DevOps

Enterprise Vercel Edge Platform with AI-powered modern deployment, Context7 integration, and intelligent edge orchestration for scalable web applications

This skill should be used when the user uses ambiguous terminology like "make it talk", "we need an api", "make it portable", "check for gaps", asks meta-questions like "am I making sense?", "does this make sense?", mentions being a "non-technical user", uses vague action verbs ("make it work", "do the thing"), mixes domain languages, uses invented terms, or when detecting semantic drift between human natural language and technical precision. Provides semantic translation, disambiguation, and domain knowledge mapping across Autogen, Langroid, MCP (Model Context Protocol), UTCP (Universal Tool Calling Protocol), FastAPI, Git/Gitflow, SRE (Site Reliability Engineering), and Memory Graphs domains. Bridges the gap between user intent and technical specificity through ontological translation.

This skill provides comprehensive knowledge for building applications with Cloudflare Sandboxes SDK, which enables secure, isolated code execution in full Linux containers at the edge. It should be used when executing untrusted code, running Python/Node.js scripts, performing git operations, building AI code execution systems, creating interactive development environments, or implementing CI/CD workflows that require full OS capabilities. Use when: Setting up Cloudflare Sandboxes, executing Python/Node.js code safely, managing stateful development environments, implementing AI code interpreters, running shell commands in isolation, handling git repositories programmatically, building chat-based coding agents, creating temporary build environments, processing files with system tools (ffmpeg, imagemagick, etc.), or when encountering issues with container lifecycle, session management, or state persistence. Keywords: cloudflare sandbox, container execution, code execution, isolated environment, durable objects, linux container, python execution, node execution, git operations, code interpreter, AI agents, session management, ephemeral container, workspace, sandbox SDK, @cloudflare/sandbox, exec(), getSandbox(), runCode(), gitCheckout(), ubuntu container

Comprehensive observability setup patterns for Google ADK agents including logging configuration, Cloud Trace integration, BigQuery Agent Analytics, and third-party observability tools (AgentOps, Phoenix, Weave). Use when implementing monitoring, debugging agent behavior, analyzing agent performance, setting up tracing, or when user mentions observability, logging, tracing, BigQuery analytics, AgentOps, Phoenix, Arize, or Weave.

Run SonarQube/SonarCloud static code analysis to check code quality, detect security vulnerabilities, code smells, and bugs. Use when the user mentions SonarQube, code quality analysis, security scanning, static analysis, or wants to check for vulnerabilities.

Systematic debugging workflow to reproduce, isolate, and fix hard software bugs, resolve related lint issues, and add tests and guardrails to prevent regressions. This skill should be used for complex bugs that teams struggle to fix, flaky/intermittent failures, production-only bugs, and environment-specific issues where code changes must be lint-clean.

Frontend development specialist covering React 19, Next.js 16, Vue 3.5, and modern UI/UX patterns with component architecture

Generates a complete iOS app icon set with all required sizes. Use when asked to create an app icon, design an iOS icon, generate app store artwork, or make an icon for an iPhone/iPad app. Follows a philosophy-first approach - first defining the visual identity and concept, then producing production-ready icons.

Tauri v2 跨平台应用开发指南。用于开发桌面 (macOS/Windows/Linux) 和移动端 (iOS/Android) 应用。包含项目初始化、Rust 后端、React 前端集成、移动端配置等最佳实践。当需要创建 Tauri 项目、配置移动端支持、编写 Rust 命令、或解决 Tauri 相关问题时使用此 skill。

Generate code in SLOP (Symbolic LLM-Optimized Programming), a language designed for minimal human involvement in coding. Use when: (1) User asks for SLOP code, (2) Need strong contracts and range types, (3) Creating code with typed holes for incremental generation, (4) Generating efficient C code. SLOP uses S-expression syntax and transpiles to C.

Parallel execution of analysis check skills. Command-specific - /ms uses all 3 checks, /build uses 2, /audit uses 2 different ones. See command for which checks to run.

Expert RP2350 development with MicroPython, covering Pimoroni Presto hardware, touchscreen interfaces, RGB lighting control, BLE server implementation, and display rendering. Use when developing for RP2350 boards, implementing touch UI, managing BLE communication, or working with RGB backlights.

Master Kubernetes observability, monitoring with Prometheus, logging, metrics, and distributed tracing. Learn to implement comprehensive monitoring strategies.

Maintaining code quality and standards in StickerNest. Use when refactoring code, checking file sizes, splitting large files, reviewing code structure, or when files exceed length limits. Covers file length limits, refactoring patterns, code organization, and the "check existing code first" principle.

Multi-stage deep investigation and reasoning for complex problems using PAL MCP. Use for architecture decisions, complex analysis, performance challenges, or when you need thorough reasoning. Triggers on complex problems requiring deep thought, hypothesis testing, or expert analysis.

Transform rough drafts into polished work through systematic revision. Multiple passes, specific focus, and the discipline to kill your darlings. The alchemical process of making good work great.

Create Docker configurations and deployment workflows for Scrapy projects when containerizing spiders or deploying to production. Generates Dockerfiles, docker-compose setups, and orchestration configurations.

Bootstraps complete backend with Apso, including API setup, database configuration, and testing. Triggers when user needs to create backend, setup API, or initialize server.

评估用户故事质量的六维度框架（独立性、可协商、有价值、可估算、小粒度、可测试），系统化审查需求质量。当需要编写用户故事、评审需求文档、拆分史诗故事时使用。提供分级检查清单和低质量故事的改进建议。

Reference and maintain the project's technology stack including frameworks, languages, databases, testing tools, and third-party services to ensure consistency across the codebase. Use this skill when making technology decisions, adding new dependencies, choosing appropriate tools or libraries, configuring build systems, setting up testing frameworks, or documenting the tech stack. Apply this skill when selecting which framework, library, or tool to use for a given task, when ensuring code follows the conventions of the chosen stack (React patterns, Python idioms, Rails conventions), when integrating third-party services, or when documenting technology choices in README or architecture documentation. This skill ensures all team members use consistent technologies, new additions align with existing stack decisions, technology choices are documented with rationale, and the project maintains coherent patterns rather than mixing conflicting approaches or frameworks.