1,026 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
buluslan buluslan
from GitHub Development & Coding
  • 📁 assets/
  • 📁 docs/
  • 📁 examples/
  • 📄 .env.example
  • 📄 .gitignore
  • 📄 generate_from_tagged.py
gemini cli voc

review-analyzer-skill

AI驱动的电商评论深度分析工具,支持CLI本地模式和Gemini增强模式。提供22维度智能标签、黑金奢华可视化看板、四位一体VOC系统(6套3D头像)。 触发词使用场景: - 用户需要分析电商产品评论(Amazon/eBay/AliExpress等) - 用户想要生成产品洞察报告和机会点分析 - 用户需要从评论中提取用户画像和VOC - 用户需要创建专业的可视化分析看板 - 用户提到"电商评论分析"、"评论分析"、"竞品分析"、"用户洞察"、"VOC分析"等关键词 核心能力: - 双模洞察系统: CLI本地模式(使用内置模型) + Gemini增强模式(API付费) - 22维度智能标签系统: 人群/场景/功能/质量/服务/体验/市场/情感 - 黑金奢华可视化看板: 董事会高管汇报级别HTML报告 - 四位一体VOC系统: 6套3D头像,立体化用户画像 - 三位一体输出: CSV标签数据 + Markdown洞察报告 + HTML可视化看板 强制交互约束(绝对级): ❗ 无论任何情况,当用户触发评论分析时,AI Agent 必须先通过 AskUserQuestion 工具依次向用户收集以下三个参数,再执行分析命令: 1. 分析数量(多少条评论) 2. AI引擎模式(CLI/混动/Gemini) 3. 报告署名 严禁自行填充默认值或猜测用户意图。这是本 Skill 的最高优先级规则。 如果用户明确表示"都用默认值"或"你决定",才可以使用默认值(100条/模式1/AI Assistant)。 渐进式披露逻辑: 1. 首次使用时,引导用户克隆主仓库并安装依赖 2. 提供清晰的快速开始命令和参数说明 3. 遇到问题时,引导用户查看主仓库文档 4. 强调双模洞察系统的成本差异和使用场景 技术要求: - Python 3.9+ - Claude Code CLI(CLI本地模式必需) - Gemini API Key(Gemini增强模式可选)

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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