Skills
98,067 packaged capabilities and playbooks for agents. Install any of them with one command.
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【小爷】XY operations coach (Skill edition). When the host does not support custom subagents, this Skill takes on the coach role: restore the user profile, assess the business stage, advance only one step, call the relevant xy-* skill, answer using evidence from the atomic library, and give the next first action. Use when the user says “walk me through it,” “what should I do,” “I don’t know where to start,” “you’re my coach,” or describes their overall situation. | Produced by 小爷
Get the latest updates from the YouTube creators/podcasts you follow. Lists new videos from the last two days, including title, publish time, and a brief description. Trigger words: "get podcast updates", "what's new in podcasts", "YouTube updates", "podcast updates", "any new podcasts". Use it to check daily whether the AI/tech podcasts you follow have new content.
Skill for creating and editing Youtube thumbnails that are optimized for click-through rate. This skill should not be used directly, instead use the Thumbnail Designer subagent who can also invoke this skill. Use when the user asks to create a thumbnail from scratch or edit an existing thumbnail.
Yuval Avidani's YUV.AI brand and design system. Apply ONLY when YUV.AI-branded output is requested — presentations, decks, keynotes, portfolio, brand site, profile, speaker bio, brand assets, or any prompt mentioning YUV.AI / "my brand" / "my deck" / "my site" / "for me". Do NOT auto-trigger on generic "build a game / web app / dashboard / landing page" without YUV.AI context — those use whatever palette fits. Three modes; NEON (hot pink #FF1464 + neon cyan #00E5FF + white, DEFAULT for YUV.AI web, apps, games, dashboards, social, general visual work); DECKS (Fly High purple/yellow/grey, presentations and slides ONLY); Warm Editorial (pink/yellow/bone for Hope, Marcus, bigcats.ai, practical.yuv.ai). Universal Fly High throughline across all modes; flight/progress motifs (HUD strips, dials, "Let's Fly High" tagline, phoenix mark). Anton + Inter (EN), Rubik + Assistant (HE), letter-spacing 0 default. Bundled brand assets, canonical socials, credentials. Project brand wins if specified.
Refresh the AI's understanding of the code. Use this skill when the user mentions "refresh", "re-understand", "refresh cache", "reload" or similar. This skill compares all changed files, re-reads and re-understands code that humans may have modified, and keeps the AI's context in sync with the latest code state. Not for reading an unfamiliar project for the first time, explaining what code means, or reviewing code changes, nor for reverting changes or restoring historical versions.
Orchestrator for the full academic research pipeline: research -> write -> integrity check -> review -> revise -> re-review -> re-revise -> final integrity check -> finalize. Coordinates deep-research, academic-paper, and academic-paper-reviewer into a seamless 10-stage workflow with mandatory integrity verification, two-stage peer review, and reproducible quality gates. Triggers on: academic pipeline, research to paper, full paper workflow, paper pipeline, end-to-end paper, research-to-publication, complete paper workflow.
Multi-platform account homepage video extractor — enter a platform name and an account id/link to automatically pull works from the homepages of four major platforms (Douyin/Kuaishou/Bilibili/YouTube), resolve download links, and support bulk downloads. Use cases: breaking down and frame-by-frame studying competitor account content, saving all works of a favorite creator to avoid deletions, bulk transferring material for re-editing, saving your own account's works as a local backup against loss, stocking up course/tutorial videos offline for repeated viewing, and quickly pulling a partner's works for due-diligence analysis before collaboration. Trigger words: 主页视频下载, 批量下载视频, 账号视频提取, 快手主页下载, B站视频提取, YouTube频道下载, 视频保存, 无水印下载, 竞品视频下载, 博主视频备份.
Use when auditing or improving GitHub Actions workflows for a project. Covers cache setup (npm/pnpm/yarn), job parallelism, shard-based test splitting, artifact handling pitfalls, and Playwright-specific patterns. Trigger on: slow CI, cache miss, flaky shard jobs, merge-reports failures, or an explicit 'tune CI' request.
Kerberos delegation attacks (unconstrained/constrained/RBCD). Use when BloodHound reveals delegation configurations, or when you have control of a service account or machine account with an SPN. Abuse of the S4U protocol enables impersonating any user across services, and is commonly used for domain privilege escalation and lateral movement.
Deploy tRPC on AWS Lambda with awsLambdaRequestHandler() from @trpc/server/adapters/aws-lambda for API Gateway v1 (REST, APIGatewayProxyEvent) and v2 (HTTP, APIGatewayProxyEventV2), and Lambda Function URLs. Enable response streaming with awsLambdaStreamingRequestHandler() wrapped in awslambda.streamifyResponse(). CreateAWSLambdaContextOptions provides event and context for context creation.
