Total 55,943 skills, AI & Machine Learning has 9312 skills
Showing 12 of 9312 skills
Use this skill when you receive a 402 Payment Required response that contains an `agentkit` extension. Covers checking 402 responses for the AgentKit extension before paying, constructing and signing a CAIP-122 challenge (SIWE for EVM, SIWS for Solana), sending the signed `agentkit` HTTP header, and interpreting access modes (free, free-trial, discount). Supports both EOA wallets (EIP-191) and Smart Contract Wallets (ERC-1271, e.g. Coinbase Smart Wallet, Safe).
Real-time and streaming AI image generation — instant results for interactive use. Use when the user requests "Real-time generation", "Fast generation", "Streaming image", "Instant image", "Live generation", "Realtime".
Enforces spec-before-code workflow for AI-driven development. Automatically selects Spec-Kit or OpenSpec mode, triages complexity (quick/standard/thorough), recovers session context, and applies quality gates (G0-G4) with automated review loops at every stage. Use this skill whenever the user says "/super-spec", "spec first", "规范先行", or starts any feature, bugfix, or refactor — especially in projects with .spec-mode, .specify/, or openspec/ directories. Even if the user doesn't explicitly ask for spec-driven workflow, activate this skill for any non-trivial code change to prevent skipping the design phase. Orchestrates: Spec-Kit/OpenSpec (OPSX) + planning-with-files + ui-ux-pro-max (v2.0, 67 styles, 161 palettes, 13 stacks) + Superpowers (TDD, code review, verification, debugging, spec/plan review loops, subagent model selection).
Coaches end-to-end ML system design interviews covering inference pipelines, recommendation systems, RAG, feature stores, and monitoring. Use for L6+ design rounds, ML architecture whiteboarding, system design practice, serving tradeoff analysis. Activate on "ML system design", "ML interview", "recommendation system design", "RAG architecture", "feature store design", "model serving". NOT for coding interviews, behavioral questions, ML theory quizzes, or paper implementations.
Create professional videos autonomously using claude-code-video-toolkit — AI voiceovers, image generation, music, talking heads, and Remotion rendering.
This skill should be used when the user asks to "run a tracking cycle", "measure AI visibility", "check share of voice", "run Morphiq Track", "track citations", "check GEO score", "generate prompts", "run content creation workflow", or mentions monitoring LLM mentions, running content creation workflows, measuring brand visibility, or generating query fanout content. Queries multiple LLM providers, produces delta reports, and maintains MORPHIQ-TRACKER.md as the persistent state file for the entire pipeline.
Interact with Google NotebookLM notebooks — chat with the AI, generate artifacts (slides, audio, video, mind maps, quizzes, flashcards, infographics, reports, data tables), manage sources (add URLs, YouTube, files, text), run research (fast/deep web research), and manage notes. Use when the user wants to query, create content from, or manage their NotebookLM notebooks and sources.
Solve competition math problems (IMO, Putnam, USAMO, AIME) with adversarial verification that catches the errors self-verification misses. Activates when asked to 'solve this IMO problem', 'prove this olympiad inequality', 'verify this competition proof', 'find a counterexample', 'is this proof correct', or for any problem with 'IMO', 'Putnam', 'USAMO', 'olympiad', or 'competition math' in it. Uses pure reasoning (no tools) — then a fresh-context adversarial verifier attacks the proof using specific failure patterns, not generic 'check logic'. Outputs calibrated confidence — will say 'no confident solution' rather than bluff. If LaTeX is available, produces a clean PDF after verification passes.
AnyCap CLI -- capability runtime for AI agents. One CLI for image generation, image read, video analysis, audio analysis, music composition, text-to-speech, web search, web crawling, file download, static site hosting, and cloud file storage. Use when the agent needs to generate images, analyze images, video, or audio, produce audio/music, search or crawl the web, download remote files, deploy static sites, or store and share files. Also use when the agent needs to authenticate with AnyCap (login, API key, credentials), or when encountering errors from AnyCap to submit feedback via 'anycap feedback'. Trigger on mentions of AnyCap, multimodal capabilities, AI-generated media, page hosting, or drive storage.
Different techniques to optimize the performance of Qdrant, including indexing strategies, query optimization, and hardware considerations. Use when you want to improve the speed and efficiency of your Qdrant deployment.
Generate high-quality images from text prompts using Volcano Engine Seedream models. Supports multiple artistic styles and aspect ratios. Use this skill when users want to create images from text descriptions, generate artwork in various styles, create visual content for creative projects, or need AI-powered image generation capabilities.
Use when creating a new beo skill, editing an existing beo skill, or pressure-testing a beo skill before deployment. This skill should win whenever the task is to make a beo skill robust against rationalization, misuse, or failure under pressure. Do not use it for project-specific AGENTS.md conventions, one-off solutions, or ordinary feature planning.