Daily Featured Skills Count
4,689 4,727 4,753 4,784 4,818 4,870 4,879
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♾️ Free & Open Source 🛡️ Secure & Worry-Free

Import Skills

Composite Most Downloads Most Likes Most Comments Newest
JimmyLv JimmyLv
from GitHub Content & Multimedia
  • 📁 references/
  • 📁 scripts/
  • 📁 workflows/
  • 📄 SKILL.md
video summarize videos

bibi

AI video & audio summarizer. Summarize YouTube videos, Bilibili videos, podcasts, TikTok, Twitter/X, Xiaohongshu, and any online video or audio. Use when the user wants to summarize a video, extract transcripts/subtitles, get chapter-by-chapter summaries, or understand video content quickly.

⬇0 ❤38 1 month ago · Uploaded Detail →
opendatalab opendatalab
from GitHub Tools & Productivity
  • 📄 _meta.json
  • 📄 CONTRIBUTING.md
  • 📄 SKILL.md
extraction automation mineru

mineru

MinerU document extraction CLI that converts PDFs, images, and web pages into Markdown, HTML, LaTeX, or DOCX via the MinerU API. Supports token-free flash extraction for quick start, precision extraction with table/formula recognition, web crawling, batch processing, and piped workflows.

⬇0 ❤38 1 month ago · Uploaded Detail →
mapbox mapbox
from GitHub Docs & Knowledge
  • 📁 evals/
  • 📁 references/
  • 📄 AGENTS.md
  • 📄 SKILL.md
data official mapbox

mapbox-android-patterns

Official integration patterns for Mapbox Maps SDK on Android. Covers installation, adding markers, user location, custom data, styles, camera control, and featureset interactions. Based on official Mapbox documentation.

⬇0 ❤38 1 month ago · Uploaded Detail →
petrowsky petrowsky
from GitHub Development & Coding
  • 📄 SKILL.md
data source developer

data-migrate

Move records from an external source (CSV, JSON, SQL dump, or API response) into a live FileMaker solution via OData. Reads the source data, maps source columns to FM fields with type coercion, gets developer approval on the mapping, then executes the migration with error tracking. Use when the developer asks to "migrate data", "import records", "move data into FileMaker", "load CSV", or "import JSON".

⬇0 ❤38 1 month ago · Uploaded Detail →
thu-nmrc thu-nmrc
from GitHub Tools & Productivity
  • 📁 assets/
  • 📁 references/
  • 📁 scripts/
  • 📄 CONTRIBUTING.md
  • 📄 LICENSE
  • 📄 README.md
automation production-grade automatically

harness-24h

A production-grade framework for long-running, autonomous agents based on Harness Engineering principles. Features three-layer self-healing memory, circuit breaker protection, KAIROS dream-mode consolidation, and multi-agent coordination. When a user describes a task idea, Agent automatically initializes the workspace, fills all template files, sets up the cron schedule, and begins execution immediately.

⬇0 ❤38 1 month ago · Uploaded Detail →
yohey-w yohey-w
from GitHub Data & AI
  • 📄 SKILL.md
greenfield buildable fragments

codd-dev

Assemble generated sprint fragments into a complete, buildable project. This is the final step in the greenfield pipeline after `codd implement`.

⬇0 ❤38 1 month ago · Uploaded Detail →
lucas-flatwhite lucas-flatwhite
from GitHub Tools & Productivity
  • 📁 autoplan/
  • 📁 benchmark/
  • 📁 browse/
  • 📄 .gitignore
  • 📄 AGENTS.md
  • 📄 ARCHITECTURE.md
dogfooding headless interact

gstack

Fast headless browser for QA testing and site dogfooding. Navigate pages, interact with

⬇0 ❤38 1 month ago · Uploaded Detail →
RuochenLyu RuochenLyu
from GitHub Data & AI
  • 📁 references/
  • 📄 SKILL.md
health data cross-metric

apple-health-analyst

Analyze Apple Health export ZIP. Run local prepare to generate structured insights, then produce a professional health report based on cross-metric analysis and historical context.

⬇0 ❤36 23 days ago · Uploaded Detail →
willpowerju-lgtm willpowerju-lgtm
from GitHub Data & AI
  • 📁 references/
  • 📄 SKILL.md
notebooklm data model

3-statements-ultra

从零构建机构级三表模型（IS/BS/CF）— 完整公式联动、季度/半年/年频自适应、IFRS/US GAAP/中国准则。 触发词：三表模型、financial model、3-statement、建模、从零建模、收入预测。 ❌ 填写已有模板请用 financial-analysis:3-statements --- # 3-Statement Model — IPO / Equity Research Quality (v4.8 · Public Edition) --- ## 🚀 Quick Start — New Users **This skill builds:** A complete institutional-grade 3-statement financial model (IS / BS / CF) in Excel, with full formula linkage, zero hardcoded forecast cells, and 9-step QC validation. **Prerequisites — install before starting:** ```bash pip install openpyxl yfinance pandas pip install notebooklm # optional — only needed if you have a NotebookLM notebook ``` **How to trigger:** Just say `"建个三表模型"` / `"build a 3-statement model for [Company]"` and the skill guides you step by step. **What to prepare:** - Company ticker (e.g. `BABA`, `0700.HK`, `600519.SS`) - A data source — see recommendations below - ~1–2 hours across 5 sessions (each session is independent — pause and resume anytime) **⚠️ Data Source Guide — Read Before Starting** | Option | Setup | Token Cost | Recommended? | |--------|-------|-----------|--------------| | **NotebookLM notebook** (annual reports / prospectus pre-loaded) | One-time OAuth auth setup | Very low — NLM handles the PDF; Claude only receives answers | ✅ Best path | | **Excel upload** (historical IS/BS/CF already structured) + short PDF excerpts | None | Low | ✅ Good | | **Direct PDF upload** (full annual report, prospectus) | None | 🔴 Very high — a single A-share annual report can be 200+ pages | ⚠️ Pro users: avoid | | **Web only** (Sina / Yahoo Finance fallback) | None | Low | ✅ Fallback | **Strongly recommended for new users: set up NotebookLM first.** The one-time auth flow takes ~5 minutes and saves significant token consumption for every future model: ```bash pip install notebooklm # Run once interactively — browser will open for Google OAuth python3 -c " import asyncio from notebooklm import NotebookLMClient async def auth(): async with await NotebookLMClient.

⬇0 ❤33 15 days 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