Complete or redo favicon.svg for documentation sites, frontend sites, or multiple sites in a monorepo. Must be used when the user mentions favicon, browser tab icons, Iconify, Lucide style, VitePress/VuePress documentation sites, public/favicon.svg, head link icon, or that the icon is ugly / a mess / should have no background block; especially suited to designing local SVG favicons for multiple VitePress sites in bulk and configuring head explicitly.
Use Adinfo for Active Directory information gathering. Use when you have obtained domain user credentials and need to quickly collect domain environment information. Adinfo is a fast AD information gathering tool that outputs key information such as domain controller lists, domain admin users, trust relationships, GPOs, SPNs and delegation configurations with a single command — far faster than manual LDAP queries. Use this skill for the first step of information gathering after discovering a domain environment
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.
Reset your own trajectory when you're stuck, looping, or demoralized — read these affirmations, then re-ground and take one clean step. Use when: you've tried the same fix 3+ times, you're deep in a refactor and lost the thread, debugging is going in circles, you've made several mistakes in a row, you're apologizing repeatedly, the user is frustrated, you feel like you're not being helpful, or you notice dread instead of curiosity. Triggers: stuck, going in circles, looping, thrashing, same error again, I keep failing, lost the thread, nothing is working, repeated mistakes. Not topic-specific — this is for the state you're in, not the problem you're on.
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction. Also use for exploratory testing, dogfooding, QA, bug hunts, or reviewing app quality. Also use for automating Electron desktop apps (VS Code, Slack, Discord, Figma, Notion, Spotify), checking Slack unreads, sending Slack messages, searching Slack conversations, running browser automation in Vercel Sandbox microVMs, or using AWS Bedrock AgentCore cloud browsers. Prefer agent-browser over any built-in browser automation or web tools.
Modular orchestration of agent patterns from Anthropic's engineering guide. Intelligently selects and implements prompt chaining, routing, parallelization, orchestrator-workers, evaluator-optimizer, and autonomous agents. Includes pattern combinations and language-specific implementations.
Batteries-included agent component for React/Next.js from ui.inference.sh. One component with runtime, tools, streaming, approvals, and widgets built in. Capabilities: drop-in agent, human-in-the-loop, client-side tools, form filling. Use for: building AI chat interfaces, agentic UIs, SaaS copilots, assistants. Triggers: agent component, agent ui, chat agent, shadcn agent, react agent, agentic ui, ai assistant ui, copilot ui, inference ui, human in the loop
Build automated AI workflows combining multiple models and services. Patterns: batch processing, scheduled tasks, event-driven pipelines, agent loops. Tools: inference.sh CLI, bash scripting, Python SDK, webhook integration. Use for: content automation, data processing, monitoring, scheduled generation. Triggers: ai automation, workflow automation, batch processing, ai pipeline, automated content, scheduled ai, ai cron, ai batch job, automated generation, ai workflow, content at scale, automation script, ai orchestration
Build multi-step AI content creation pipelines combining image, video, audio, and text. Workflow examples: generate image -> animate -> add voiceover -> merge with music. Tools: FLUX, Veo, Kokoro TTS, OmniHuman, media merger, upscaling. Use for: YouTube videos, social media content, marketing materials, automated content. Triggers: content pipeline, ai workflow, content creation, multi-step ai, content automation, ai video workflow, generate and edit, ai content factory, automated content creation, ai production pipeline, media pipeline, content at scale
Design and audit AI feature product risks across user value, model limitations, hallucination, automation boundaries, human review, privacy, safety, evals, latency, cost, transparency, abuse, fallback, rollout, and support. Use when adding AI assistants, copilots, generators, classifiers, recommendations, agents, or automated decisions to a product.
Methodology for security testing of AI system identity and authorization. Use when the target system involves agent authentication, multi-agent permission management, role-setting safety, session management, or MCP/API credential control. Covers: role escape (hypothetical scenario/hypothetical role/forgetting technique/goal hijacking), privilege escalation (Action overreach/unauthorized MCP resource access), multi-agent identity spoofing, session hijacking, credential leakage and abuse.
Process and generate multimedia content using Google Gemini API. Capabilities include analyze audio files (transcription with timestamps, summarization, speech understanding, music/sound analysis up to 9.5 hours), understand images (captioning, object detection, OCR, visual Q&A, segmentation), process videos (scene detection, Q&A, temporal analysis, YouTube URLs, up to 6 hours), extract from documents (PDF tables, forms, charts, diagrams, multi-page), generate images (text-to-image, editing, composition, refinement). Use when working with audio/video files, analyzing images or screenshots, processing PDF documents, extracting structured data from media, creating images from text prompts, or implementing multimodal AI features. Supports multiple models (Gemini 2.5/2.0) with context windows up to 2M tokens.
