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Found 7,154 Skills
Conducts citation-backed research using Firecrawl MCP search, scrape, map, crawl, and agent tools with selectable quick, standard, deep, and ultradeep modes. Use for multi-source comparisons, technical evaluations, market research, and high-stakes decision support.
REQUIRED skill for planning and designing coding tasks before implementation. Use this skill when: (1) User asks to "plan", "design", "create a plan", or "think before coding" (2) Complex tasks requiring multiple files or steps (3) Tasks involving both backend and frontend changes (4) Breaking down ambiguous requirements into concrete tasks This skill ensures plans are properly documented, saved as markdown, reviewed by subagent, and registered as todos before any code is written. Do NOT skip this skill for non-trivial tasks.
Generate AI-friendly Python CLIs using Click, Pydantic, and uv. Use when user wants to create a new CLI tool that follows best practices for agentic coding environments.
Orchestrate parallel debugging agents with root-cause tracing for multi-failure scenarios
Discover and install automation hooks for Claude Code and Opencode. This skill should be used when users ask to "list hooks", "install a hook", "show available hooks", "enable hook", "what hooks are available", or need help managing agent automation hooks.
Capture AI agent sessions in your git workflow. Use for setup, rewinding to checkpoints, exploring session history, and troubleshooting.
Native SwiftUI WebKit integration with the new WebView struct and WebPage observable class. Covers WebView creation from URLs, WebPage for navigation control and state management, JavaScript execution (callJavaScript with arguments and content worlds), custom URL scheme handlers, navigation management (load, reload, back/forward), navigation decisions, text search (findNavigator), content capture (snapshots, PDF generation, web archives), and configuration (data stores, user agents, JS permissions). Use when embedding web content in SwiftUI apps instead of the old WKWebView + UIViewRepresentable/NSViewRepresentable bridge pattern. This is a brand new API — do NOT use the old WKWebView wrapping approach.
Optimize LLM prompts, tools, and agents in Opik using standardized optimizer workflows (prompt optimization, tool optimization, and parameter tuning), dataset/metric wiring, and result interpretation.
Generates wiring verification YAML for loom plans. Helps agents prove that features are properly integrated — commands registered, endpoints mounted, modules exported, components rendered. Use when writing truths/artifacts/wiring fields for loom plan stages.
Use this agent when you need to verify that a UI implementation matches its Figma design specifications. This agent should be called after code has been written to implement a design, particularly after HTML/CSS/React components have been created or modified. The agent will visually compare the live implementation against the Figma design and provide detailed feedback on discrepancies.\n\nExamples:\n- <example>\n Context: The user has just implemented a new component based on a Figma design.\n user: "I've finished implementing the hero section based on the Figma design"\n assistant: "I'll review how well your implementation matches the Figma design."\n <commentary>\n Since UI implementation has been completed, use the design-implementation-reviewer agent to compare the live version with Figma.\n </commentary>\n </example>\n- <example>\n Context: After the general code agent has implemented design changes.\n user: "Update the button styles to match the new design system"\n assistant: "I've updated the butto...
Use this agent when you need a final review pass to ensure code changes are as simple and minimal as possible. This agent should be invoked after implementation is complete but before finalizing changes, to identify opportunities for simplification, remove unnecessary complexity, and ensure adherence to YAGNI principles. Examples: <example>Context: The user has just implemented a new feature and wants to ensure it's as simple as possible. user: "I've finished implementing the user authentication system" assistant: "Great! Let me review the implementation for simplicity and minimalism using the code-simplicity-reviewer agent" <commentary>Since implementation is complete, use the code-simplicity-reviewer agent to identify simplification opportunities.</commentary></example> <example>Context: The user has written complex business logic and wants to simplify it. user: "I think this order processing logic might be overly complex" assistant: "I'll use the code-simplicity-reviewer agent to analyze the complexity...
Use this agent when you need to perform security audits, vulnerability assessments, or security reviews of code. This includes checking for common security vulnerabilities, validating input handling, reviewing authentication/authorization implementations, scanning for hardcoded secrets, and ensuring OWASP compliance. <example>Context: The user wants to ensure their newly implemented API endpoints are secure before deployment.\nuser: "I've just finished implementing the user authentication endpoints. Can you check them for security issues?"\nassistant: "I'll use the security-sentinel agent to perform a comprehensive security review of your authentication endpoints."\n<commentary>Since the user is asking for a security review of authentication code, use the security-sentinel agent to scan for vulnerabilities and ensure secure implementation.</commentary></example> <example>Context: The user is concerned about potential SQL injection vulnerabilities in their database queries.\nuser: "I'm worried about SQL inj...