repomix
Guide for using Repomix - a powerful tool that packs entire repositories into single, AI-friendly files. Use when packaging codebases for AI analysis, generating context for LLMs, creating codebase snapshots, a...
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Guide for using Repomix - a powerful tool that packs entire repositories into single, AI-friendly files. Use when packaging codebases for AI analysis, generating context for LLMs, creating codebase snapshots, a...
Performance analysis, profiling techniques, bottleneck identification, and optimization strategies for code and systems. Use when the user needs to improve performance, reduce resource usage, or identify and fi...
Guide for implementing Cloudflare Browser Rendering - a headless browser automation API for screenshots, PDFs, web scraping, and testing. Use when automating browsers, taking screenshots, generating PDFs, scrap...
Comprehensive guide for building serverless applications with Cloudflare Workers. Use when developing Workers, configuring bindings, implementing runtime APIs, testing Workers, using Wrangler CLI, deploying to...
Browser automation, debugging, and performance analysis using Puppeteer CLI scripts. Use for automating browsers, taking screenshots, analyzing performance, monitoring network traffic, web scraping, form automa...
This skill should be used when systematically testing the NetBox MCP server after code changes or to validate tool functionality. Provides structured protocol for discovering and testing MCP tools with a live N...
Systematic code review workflow using zen mcp's codex tool. Use this skill when the user explicitly requests "use codex to check the code", "check if the recently generated code has any issues", or "check the c...
Measure what matters with proper event tracking, funnels, cohorts, and metrics. Use when setting up analytics, tracking features, or understanding behavior.
使用perf-prof进行Linux系统问题分析。perf-prof是基于perf_event的系统级分析工具,事件在内存中实时处理,可长期运行。触发场景:(1) CPU使用率高、热点分析 (2) 进程状态异常(D/S状态多) (3) 延迟抖动、响应慢 (4) 内存泄露...
Demonstrates plugin skill discovery; logic lives in the main example runtime.
Add purposeful debug logging to improve observability without changing behavior.
Perform structured, actionable code reviews for Python code with clear findings and suggestions.
Use when errors occur deep in execution and you need to trace back to find the original trigger - systematically traces bugs backward through call stack, adding instrumentation when needed, to identify source o...
Use this skill when faced with a difficult debugging task where you need to replicate some bug or behavior in order to see what is going wrong.
Leveraging AI coding assistants and tools to boost development productivity, while maintaining oversight to ensure quality results.
Performance optimization guidelines for Splitrail. Use when optimizing parsing, reducing memory usage, or improving throughput.
L5-L8 函數簽名驗證 - 檢查參數、返回值、類型提示、文檔字符串。 BlueMouse 17-Layer Validation Group 2。 Triggers: "signature", "參數檢查", "type hints", "docstring"
BlueMouse 17-Layer Code Validation System - Complete Python code quality validation covering syntax, structure, function signatures, dependencies, types, logic, security, and performance. Triggers: "validate",...
L13-L17 類型和邏輯驗證 - 檢查類型一致性、邏輯完整性、錯誤處理、安全性、性能。 BlueMouse 17-Layer Validation Group 4(最深層檢查)。 Triggers: "logic", "security", "performance", "error handling", "安全檢查"
Use when exploring codebase, architecture, or call flows
Test Ark Dashboard with Playwright and create PRs with screenshots. Use when testing dashboard UI, taking screenshots for PRs, or reviewing dashboard changes.
Track user journeys with intent context and friction signals. Use when instrumenting onboarding, checkout, or any multi-step flow where you need to understand WHY users fail.
Configure crash symbolication for readable stack traces. Use when setting up dSYMs (iOS), ProGuard/R8 mappings (Android), or source maps (React Native).
Set up session replay for visual debugging. Use when implementing screen recording, replay features, or visual debugging tools.
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.