2,138 Open Skills

Free to get · One-click to use

✅ AI semantic search & keyword search
✅ Discussions & community interaction
✅ Version updates & multi-metric ranking
✅ Open SKILL.md standard

Import Skills

Composite Most Downloads Most Likes Most Comments Newest
eze-is eze-is
from GitHub Databases & Storage
  • 📁 references/
  • 📁 scripts/
  • 📄 .workspace_path
  • 📄 SKILL.md
workspace data published_at

daily-news

每日资讯日报生成器。三阶段工作流：获取元数据、生成摘要、输出日报。 触发场景：每日新闻、资讯日报、信息监控、新闻聚合、daily news、生成日报。 也用于添加新信源（自动分析网页并生成 method 文件）。 --- # Daily News 三阶段工作流：**获取元数据** → **生成摘要** → **输出日报** ## 工作目录 首次运行询问工作目录路径（如 `~/daily-news`），后续记住。 ``` <workspace>/ ├── profile.yaml # 用户画像（关于我、关注什么） ├── settings.yaml # 日报设置（语言、格式偏好） ├── methods/ # 信源获取方法 ├── data/news.db # SQLite 数据库 └── output/YYYY-MM-DD.md # 日报输出 ``` 初始化： ```bash mkdir -p <workspace>/methods <workspace>/data <workspace>/output cp references/examples/settings.example.yaml <workspace>/settings.yaml cp references/examples/profile.example.yaml <workspace>/profile.yaml python3 scripts/db.py init --db <workspace>/data/news.db ``` 初始化完成后： 1. 将工作目录写入用户的 `~/.claude/CLAUDE.md`，追加一行： ``` - daily-news skill 的项目目录在：<workspace> ``` 这样后续新会话无需再询问目录位置。 2. 询问用户是否需要调整画像。 --- ## 阶段 0：选择抓取日期范围（新增） 在执行抓取前，询问用户日期范围，从源头减少非必要工作量。 ### 日期范围选项 ``` 请选择抓取时间范围： 1. 今天（默认） → published_at >= 今天 2. 昨天 → published_at >= 昨天 3. 最近3天 → published_at >= 3天前 4. 最近7天 → published_at >= 7天前 5. 从上次抓取至今（增量） → published_at >= last_fetched_date 6. 自定义日期范围 → 输入开始日期 ``` ### 增量抓取逻辑 **每个信源独立追踪抓取日期**： ```yaml # methods/twitter-karpathy.yaml

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Skill File Structure Sample (Reference)

skill-sample/
├─ SKILL.md              ⭐ Required: skill entry doc (purpose / usage / examples / deps)
├─ manifest.sample.json  ⭐ Recommended: machine-readable metadata (index / validation / autofill)
├─ LICENSE.sample        ⭐ Recommended: license & scope (open source / restriction / commercial)
├─ scripts/
│  └─ example-run.py     ✅ Runnable example script for quick verification
├─ assets/
│  ├─ example-formatting-guide.md  🧩 Output conventions: layout / structure / style
│  └─ example-template.tex         🧩 Templates: quickly generate standardized output
└─ references/           🧩 Knowledge base: methods / guides / best practices
   ├─ example-ref-structure.md     🧩 Structure reference
   ├─ example-ref-analysis.md      🧩 Analysis reference
   └─ example-ref-visuals.md       🧩 Visual reference

More Agent Skills specs Anthropic docs: https://agentskills.io/home

SKILL.md Requirements

├─ ⭐ Required: YAML Frontmatter (must be at top)
│  ├─ ⭐ name                 : unique skill name, follow naming convention
│  └─ ⭐ description          : include trigger keywords for matching
│
├─ ✅ Optional: Frontmatter extension fields
│  ├─ ✅ license              : license identifier
│  ├─ ✅ compatibility        : runtime constraints when needed
│  ├─ ✅ metadata             : key-value fields (author/version/source_url...)
│  └─ 🧩 allowed-tools        : tool whitelist (experimental)
│
└─ ✅ Recommended: Markdown body (progressive disclosure)
   ├─ ✅ Overview / Purpose
   ├─ ✅ When to use
   ├─ ✅ Step-by-step
   ├─ ✅ Inputs / Outputs
   ├─ ✅ Examples
   ├─ 🧩 Files & References
   ├─ 🧩 Edge cases
   ├─ 🧩 Troubleshooting
   └─ 🧩 Safety notes

Why SkillWink?

Skill files are scattered across GitHub and communities, difficult to search, and hard to evaluate. SkillWink organizes open-source skills into a searchable, filterable library you can directly download and use.

We provide AI semantic + keyword search, version updates, multi-metric ranking (downloads / likes / comments / updates), and open SKILL.md standards. You can also discuss usage and improvements on skill detail pages.

AI Semantic Search Keyword Search Version Updates Multi-Metric Ranking Open Standard Discussion

Quick Start:

Import/download skills (.zip/.skill), then place locally:

~/.claude/skills/ (Claude Code)

~/.codex/skills/ (Codex CLI)

One SKILL.md can be reused across tools.

FAQ

Everything you need to know: what skills are, how they work, how to find/import them, and how to contribute.

1. What are Agent Skills?

A skill is a reusable capability package, usually including SKILL.md (purpose/IO/how-to) and optional scripts/templates/examples.

Think of it as a plugin playbook + resource bundle for AI assistants/toolchains.

2. How do Skills work?

Skills use progressive disclosure: load brief metadata first, load full docs only when needed, then execute by guidance.

This keeps agents lightweight while preserving enough context for complex tasks.

3. How can I quickly find the right skill?

Use these three together:

  • Semantic search: describe your goal in natural language.
  • Multi-filtering: category/tag/author/language/license.
  • Sort by downloads/likes/comments/updated to find higher-quality skills.

4. Which import methods are supported?

  • Upload archive: .zip / .skill (recommended)
  • Upload skills folder
  • Import from GitHub repository

Note: file size for all methods should be within 10MB.

5. How to use in Claude / Codex?

Typical paths (may vary by local setup):

  • Claude Code：~/.claude/skills/
  • Codex CLI：~/.codex/skills/

One SKILL.md can usually be reused across tools.

6. Can one skill be shared across tools?

Yes. Most skills are standardized docs + assets, so they can be reused where format is supported.

Example: retrieval + writing + automation scripts as one workflow.

7. Are these skills safe to use?

Some skills come from public GitHub repositories and some are uploaded by SkillWink creators. Always review code before installing and own your security decisions.

8. Why does it not work after import?

Most common reasons:

  • Wrong folder path or nested one level too deep
  • Invalid/incomplete SKILL.md fields or format
  • Dependencies missing (Python/Node/CLI)
  • Tool has not reloaded skills yet

9. Does SkillWink include duplicates/low-quality skills?

We try to avoid that. Use ranking + comments to surface better skills:

  • Duplicate skills: compare differences (speed/stability/focus)
  • Low quality skills: regularly cleaned up