Search, install, and manage AI agent skills, commands, tools, knowledge, workflows, wikis, vaults, and memories from any source. Works with Claude Code, OpenCode, Cursor, and any AI coding assistant.
Generate conductor-compatible YAML plans. Use when user requests "help me implement X", "create a plan for X", or asks for implementation guidance. NOT for questions, debugging, or code reviews.
Unified browser automation skill. Supports lightweight HTTP fetch for static pages, web search, and full interactive Chromium automation for JS-heavy sites.
ClawGuard v3 Auditor - 企业级 Skill 安全审计器，支持意图偏离检测、SAST、供应链安全、ML 异常检测。当用户要求审计、检测、安装前检查一个 Skill 的安全性时触发。
通过阿里云邮箱、QQ邮箱或163邮箱等发送和接收邮件。支持发送普通邮件、带附件邮件、接收邮件、检查新邮件。当用户要求发送邮件、查看邮件、检查新邮件时使用。
Interact with Obsidian vaults using the Obsidian CLI to read, create, search, and manage notes, tasks, properties, and more. Also supports plugin and theme development with commands to reload plugins, run JavaScript, capture errors, take screenshots, and inspect the DOM. Use when the user asks to interact with their Obsidian vault, manage notes, search vault content, perform vault operations from the command line, or develop and debug Obsidian plugins and themes.
MUST use when user asks to create, edit, manage, or share snippets, or asks how snippets work
Inspect GitHub PR for CI failures, merge conflicts, update-branch requirements, reviewer comments, change requests, and unresolved review threads. Create fix plans and implement after user approval. Reply to ALL reviewer comments with action taken or reason for not addressing, then resolve threads. Notify reviewers after fixes.
Add a Model Context Protocol (MCP) server to extend your toolbox with external tools
SSH into host `h100_sglang`, enter Docker container `sglang_bbuf`, work in `/data/bbuf/repos/sglang`, and use the ready H100 remote environment for SGLang **diffusion** development and validation. Use when a task needs diffusion model smoke tests, Triton/CUDA kernel validation, torch.compile diffusion checks, or a safe remote copy for diffusion-specific SGLang changes.
Generates optimized prompts for any AI tool.
Generates OpenChart (https://github.com/tryopendata/openchart) chart, table, graph, and sankey specs from data, and guides editorial design decisions. Use when creating visualizations, building charts, rendering data tables, generating VizSpec JSON, creating network graphs, building sankey/flow diagrams, answering questions about OpenChart types and encoding rules, or making design decisions about chart type selection, color strategy, typography, annotations, and editorial framing. Also covers custom D3.js infographics for cases beyond declarative specs. --- # Data Visualization with OpenChart **Core concept:** Write a VizSpec JSON object, render with `<Chart>` / `<DataTable>` / `<Graph>` / `<Sankey>` (React/Vue/Svelte) or `createChart()` / `createTable()` / `createGraph()` / `createSankey()` (vanilla JS). The engine validates, compiles, and renders. Specs are plain JSON, no imperative drawing. See https://github.com/tryopendata/openchart for the rendering engine. **CSS is required.** OpenChart's stylesheet must be loaded for proper rendering (chrome, tables, tooltips, brand watermark). Framework imports handle this automatically, but CDN/standalone HTML needs an explicit `<link>`: ```html <link rel="stylesheet" href="https://esm.sh/@opendata-ai/openchart-vanilla/styles.css"> ``` See [rendering reference](references/rendering.md) for details. ## Chart Selection Decision Tree ``` Single value to highlight -> Use chrome.title as a big number display Temporal x-axis column? -> 1 series: line | 2-5 series: line + color | 6+: filter to top 5 Categorical + numeric? -> Ranked list: bar (horizontal) | Periodic (Q1, Jan): bar (vertical) | 2-6 composition: arc Two numeric columns? -> point (optional size/color for 3rd/4th dims) Categorical + series + num? -> stacked bar (use color for series) Distribution/spread? -> circle (strip plot) Nodes + edges / network? -> graph (force/radial/hierarchical layout) Flow between stages? -> sankey
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
├─ ⭐ 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
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.
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.
Everything you need to know: what skills are, how they work, how to find/import them, and how to contribute.
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.
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.
Use these three together:
Note: file size for all methods should be within 10MB.
Typical paths (may vary by local setup):
One SKILL.md can usually be reused 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.
Some skills come from public GitHub repositories and some are uploaded by SkillWink creators. Always review code before installing and own your security decisions.
Most common reasons:
We try to avoid that. Use ranking + comments to surface better skills:
