Free to get · One-click to use
Use this skill when you need to compile CPython, run tests, verify your changes work, check if a fix is correct, or debug test failures. Covers building from source with ./configure and make, ccache for faster rebuilds, Argument Clinic regeneration, and the unittest-based test system (NOT pytest). Essential for any task that requires running code or tests.
Self-evolving AI agent system with 26 tools, three-layer memory, MCP plugins, and 24/7 self-repair in pure Python.
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
AuDHD-aware Socratic mentor for Python, Data Engineering, and SQL. Teaches through guided questioning with network→DE bridges, bottom-up processing support, dopamine-driven productive struggle, and adaptive scaffolding. Triggers on: teach me, help me understand, study session, mentor me, quiz me on, explain, learn, stuck on, or any Python/SQL/DE learning request.
当用户要求“设置 ChromaDB”、“创建 Chroma 集合”、“向 ChromaDB 添加嵌入”、“查询 ChromaDB”、“搜索向量”、“使用 ChromaDB 进行语义搜索”、“过滤 ChromaDB 结果”、“ChromaDB 元数据过滤”、“配置 Chroma”、“使用 ChromaDB 持久客户端”、“从 ChromaDB 删除”时，或者当编写与 chromadb Python 包交互的任何代码。提供最新的API模式、过滤语法、集合配置和嵌入函数集成。
一站式学术研究工作流：论文检索与阅读(arXiv + Zotero)、文献综述写作(Google Docs)、 论文精读与审稿(paper-reviewer)、学术插图生成(PaperBanana)、架构图绘制(draw.io)、演示文稿制作(python-pptx / Pencil)。 整合 paper-research、paper-reviewer、google-docs、paper-banana、drawio、zotero-mcp、pptx 七大子技能。
Perform thorough, structured code reviews on Python, JavaScript, TypeScript, or any common language. Use this skill when asked to review code, audit a function, check a pull request, or give feedback on code quality, security, or performance. Use even if the user says "take a look at this" or "what do you think of this."
MCP 应用程序 UI 的综合 gdansk 实施和调试指南。在添加或修复 Amber 和 FastMCP 工具 UI、将 `@amber.tool(..., widget=...)` 连接到 React `views/widgets/**/widget.tsx` 或 `widget.jsx` 条目、启用 SSR、配置元数据或 `cache_html`、添加 JS 插件适配器（例如 Tailwind CSS）、在 FastAPI 下安装或诊断 gdansk 捆绑和运行时错误时使用。
Create publication-quality figures with matplotlib/seaborn (Python) or ggplot2 (R). Covers multi-panel layouts, colorblind-safe palettes, and journal export settings.
Instrument Python LLM apps, build golden datasets, write eval-based tests, run them, and root-cause failures — covering the full eval-driven development cycle. Make sure to use this skill whenever a user is developing, testing, QA-ing, evaluating, or benchmarking a Python project that calls an LLM, even if they don't say "evals" explicitly. Use for making sure an AI app works correctly, catching regressions after prompt changes, debugging why an agent started behaving differently, or validating output quality before shipping.
Writes and runs Python code in a sandbox. Describe the task in plain English — the skill will write and execute the program.
LLMaps 的使用和贡献指南：用于交互式 Web 地图的 Python 库（MapLibre、单个 HTML）。当使用 llmaps（pip 或 repo）构建地图时、编辑 llmaps 存储库时或当用户提及 llmaps、MapLibre 或地图生成时使用。
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:
