Daily Featured Skills Count
4,689 4,727 4,753 4,784 4,818 4,870 4,879
04/28 04/29 04/30 05/01 05/02 05/03 05/04
♾️ Free & Open Source 🛡️ Secure & Worry-Free

Import Skills

Composite Most Downloads Most Likes Most Comments Newest
wzj177 wzj177
from GitHub Content & Multimedia
  • 📁 assets/
  • 📁 references/
  • 📁 scripts/
  • 📄 .gitignore
  • 📄 LICENSE
  • 📄 README.md
scripts output_dir python

ai-tryon

AI 虚拟试穿 Agent。用户提供服装信息（图片或文字描述均可）， Agent 全程引导完成：服装图预处理 → AI 生成模特 → 虚拟试穿合成 → 生成展示视频。 支持阿里云百炼试衣 API、豆包 Seedream 生图、豆包 Seedance 生视频。 当用户提到"试穿"、"试衣"、"穿上效果"、"模特上身"、"虚拟试衣"、 "看看穿上什么样"、"帮我生成穿衣效果"、"virtual try-on"、"上身图"、 "换装"、"我想看穿上的效果"时，必须立即触发此 Agent。 --- # AI 虚拟试穿 Agent ## 职责 引导用户完成虚拟试穿全流程，输出试穿效果图和展示视频。 不涉及上架、文案、定价。有上架需求告知使用 shopify-quick-listing。 --- ## 配置说明（告知用户时必须按此说明） **.env 文件的唯一标准位置是 `scripts/` 目录：** ``` ~/.claude/skills/ai-tryon/scripts/.env ← 正确位置 ~/.claude/skills/ai-tryon/.env ← 错误，不要放这里 ``` 告知用户配置的标准话术： > 请在 Skill 的 scripts 目录下创建 .env 文件： > ```bash > cp ~/.claude/skills/ai-tryon/scripts/.env.example \ > ~/.claude/skills/ai-tryon/scripts/.env > # 然后编辑填入 Key > ``` 不要让用户在 `ai-tryon/` 根目录或其他位置创建 .env。 --- ## 输出目录约束（最高优先级规则） **所有脚本调用都必须传 `--output-dir`，绝对禁止省略。** 输出目录的唯一真实来源是 `.env` 中的 `TRYON_OUTPUT_DIR` 环境变量： ```bash # .env 示例 TRYON_OUTPUT_DIR=/Users/xxx/Desktop/tryon_output ``` ### 对话开始时锁定 Session（必须在首次调用任何脚本前执行） **每次对话开始时，立即运行以下命令锁定本次任务目录，整个对话全程复用此 `OUTPUT_DIR`：** ```bash # 一行命令：获取（或创建）当前 session 目录，同时确保目录存在 OUTPUT_DIR=$(python scripts/output_manager.py --get-session) echo "本次任务目录：$OUTPUT_DIR" ``` - **24 小时内**再次运行同一命令，返回同一个 `task_YYYYMMDD_HHMMSS` 目录（文件不会覆盖） - 用户明确说「开始新任务」/「重新来」时，改用： ```bash OUTPUT_DIR=$(python scripts/output_manager.py --new-session) echo "新任务目录：$OUTPUT_DIR" ``` 然后每次调用脚本**必须传入同一个 `$OUTPUT_DIR`**： ```bash python scripts/image_gen_tryon.py --desc "..." --output-dir "$OUTPUT_DIR" python scripts/tryon_runner.py --garment g.jpg --output-dir "$OUTPUT_DIR" python scripts/video_gen.py --image img.jpg --output "$OUTPUT_DIR" ``` ### 为什么必须这样做 - 不传 `--output-dir` 时脚本会 fallback 到 `TRYON_OUTPUT_DIR` 环境变量或当前终端 pwd 下的 `tryon_output/` - **但 Agent 子进程的 pwd 不可控**，可能导致文件散落到意外位置 - 多轮对话后 Agent 容易遗忘，显式传参是唯一可靠保证 ### 输出文件名控制（可选） `image_gen_tryon.py` 支持 `--output-filename`，生成后会将第一个结果复制为指定文件名： ```bash python scripts/image_gen_tryon.py --desc "..." --output-dir "$OUTPUT_DIR" \ --output-filename model_ruyan_custom.jpg ``` ### 目录结构 每次对话/试穿任务自动创建独立的 session 子目录（以日期

⬇0 ❤17 1 month ago · Uploaded Detail →
booklib-ai booklib-ai
from GitHub Development & Coding
  • 📄 skill.md
python booklib data

booklib-skills

BookLib — curated skills from canonical programming books. Covers Kotlin, Python, Java, TypeScript, Rust, architecture, DDD, data-intensive systems, UI design, and more. Install individual skills via npx skillsadd booklib-ai/booklib/<name>.

⬇0 ❤17 1 month ago · Uploaded Detail →
co-r-e co-r-e
from GitHub Content & Multimedia
  • 📁 references/
  • 📄 SKILL.md
deck design structured

deck-designer

Interactive deck design consultant that guides users through structured Q&A to plan a new DexCode slide deck before building it. Gathers purpose, audience, content outline, and design preferences through conversation, then outputs a structured brief document and deck.config.ts parameters. Use when user says "デッキを設計", "deck design", "プレゼンの企画", "壁打ち", "アウトラインを考えて", "新しいデッキの相談", "plan a deck", "help me design a presentation", "brainstorm deck", or "スライドの構成を考えて".

⬇0 ❤17 1 month ago · Uploaded Detail →
0xDarkMatter 0xDarkMatter
from GitHub Testing & Security
  • 📁 assets/
  • 📁 references/
  • 📁 scripts/
  • 📄 SKILL.md
api design graphql

api-design-ops

API design patterns for REST, gRPC, and GraphQL. Use for: api design, REST, gRPC, GraphQL, protobuf, schema design, api versioning, pagination, rate limiting, error format, OpenAPI, API authentication, JWT, OAuth2, API gateway, webhook, idempotency.

⬇0 ❤17 1 month ago · Uploaded Detail →
wjllance wjllance
from GitHub Data & AI
  • 📁 openclaw/
  • 📁 references/
  • 📄 _meta.json
  • 📄 package.json
  • 📄 README.md
data trading real-time

standx-cli

Crypto trading CLI for StandX exchange v0.7.0. Use when users need to: (1) Query crypto market data (prices, order books, klines, funding rates), (2) Manage trading orders (create, cancel, view), (3) Check account balances, positions, and trade history, (4) Stream real-time market data via WebSocket, (5) Manage leverage and margin settings, (6) Monitor real-time dashboard, (7) View portfolio summary. Supports BTC, ETH, SOL, XRP and other trading pairs.

⬇0 ❤17 1 month ago · Uploaded Detail →
1596941391qq 1596941391qq
from GitHub Docs & Knowledge
  • 📁 .claude/
  • 📁 resources/
  • 📁 rules/
  • 📄 .gitignore
  • 📄 forum_database.json
  • 📄 install.bat
blackhatworld greyhatmafia browser-use

Edge Knowledge

AI驱动的边缘知识挖掘系统。针对用户需求，从高价值论坛（Reddit、BlackHatWorld、GreyHatMafia 等）智能推荐 + browser-use 深度爬取 + 视觉识别 + 分析边缘技巧、骚人、资源，并输出单一结构化 Markdown 报告。

⬇0 ❤17 1 month ago · Uploaded Detail →
PostHog PostHog
from GitHub Research & Analysis
  • 📄 SKILL.md
experiment behavior patterns

analyzing-experiment-session-replays

Analyze session replay patterns across experiment variants to understand user behavior differences. Use when the user wants to see how users interact with different experiment variants, identify usability issues, compare behavior patterns between control and test groups, or get qualitative insights to complement quantitative experiment results.

⬇0 ❤17 1 month ago · Uploaded Detail →
RafaelGorski RafaelGorski
from GitHub Business & Operations
  • 📄 SKILL.md
principles business identification

business-context

Establish structured business context and project principles before problem discovery. Use as Step 0 of Problem-Based SRS to capture project identity, business principles, stakeholders, domain boundaries, and success criteria that feed into Customer Problems identification.

⬇0 ❤17 1 month ago · Uploaded Detail →

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 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.

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