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
vanillaflava vanillaflava
from GitHub Docs & Knowledge
  • 📁 assets/
  • 📁 references/
  • 📄 SKILL.md
wiki templates schema

wiki-config

Set up, validate, and reconfigure the llm-wiki skill suite. Use when the user says /wiki-config, asks to "set up my wiki", "configure wiki", "initialize wiki config", mentions "page structure problems", "header errors", "schema issues", "missing templates", "page templates", or when any wiki skill reports a missing or invalid config, schema, or templates folder. Owns the interactive configuration flow, schema management, and template management for the wiki system.

⬇0 ❤28 9 days ago · Uploaded Detail →
jdevalk jdevalk
from GitHub Tools & Productivity
  • 📄 AGENTS.md
  • 📄 README.md
  • 📄 SKILL.md
astro data seo

astro-seo

Audits and improves SEO for Astro sites. Use when the user asks to audit, set up, or improve SEO on an Astro site, or mentions head metadata, structured data, JSON-LD, sitemaps, IndexNow, Open Graph images, schema endpoints, NLWeb, hreflang, or search engine indexing in an Astro project. Produces drop-in code routed through `@jdevalk/astro-seo-graph` and chains into `metadata-check` for generated SEO strings. --- # Astro SEO Audits and improves the SEO setup of an Astro site against the full stack described in [Astro SEO: the definitive guide](https://joost.blog/astro-seo-complete-guide/). The skill covers nine areas — technical foundation, structured data, content, site structure, performance, sitemaps and indexing, agent discovery, redirects, and analytics — and produces drop-in code for anything missing or weak. The opinionated spine of this skill is [`@jdevalk/astro-seo-graph`](https://github.com/jdevalk/seo-graph). Most of the fixes route through it. If the project doesn't use it yet, installing it is the first recommendation. **Code recipes live in `AGENTS.md`** — read it when you need to implement a specific fix. This file has the workflow and audit checklist. ## Workflow 1. **Detect the project** — confirm this is an Astro site and understand its shape. 2. **Audit** — score nine categories and produce actionable findings. 3. **Improve** — generate or modify files to close the gaps. Recipes are in `AGENTS.md`. 4. **Metadata pass** — invoke `metadata-check` on every short string the skill generated (titles, descriptions, schema `description` fields, FAQ answers, frontmatter excerpts). 5. **Verify** — run the build, check validations pass, remind the user about non-file tasks (Search Console, Bing Webmaster Tools, IndexNow key verification). --- ## Phase 0: Detect the project

⬇0 ❤37 29 days ago · Uploaded Detail →
midspiral midspiral
from GitHub Data & AI
  • 📄 SKILL.md
dafny when verification

lemmafit-dafny

Dafny code patterns and reference for lemmafit apps. Use when writing or editing .dfy files, defining state machines (Model, Action, Inv, Init, Step), or when Dafny verification fails and you need to fix errors. Covers the AppCore module pattern and common mistakes.

⬇0 ❤37 1 month ago · Uploaded Detail →
pasky pasky
from GitHub Data & AI
  • 📄 SKILL.md
decisions past what

chronicle-read

Reconstruct high-level past events (decisions, commitments, timelines) from /chronicle chapters. Use for longer-term recall beyond what <context_summary> paragraphs cover — arc of past discussions, decisions made, what happened last week(s).

⬇0 ❤37 1 month ago · Uploaded Detail →
OSideMedia OSideMedia
from GitHub Content & Multimedia
  • 📁 .claude/
  • 📁 db/
  • 📁 docs/
  • 📄 .gitattributes
  • 📄 .gitignore
  • 📄 CHANGELOG.md
ai video higgsfield

higgsfield

Use this skill whenever the user asks anything about Higgsfield AI — writing or refining video/image prompts, choosing a model (Kling, Sora 2, Veo, Wan, Seedance, Minimax Hailuo, DoP, Soul, Nano Banana, Seedream, Flux, GPT Image, etc.), camera controls, named motion presets, Soul ID character consistency, Cinema Studio 2.5/3.0, Vibe Motion, troubleshooting failed generations, credit optimization, Photodump, or any mention of higgsfield.ai. Also trigger on generic "write me a video prompt" or "make me an AI video prompt" requests when Higgsfield is the user's configured platform.

⬇0 ❤37 1 month ago · Uploaded Detail →
regenrek regenrek
from GitHub Development & Coding
  • 📁 architecture-ownership/
  • 📁 codex-analysis/
  • 📁 codex-sandbox/
  • 📄 SKILL.md
frontend page landing

shadcn-vite-iconify-landing-page

Build, critique, and iterate high-converting marketing or product landing pages using React + Vite + TypeScript + Tailwind and shadcn/ui components, with all icons sourced from Iconify. Use when the user asks for a landing page, sales page, signup page, CRO improvements, above-the-fold vs below-the-fold structure, hero + CTA copy, section order, or wants production-ready shadcn + Vite code.

⬇0 ❤37 1 month ago · Uploaded Detail →
faugustdev faugustdev
from GitHub Data & AI
  • 📁 examples/
  • 📁 references/
  • 📁 scripts/
  • 📄 .gitignore
  • 📄 CONTRIBUTING.md
  • 📄 LICENSE
automation markdown context

gcc

Git Context Controller (GCC) v2 — Lean agent memory backed by real git. Stores hash + intent + optional decision notes instead of verbose markdown. Auto-bridges to aiyoucli vector memory when available. Dual mode: git-backed (lean index.yaml) or standalone (markdown fallback). Triggers on /gcc commands or natural language like 'commit this progress', 'branch to try an alternative', 'merge results', 'recover context'.

⬇0 ❤37 1 month ago · Uploaded Detail →
crafter-station crafter-station
from GitHub Tools & Productivity
  • 📁 references/
  • 📁 scripts/
  • 📄 README.md
  • 📄 SKILL.md
agents.md automation intent

intent-layer

Set up hierarchical Intent Layer (AGENTS.md files) for codebases. Use when initializing a new project, adding context infrastructure to an existing repo, user asks to set up AGENTS.md, add intent layer, make agents understand the codebase, or scaffolding AI-friendly project documentation. --- # Intent Layer Hierarchical AGENTS.md infrastructure so agents navigate codebases like senior engineers. ## Core Principle **Only ONE root context file.** CLAUDE.md and AGENTS.md should NOT coexist at project root. Child AGENTS.md in subdirectories are encouraged for complex subsystems. ## Workflow ``` 1. Detect state scripts/detect_state.sh /path/to/project → Returns: none | partial | complete 2. Route none/partial → Initial setup (steps 3-5) complete → Maintenance (step 6) 3. Measure [gate - show table first] scripts/analyze_structure.sh /path/to/project scripts/estimate_tokens.sh /path/to/each/source/dir 4. Decide No root file → Ask: CLAUDE.md or AGENTS.md? Has root file → Add Intent Layer section + child nodes if needed 5. Execute Use references/templates.md for structure Use references/node-examples.md for real-world patterns

⬇0 ❤37 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