16,022 Open Skills

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✅ Keyword search & category filters
✅ Discussions & community interaction
✅ Version updates & multi-metric ranking
✅ Open SKILL.md standard

Import Skills

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brandonwise brandonwise
from GitHub Data & AI
text ai-generated detection

humanizer

Humanize AI-generated text by detecting and removing patterns typical of LLM output. Rewrites text to sound natural, specific, and human. Uses 28 pattern detectors, 560+ AI vocabulary terms across 3 tiers, and statistical analysis (burstiness, type-token ratio, readability) for comprehensive detection. Use when asked to humanize text, de-AI writing, make content sound more natural/human, review writing for AI patterns, score text for AI detection, or improve AI-generated drafts. Covers content, language, style, communication, and filler categories.

⬇0 ❤22 9 days ago · Uploaded Detail →
shyuan shyuan
from GitHub Content & Multimedia
text when ai-generated

writing-humanizer

Use when editing or reviewing text to remove AI-generated patterns and make writing more natural and human. Use when the user provides text and asks to remove AI tone, humanize, rewrite naturally, or polish. Also use when text is clearly AI-generated Chinese content. 適用於使用者要求「去 AI 味」、「人性化」、「改寫得更自然」、「潤稿」、「改得像人寫的」時。

⬇0 ❤8 2 days ago · Uploaded Detail →
Deepractice Deepractice
from GitHub Development & Coding
frontend ai-generated design

lucid-ui

Professional UI design system that replaces generic AI aesthetics (purple gradients, neon colors) with intentional, distinctive design. Use this skill whenever generating frontend UI, web pages, landing pages, dashboards, or any visual interface. Provides concrete color palettes, typography rules, spacing systems, and anti-patterns to ensure AI-generated UIs look professionally designed rather than AI-generated.

⬇0 ❤8 9 days ago · Uploaded Detail →
LupinLin1 LupinLin1
from GitHub Content & Multimedia
ai-generated images jimeng

jimeng-api

Generate images and videos using the Jimeng API (即梦AI) at jimeng.modelhub.cc. Use this skill when users request AI-generated images, artwork, illustrations, or AI-generated videos from the Jimeng service. Supports text-to-image, image-to-image, text-to-video, image-to-video (first frame), first+last frame, and omni_reference video generation (with mixed image/video/audio materials).

⬇0 ❤6 7 days ago · Uploaded Detail →
talent-factory talent-factory
from GitHub Docs & Knowledge
text comprehensive ai-generated

humanizer

Removes indicators of AI-generated text. Use this skill when editing or reviewing text to make it sound more natural and human. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and corrects patterns such as: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em-dash overuse, rule of three, AI vocabulary, negative parallelisms, and excessive subjunctive phrases.

⬇0 ❤3 6 days ago · Uploaded Detail →
yazelin yazelin
from GitHub Content & Multimedia
cat ai-generated ai

catime

Fetch and send AI-generated hourly cat images. Every hour a unique cat artwork is born via Google Gemini. Use when user asks for a cat picture, wants to browse the cat gallery, or requests the latest AI-generated cat image to be sent to them.

⬇0 ❤2 3 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