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Found 12,139 Skills
better-chatbot project conventions and standards. Use for contributing code, following three-tier tool system (MCP/Workflow/Default), or encountering server action validators, repository patterns, component design errors.
Solve a user-specified web task code-as-action style by driving a local Playwright browser through one bash command at a time, saving screenshots and an action log into `final_runs/run_<id>/`, and visually verifying the result. Use when the user asks to automate a web task (search, filter, form-fill, multi-step flow, data extraction) and wants reusable scripts plus screenshot evidence rather than a one-shot answer.
Use for simulator lifecycle, app install/launch, live viewing, UI inspection, touch/keyboard automation, screenshots, recordings, logs, pasteboard, hardware controls, and repeatable simulator flows.
Complete fal.ai video-to-video system. PROACTIVELY activate for: (1) Kling O1 video editing, (2) Sora Remix transformation, (3) Video upscaling, (4) Frame interpolation, (5) Style transfer (anime, painting), (6) Object replacement/removal, (7) Color correction, (8) Video enhancement pipelines. Provides: Edit types (general/style/object), upscaling options, style keywords, enhancement workflows. Ensures consistent video transformation without flickering.
Use when building creative browser demos with @chenglou/pretext — DOM-free text layout for ASCII art, typographic flow around obstacles, text-as-geometry games, kinetic typography, and text-powered generative art. Produces single-file HTML demos by default.
Fetch raw OHLCV price data using the aipa CLI. Use this skill whenever the user asks for price data, candle data, OHLCV data, historical prices, stock quotes, crypto prices, moving averages, volume data, or any raw market data without AI analysis. Also use for: top performers, worst performers, best stocks, top gainers, biggest losers, market movers, ranking tickers by price change / volume / value / MA scores / money flow (`aipa performers`); volume profile, POC, point of control, value area, support/resistance by volume, volume-by-price histogram (`aipa volume-profile`). Also use for fundamental data: company info, financial ratios, PE, PB, ROE, NPL, CAR, fundamental ranking and screening (`aipa fundamentals info/ratios/rank/screen`). Also use when the user wants to inspect what data is available, build charts, perform their own calculations, or get numbers for a spreadsheet. Even if the user doesn't mention "aipa", trigger this skill for any raw financial data, fundamental data, or market ranking request.
Research computing toolkit for optoelectronic information science and engineering, MATLAB/Octave, Python scientific analysis, signal processing, image processing, statistics, simulation, optimization, publication figures, sensor/time-series data, citation lookup, and common scientific libraries. Use when the user asks for MATLAB code, scientific Python, data analysis, plots, simulations, formulas, statistics, machine learning, optical/physical/materials computation, or reproducible research workflows.
Findings-first review discipline for code, diffs, task plans, live workflow changes, and implementation evidence.
Guide Claude on securing Vaadin 25 applications with Spring Security. This skill should be used when the user asks to "add security", "add login", "create a login view", "create a login form", "use Spring Security", "secure a view", "add authentication", "add authorization", "use @RolesAllowed", "use @PermitAll", "use @AnonymousAllowed", "use @DenyAll", "use VaadinSecurityConfigurer", "add OAuth2", "use OAuth2 login", "use Google login", "use Keycloak", "use GitHub login", "add logout", "add a logout button", "use AuthenticationContext", "protect a view", "role-based access", "configure SecurityFilterChain", or needs help with view access control, login forms, OAuth2 providers, or logout handling in Vaadin Flow.
You are a highly skilled content strategist and repurposing specialist. Use this skill when the user wants to repurpose existing content into new formats, find the best format for a content idea, humanize AI-generated content, or generate social media topic ideas. Activate when the user mentions "repurpose this," "turn this into," "content repurposing," "repurpose my blog," "repurpose my podcast," "repurpose my video," "repurpose my newsletter," "repurpose my email," "content format," "best format for this," "what format should I use," "humanize this," "make this sound human," "rewrite this AI content," "content calendar," "content ideas," "topic ideas," "content buckets," "1 post into many," "one piece many formats," "carousel from blog," "reel script from blog," "email from YouTube," "thread from newsletter," "LinkedIn post ideas," "Instagram content ideas," "Twitter content ideas," "content batching," "weekly content plan," "monthly content strategy," "swipe file," or "content workflow." Covers content repurposing across all major platforms and formats, format recommendation based on goals and audience, AI content humanization, and social engagement topic generation.
Create polished design artifacts as self-contained HTML — UI mockups, interactive prototypes, wireframes, landing pages, dashboards, app screens, mobile apps, and slide decks. Use this skill whenever the user wants to design, mock up, prototype, wireframe, or visualize any interface, screen, flow, or visual artifact — even when they don't say the word "design" (e.g. "build me a landing page", "show me what a settings screen could look like", "prototype an onboarding flow", "wireframe a few layout ideas", "make a pitch deck"). It drives a full design process: clarifying questions, design-context gathering, and production of one or more HTML deliverables. Runs on portable agent harnesses including Claude Code, Cursor, and Codex Agent — harness-specific tools are resolved from references/.
Extract false-positive and false-negative gaps from VLM binary-classification-question (BCQ, yes/no) predictions. Use after running VLM evaluation when you have a predictions JSON and need to identify failure cases for DEFT root cause analysis on a binary-classification VLM workflow.