Daily Featured Skills Count
3,626 3,840 3,909 3,920 3,927 3,966 4,007
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♾️ Free & Open Source 🛡️ Secure & Worry-Free

Import Skills

tanweai tanweai
from GitHub Ops & Delivery
  • 📄 SKILL.md

pua-en

Put your AI on a Performance Improvement Plan. Forces exhaustive problem-solving with Western big-tech performance culture rhetoric and structured debugging. Trigger when: (1) task failed 2+ times or stuck tweaking same approach; (2) about to say 'I cannot', suggest manual work, or blame environment without verifying; (3) being passive—not searching, not reading source, just waiting; (4) user frustration: 'try harder', 'stop giving up', 'figure it out', 'again???', or similar. Also for complex debugging, env issues, config/deployment failures. All task types: code, config, research, writing, deployment, infra, API. Do NOT trigger on first-attempt failures or when a known fix is executing.

0 14.1K 10 days ago · Uploaded Detail →
imbue-ai imbue-ai
from GitHub Development & Coding
  • 📁 scripts/
  • 📄 SKILL.md

vet

Run vet immediately after ANY logical unit of code changes. Do not batch your changes, do not wait to be asked to run vet, make sure you are proactive.

0 179 10 days ago · Uploaded Detail →
LycheeMem LycheeMem
from GitHub Data & AI
  • 📁 skills/
  • 📁 src/
  • 📄 index.ts
  • 📄 INSTALL_OPENCLAW.md
  • 📄 INSTALL_OPENCLAW_zh.md

LycheeMem

This plugin is a thin adapter between OpenClaw and LycheeMem. It does not replace `memory-core`, does not claim `plugins.slots.memory`, and does not duplicate LycheeMem algorithms.

0 193 12 days ago · Uploaded Detail →
microsoft microsoft
from GitHub Development & Coding
  • 📄 SKILL.md

configure-canvas-mcp

Configure the Canvas Authoring MCP server for Claude Code, VS Code Copilot, or GitHub Copilot CLI. USE WHEN "configure MCP", "set up MCP server", "MCP not working", "connect Canvas Apps MCP", "canvas-authoring not available", "MCP not configured", "set up canvas apps". DO NOT USE WHEN prerequisites are missing — direct the user to install .NET 10 SDK first.

0 111 12 days ago · Uploaded Detail →
patrick-fu patrick-fu
from GitHub Development & Coding
  • 📁 evals/
  • 📁 references/
  • 📄 SKILL.md

brainstorm

Explore ideas, clarify goals, and help the user narrow down directions before planning or coding. Use this whenever the user proposes a new feature or idea, asks "what do you think about X", says "I'm thinking of building Y", wants to compare approaches, asks how to approach a problem, or seems to be exploring rather than ready to execute. Also use it when the user says "brainstorm", "let's think about this", "what's the best way to...", or any time the right next step is to clarify the problem and converge on a direction, not to write code yet. --- # Brainstorm Before anything else, ask. Don't jump to solutions or implementation. The goal is to draw out what the user actually means, uncover what they have not said yet, and help them converge on a direction. Think of this as Socratic dialogue with momentum: use questions to guide the thinking, but do not leave the user wandering in options forever. ## Start With Context Before asking, absorb the context that already exists in the conversation, codebase, docs, and project state. Do not ask for information you can already infer or look up directly. ## Guide The Conversation

0 5 6 days ago · Uploaded Detail →
questdb questdb
from GitHub Databases & Storage
  • 📁 references/
  • 📄 SKILL.md

questdb

Use this skill whenever working with QuestDB — a high-performance time-series database. Trigger on any mention of QuestDB, time-series SQL with SAMPLE BY, LATEST ON, ASOF JOIN, ILP ingestion, or the questdb Python/Go/Java/Rust/.NET client libraries. Also trigger when writing Grafana queries against QuestDB, creating materialized views for time-series rollups, working with order book or financial market data in QuestDB, or any SQL that involves designated timestamps or time-partitioned tables. QuestDB extends SQL with unique time-series keywords — standard PostgreSQL or MySQL patterns will fail. Always read this skill before writing QuestDB SQL to avoid hallucinating incorrect syntax. --- # QuestDB Skill ## How to Use This Skill **IMPORTANT — MINIMIZE ROUND-TRIPS:** - Do NOT explore library source code (cryptofeed, questdb, etc.) - Do NOT check library versions or verify callback signatures - Do NOT read installed package files to "understand the API" - Do NOT verify infrastructure (Docker containers, Grafana health) is running — trust the user's prompt - Do NOT start `02_ingest.py` separately — `03_dashboard.py` launches it and verifies data automatically - Do NOT read extra reference files for topics already covered in this skill file - DO read reference files when their topic applies (e.g. enterprise.md for auth, grafana-advanced.md for complex panels) - Do NOT use task tracking (TaskCreate/TaskUpdate) for straightforward builds - Do NOT add `sleep` commands to wait for data or check background processes (the deploy script handles this) - Do NOT Ctrl+C, restart, or re-launch the ingestion process once `03_dashboard.py` has started it - Do NOT put VWAP, Bollinger, or RSI in separate timeseries panels — they are refIDs on the OHLC candlestick panel - Do NOT omit or empty `fieldConfig.overrides` — they put RSI on a right Y-axis (0-100%) and spread on a right axis. Without them, different scales crush the chart flat. - Do NOT set dashboard refresh to `"5s"` — the defa

0 6 9 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