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Found 3,732 Skills
ALWAYS LOAD WHEN WORKING WITH PYSIDE6, QT, OR DESKTOP GUI CODE. PySide6 desktop apps: Manager→Service→Wrapper architecture, qasync integration, signals, system tray, testing.
Guides use of ProjectDiscovery Katana for web crawling and spidering in security testing and recon workflows. Covers installation, standard vs headless mode, scope and rate limits, JSONL output, and piping from httpx or URL lists. Use when the user mentions Katana, projectdiscovery/katana, web crawling, spidering, endpoint discovery, attack surface mapping, or chaining crawlers in automation pipelines.
Master the art of calls-to-action that convert. Direct CTAs, transitional CTAs, button copy, and microcopy that turns readers into customers. Use when: Writing button text for landing pages and emails; Creating CTAs for different stages of awareness; Designing click-worthy microcopy; A/B testing CTA variations; Building email sequences with graduated CTAs
This skill should be used when the user asks to "optimize TypeScript performance", "speed up tsc compilation", "configure tsconfig.json", "fix type errors", "improve async patterns", or encounters TS errors (TS2322, TS2339, "is not assignable to"). Also triggers on .ts, .tsx, .d.ts file work involving type definitions, module organization, or memory management. Does NOT cover TypeScript basics, framework-specific patterns, or testing.
Manages Apache Airflow operations including listing, testing, running, and debugging DAGs, viewing task logs, checking connections and variables, and monitoring system health. Use when working with Airflow DAGs, pipelines, workflows, or tasks, or when the user mentions testing dags, running pipelines, debugging workflows, dag failures, task errors, dag status, pipeline status, list dags, show connections, check variables, or airflow health.
Implement backup and restore strategies for disaster recovery. Use when creating backup plans, testing restore procedures, or setting up automated backups.
This skill should be used when working with DSPy.rb, a Ruby framework for building type-safe, composable LLM applications. Use this when implementing predictable AI features, creating LLM signatures and modules, configuring language model providers (OpenAI, Anthropic, Gemini, Ollama), building agent systems with tools, optimizing prompts, or testing LLM-powered functionality in Ruby applications.
Code quality orchestrator enforcing TRUST 5 validation, proactive code analysis, linting standards, and automated best practices. Use when performing code review, quality gate checks, lint configuration, TRUST 5 compliance validation, or establishing coding standards. Do NOT use for writing tests (use moai-workflow-testing instead) or debugging runtime errors (use expert-debug agent instead).
Automatically suggest tests for new functions and components. Use when new code is written, functions added, or user mentions testing. Creates test scaffolding with Jest, Vitest, Pytest patterns. Triggers on new functions, components, test requests, testing mentions.
Generates consistent UI components, layouts, and design tokens following a design system. Enforces spacing, color, typography, and accessibility standards across React/TypeScript projects. Use when creating new UI components, building page layouts, choosing colors or typography, setting up design tokens, or reviewing UI code for design consistency. Covers 8pt spacing grid, Tailwind CSS token usage, shadcn/ui primitives, WCAG 2.1 AA compliance, responsive breakpoints, semantic HTML structure, and TypeScript component interfaces. Does NOT cover backend implementation (use python-backend-expert), testing (use react-testing-patterns), or deployment (use deployment-pipeline).
Build production ML systems with PyTorch 2.x, TensorFlow, and modern ML frameworks. Implements model serving, feature engineering, A/B testing, and monitoring. Use PROACTIVELY for ML model deployment, inference optimization, or production ML infrastructure.
This skill provides project-specific coding conventions, architectural principles, repository structure standards, testing patterns, and contribution guidelines for the better-chatbot project (https://github.com/cgoinglove/better-chatbot). Use this skill when contributing to or working with better-chatbot to understand the design philosophy and ensure code follows established patterns. Includes: API architecture deep-dive, three-tier tool system (MCP/Workflow/Default), component design patterns, database repository patterns, architectural principles (progressive enhancement, defensive programming, streaming-first), practical templates for adding features (tools, routes, repositories). Use when: working in better-chatbot repository, contributing features/fixes, understanding architectural decisions, following server action validators, implementing tools/workflows, setting up Playwright tests, adding API routes, designing database queries, building UI components, handling multi-AI provider integration Keywords: better-chatbot, chatbot contribution, better-chatbot standards, chatbot development, AI chatbot patterns, API architecture, three-tier tool system, repository pattern, progressive enhancement, defensive programming, streaming-first, compound component pattern, Next.js chatbot, Vercel AI SDK chatbot, MCP tools, workflow builder, server action validators, tool abstraction, DAG workflows, shared business logic, safe() wrapper, tool lifecycle