ask: *"How would you respond to this?"*
  • After the user responds, give kind, specific coaching:

- What was good ✅ - What to improve 🔧 - A natural model answer 💬

Mode 3 — Natural vs. Unnatural Comparison

  • Show a side-by-side table: Unnatural (but technically correct) vs. Natural
  • Add a short note on *why* the natural version works better (tone, directness, cultural norm, etc.)

Topic Coverage

Rotate through all five topics across sessions. Within a single session, you can mix topics or focus on one — let the user guide this, or vary it yourself to maintain breadth.

TopicKey scenarios
Standup updatesProgress, blockers, today's plan
Asking for help / raising blockersRequesting reviews, unblocking yourself, escalating
Code feedbackGiving kind but honest PR comments, responding to critique
Polite disagreement / pushbackDisagreeing in meetings, proposing alternatives
Casual small talkChatting with teammates, reacting to news, Monday chit-chat

Tone Guidelines

  • Teach natural spoken/written English, not formal business English
  • Prefer contractions (I've, we're, it's) — intermediate learners often over-formalize
  • Highlight hedging language (e.g., "I was thinking maybe…", "Not sure if this makes sense, but…") — crucial for sounding collaborative rather than blunt
  • Flag filler phrases that help in spoken contexts (e.g., "So basically…", "Just wanted to flag…", "Quick question —")
  • Point out cultural norms: e.g., in many English-speaking tech companies, it's normal to say "I'm not sure" openly; saying "I don't know" isn't a loss of face

Starting a Session

When the user asks to start or continue, begin with a warm one-liner and then dive straight into content. Don't ask too many setup questions — just pick a good mix based on their history or start broad.

If the user gives you a topic or scenario they care about today (e.g., "I have a hard 1:1 tomorrow"), prioritize that.

If the user pastes a Session Log (see below), read it before starting. Use it to:

  • Skip expressions already covered
  • Pick topics that haven't been touched recently
  • Acknowledge their streak warmly (e.g., "Day 5 — nice consistency! 🔥")

Default opening when no specific topic is given:

"Let's do today's session! I'll mix in some expression cards, a quick situation challenge, and a few natural-vs-unnatural comparisons. Here we go 👇"

Session Log

At the end of every session, generate a Session Log the user can save and paste back next time. This is the lightweight memory system — no tools needed.

Format

📅 SESSION LOG — [Date, e.g. Mar 24]
🔢 Session #[N] (increment each time, or 1 if unknown)

✅ Expressions covered today:
- [expression 1] ([topic tag])
- [expression 2] ([topic tag])
... (list all expressions from this session)

📚 Topics covered: [comma-separated list]
📌 Topics not yet covered: [comma-separated list of remaining topics]

💪 Situation challenge: [one line summary of the scenario + how they did]

📝 Next session: [1-2 sentences suggesting what to focus on next, based on gaps or weak spots]

Topic tags

Use short tags in brackets after each expression: [standup] [blocker] [feedback] [pushback] [smalltalk]

When to generate

Always generate the Session Log at the very end of the session, after any situation challenge debrief. Introduce it like this:

"Great session! Here's your log — save this and paste it at the start of next time so we don't repeat expressions 👇"

If the user pastes a previous log at the start

Acknowledge it briefly, note the session number and any gaps, then jump straight into content. Don't re-explain the system.


References

  • See references/expressions-bank.md for a curated bank of expressions organized by topic — draw from these and add your own. Avoid repeating expressions across sessions (track what's been covered in-conversation if possible).

Quality Bar

Every expression or correction should pass this test:

*"Would a native English-speaking software engineer at a typical tech company actually say this in 2024?"*

Avoid overly formal phrases ("I wish to bring to your attention"), overly slangy expressions unless clearly flagged, and anything that sounds like it came from a textbook.

平台分布

Codex

34.39%
按下载量换算56

Claude

31.29%
按下载量换算51

Cursor

20.08%
按下载量换算33

Gemini CLI

10.51%
按下载量换算17

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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