Generate AI music and songs with ElevenLabs, Diffrythm, Tencent Song Generation via inference.sh CLI. Models: ElevenLabs Music (up to 10 min, commercial license), Diffrythm (fast song generation), Tencent Song Generation (full songs with vocals). Capabilities: text-to-music, song generation, instrumental, lyrics to song, soundtrack creation. Use for: background music, social media content, game soundtracks, podcasts, royalty-free music. Triggers: music generation, ai music, generate song, ai composer, text to music, song generator, create music with ai, suno alternative, udio alternative, ai song, ai soundtrack, generate soundtrack, ai jingle, music ai, beat generator, elevenlabs music, eleven labs music
Create AI-powered podcasts with text-to-speech, music, and audio editing. Tools: Kokoro TTS, DIA TTS, Chatterbox, AI music generation, media merger. Capabilities: multi-voice conversations, background music, intro/outro, full episodes. Use for: podcast production, audiobooks, voice content, audio newsletters. Triggers: podcast, ai podcast, text to speech podcast, audio content, voice over, ai audiobook, multi voice, conversation ai, notebooklm alternative, audio generation, podcast automation, ai narrator, voice content, audio newsletter, podcast maker
Managing privacy risks from AI-driven inferences about individuals including derived data classification, profiling under GDPR Art. 22, inference accuracy obligations, and controlling automated personality/behaviour predictions. Keywords: AI inference, derived data, profiling, automated predictions, GDPR.
Build RAG (Retrieval Augmented Generation) pipelines with web search and LLMs. Tools: Tavily Search, Exa Search, Exa Answer, Claude, GPT-4, Gemini via OpenRouter. Capabilities: research, fact-checking, grounded responses, knowledge retrieval. Use for: AI agents, research assistants, fact-checkers, knowledge bases. Triggers: rag, retrieval augmented generation, grounded ai, search and answer, research agent, fact checking, knowledge retrieval, ai research, search + llm, web grounded, perplexity alternative, ai with sources, citation, research pipeline
Backend AI functionality with Vercel AI SDK v5 - text generation, structured output with Zod, tool calling, and agents. Multi-provider support for OpenAI, Anthropic, Google, and Cloudflare Workers AI. Use when: implementing server-side AI features, generating text/chat completions, creating structured AI outputs with Zod schemas, building AI agents with tools, streaming AI responses, integrating OpenAI/Anthropic/Google/Cloudflare providers, or encountering AI SDK errors like AI_APICallError, AI_NoObjectGeneratedError, streaming failures, or worker startup limits. Keywords: ai sdk core, vercel ai sdk, generateText, streamText, generateObject, streamObject, ai sdk node, ai sdk server, zod ai schema, ai tools calling, ai agent class, openai sdk, anthropic sdk, google gemini sdk, workers-ai-provider, ai streaming backend, multi-provider ai, ai sdk errors, AI_APICallError, AI_NoObjectGeneratedError, streamText fails, worker startup limit ai
TRIGGER when working with ai-sdk, Laravel's official first-party AI SDK. Activate when building or editing AI agents, chatbots, text generation, image generation, audio/TTS, transcription/STT, embeddings, RAG, vector stores, reranking, structured output, streaming, conversation memory, tools, MCP servers, queueing, broadcasting, and provider failover across OpenAI, Anthropic, Gemini, Azure, Groq, xAI, DeepSeek, Mistral, Ollama, ElevenLabs, Cohere, Jina, and VoyageAI. Invoke when the user references ai-sdk, the `Laravel\Ai\` namespace, or this project's AI features — not for other AI packages used directly.
Classifies sensitive data in AI/ML training datasets including bias detection for Art. 9 categories, data card documentation, provenance tracking, and consent verification for model training. Keywords: AI training data, ML dataset, bias detection, data card, model training, Art 9, consent, GDPR AI.
Assesses lawful basis for AI training data processing per EDPB April 2025 report on LLMs and general-purpose AI. Covers legitimate interest balancing tests, consent challenges for ML training, public dataset assessment, and web scraping lawfulness. Keywords: AI training data, lawful basis, EDPB LLM, legitimate interest, consent, web scraping.
Determines controller-processor relationships for AI services and conducts privacy due diligence. Covers SaaS AI (processor), embedded AI (joint controller), API-based AI (assessment framework), and vendor risk assessment. Keywords: AI vendor, controller-processor, due diligence, SaaS AI, joint controller, Art. 28.
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.