io.github.ComeOnOliver/skillshub/cursor-mem

Cursorでclaude-memのMCPサーバーにアクセスし、過去のセッション記録を検索・新しい観測を記録。トリガー: 'メモリ検索', 'claude-mem', '過去の判断', '記録して', 'memory search', 'past decisions'. Do NOT load for: 通常のコーディング、一時的なメモ、実装作業。

io.github.AlekseiUL/heisenberg-team/cursor-agent

A comprehensive skill for using the Cursor CLI agent for various software engineering tasks (updated for 2026 features, includes tmux automation guide). Use when user wants to run Cursor agent, code with Cursor, or automate development tasks via Cursor CLI.

io.github.bradygaster/squad/security-review

How to review PRs for security — credentials, injection, workflow permissions, supply chain, git operation safety

io.github.openshift/lightspeed-console/css-review

Review CSS for coding style, PatternFly token usage, and best practices. Use when the user asks to review CSS, check styles, or audit CSS files.

io.github.CopilotKit/CopilotKit/mcp-builder

DEPRECATED: This skill has been replaced by `mcp-app-builder`. Check if `mcp-app-builder` is available in the skills folder. If not, install it: `npx skills install mcp-use/mcp-use --skill mcp-app-builder` Use `mcp-app-builder` instead of this skill. Build Model Context Protocol (MCP) servers with mcp-use framework. Use when creating MCP servers, defining tools/resources/prompts, working with mcp-use, bootstrapping MCP projects, or when user mentions MCP development, tools, resources, or prompts.

io.github.CopilotKit/CopilotKit/mcp-apps-builder

**MANDATORY for ALL MCP server work** - mcp-use framework best practices and patterns. **READ THIS FIRST** before any MCP server work, including: - Creating new MCP servers - Modifying existing MCP servers (adding/updating tools, resources, prompts, widgets) - Debugging MCP server issues or errors - Reviewing MCP server code for quality, security, or performance - Answering questions about MCP development or mcp-use patterns - Making ANY changes to server.tool(), server.resource(), server.prompt(), or widgets This skill contains critical architecture decisions, security patterns, and common pitfalls. Always consult the relevant reference files BEFORE implementing MCP features.

io.github.tranhieutt/software_development_department/kubernetes-architect

Expert Kubernetes architect specializing in cloud-native infrastructure, advanced GitOps workflows (ArgoCD/Flux), and enterprise container orchestration.

io.github.sd0xdev/sd0x-dev-flow/refactor

Multi-target refactoring orchestrator. Use when: cleaning up messy code/docs, simplifying code, restructuring documents, batch cleanup. Not for: new features (use feature-dev), bug fixes (use bug-fix), code understanding (use code-explore). Output: refactored code/docs + review gate.

io.github.brycewang-stanford/Auto-Empirical-Research-Skills/database-comparison-guide

Compare major academic databases and when to use each for research

io.github.brycewang-stanford/Auto-Empirical-Research-Skills/deploy

Render Quarto slides and sync to docs/ for GitHub Pages deployment. Use when deploying lecture slides after making changes.

io.github.brycewang-stanford/Auto-Empirical-Research-Skills/deploy

Render Quarto slides and sync to docs/ for GitHub Pages deployment. Use when deploying lecture slides after making changes.

io.github.brycewang-stanford/Auto-Empirical-Research-Skills/api-data-fetcher

Fetch economic data from FRED, World Bank, and other APIs

io.github.brycewang-stanford/Auto-Empirical-Research-Skills/python-reproducibility-guide

Reproducible Python environments, notebooks, and literate programming

io.github.brycewang-stanford/Auto-Empirical-Research-Skills/python-causality-guide

Learn causal inference with Python using the Brave and True handbook

io.github.brycewang-stanford/Auto-Empirical-Research-Skills/python-dataviz-guide

Publication-quality data visualization with matplotlib, seaborn, and plotly

io.github.brycewang-stanford/Auto-Empirical-Research-Skills/python-panel-data

Panel data analysis with Python using linearmodels and pandas.

io.github.brycewang-stanford/Auto-Empirical-Research-Skills/algorithm-designer

Design and document statistical algorithms with pseudocode and complexity analysis

io.github.brycewang-stanford/Auto-Empirical-Research-Skills/automation

10 research automation skills. Trigger: automating experiments, tracking results, reproducible pipelines. Design: ML experiment management, workflow orchestration, and lab automation tools.

io.github.brycewang-stanford/Auto-Empirical-Research-Skills/20-wenddymacro-python-econ-skill

Use when writing Python code for DSGE models, HANK models, numerical economic computation, causal inference, or quantitative economic data analysis

io.github.brycewang-stanford/Auto-Empirical-Research-Skills/zotero-pdf2zh-guide

PDF Chinese translation plugin for Zotero reference manager

io.github.secondsky/claude-skills/mobile-app-debugging

Mobile app debugging for iOS, Android, cross-platform frameworks. Use for crashes, memory leaks, performance issues, network problems, or encountering Xcode instruments, Android Profiler, React Native debugger, native bridge errors.

io.github.secondsky/claude-skills/mobile-app-testing

Mobile app testing with unit tests, UI automation, performance testing. Use for test infrastructure, E2E tests, testing standards, or encountering test framework setup, device farms, flaky tests, platform-specific test errors.

io.github.secondsky/claude-skills/mobile-first-design

Designs responsive interfaces starting from mobile screens with progressive enhancement for larger devices. Use when building responsive websites, optimizing for mobile users, or implementing adaptive layouts.

io.github.secondsky/claude-skills/mobile-offline-support

Offline-first mobile apps with local storage, sync queues, conflict resolution. Use for offline functionality, data sync, connectivity handling, or encountering sync conflicts, queue management, storage limits, network transition errors.