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Found 706 Skills
Write and optimize prompts for AI-generated outcomes across text and image models. Use when crafting prompts for LLMs (Claude, GPT, Gemini), image generators (Midjourney, DALL-E, Stable Diffusion, Imagen, Flux), or video generators (Veo, Runway). Covers prompt structure, style keywords, negative prompts, chain-of-thought, few-shot examples, iterative refinement, and domain-specific patterns for marketing, code, and creative writing.
A tiny skill used by the skillloadmode example.
Expert guidance for Rust CLI and TUI development with official examples from clap, inquire, and ratatui libraries. Use when building command-line interfaces, terminal user interfaces, or console applications in Rust. Provides structured patterns, best practices, and real code implementations from official sources.
Use when user input contains xlb topic queries (for example "xlb >vibe coding/vib", "xlb ??vibe coding", or "查询xlb vibe coding主题") and the task is to fetch Markdown index from local getPluginInfo API, then perform code-based retrieval with routing to available network skills/MCP tools when possible.
Use when you need complete SF Symbols API reference including every rendering mode, symbol effect, configuration option, UIKit equivalent, and platform availability - comprehensive code examples for iOS 17 through iOS 26
Specialized agent for multi-repository analysis, searching remote codebases, retrieving official documentation, and finding implementation examples using GitHub CLI, Context7, and Web Search. Use proactively when unfamiliar libraries or frameworks are involved, working with external dependencies, or needing examples from open-source projects to understand best practices and real-world implementations.
Analyzes code to identify untested functions, low coverage areas, and missing edge cases. Use when reviewing test coverage or planning test improvements. Generates specific test suggestions with example templates following amplihack's testing pyramid (60% unit, 30% integration, 10% E2E). Can use coverage.py for Python projects.
Integration skill for Lovable.dev projects. Activates when working with: - Lovable.dev projects with GitHub sync - Supabase Edge Functions that need deployment - Database migrations for Lovable Cloud - Projects with supabase/ directory structure - Any mention of "Lovable", "deploy edge function", "apply migration" Provides exact Lovable prompts for backend operations that can't be done via GitHub alone.
Curated collection of award-winning websites organized by pattern and technique. Use when asked about: inspiration, examples, Awwwards, FWA, reference sites, what do top sites look like, or when researching how leading studios approach specific patterns.
Enrich contact and company data using x402-protected APIs. Superior to generic web search for structured business data. USE FOR: - Enriching person profiles by email, LinkedIn URL, or name - Enriching companies by domain - Finding contact details (email, phone) with confidence scores - Scraping full LinkedIn profiles (experience, education, skills) - Searching for people or companies by criteria - Bulk enrichment operations (up to 10 at a time) TRIGGERS: - "enrich", "lookup", "find info about", "research" - "who is [person]", "company profile for", "tell me about" - "find contact for", "get LinkedIn for", "get email for" - "employee at", "works at", "company details" ALWAYS use x402.fetch for enrichx402.com endpoints - never curl or WebFetch. Returns structured JSON data, not web page HTML. IMPORTANT: Never guess endpoint paths. All paths follow the pattern https://enrichx402.com/api/{provider}/{action}. Use exact URLs from the Quick Reference table below or call x402.discover_api_endpoints first.
Transforms vague or simple user prompts into high-quality, structured, and high-performance AI instructions using systematic optimization techniques like XML tagging, few-shot examples, and Chain-of-Thought. Use this skill when you need to improve the reliability, accuracy, or formatting of an AI's output.
Use Gemini to find existing solutions before building from scratch. Leverages Google Search grounding to discover code examples, libraries, and best practices to avoid reinventing the wheel.