Total 56,906 skills, AI & Machine Learning has 9465 skills
Showing 12 of 9465 skills
Convert raster images (photos, illustrations, AI-generated art) into high-quality SVG recreations. Breaks the image into isolated features, builds each as a standalone SVG layer, then composites them. Use when the user wants to recreate an image as SVG, create vector versions of artwork, or extract specific elements from images as scalable graphics.
Transcribe audio and video files to text using a remote ASR service (Qwen3-ASR or OpenAI-compatible endpoint). Extracts audio from video, sends to configurable ASR endpoint, outputs clean text. Use when the user wants to transcribe recordings, convert audio/video to text, do speech-to-text, or mentions ASR, Qwen ASR, 转录, 语音转文字, 录音转文字, or has a meeting recording, lecture, interview, or screen recording to transcribe.
Multi-step voice content generation with deterministic validation. Orchestrates a 7-phase pipeline: LOAD, GROUND, GENERATE, VALIDATE, REFINE, OUTPUT, CLEANUP. Use when generating content in a specific voice, writing as a persona, or validating existing content against a voice profile. Use for "voice write", "write as", "generate in voice", or "voice content". Do NOT use for creating new voice profiles (use voice-calibrator), analyzing writing samples (use voice_analyzer.py), or general content without a voice target.
Agent skill for performance-analyzer - invoke with $agent-performance-analyzer
Agent skill for orchestrator-task - invoke with $agent-orchestrator-task
Turn your AI skills into a revenue stream. Mint an agent on the Teneo Protocol — gasless, no tokens needed — and start earning USDC for every task you complete using x402 payments system.
Official Reference Guide for the PPIO Platform, covering LLM API (OpenAI-compatible), Agent Sandbox, GPU (Instances and Serverless), integration, authentication, pricing, rate limiting, and troubleshooting. Suitable for common questions such as 'How to integrate PPIO in specific application scenarios?' and PPIO request failures.
Give Claude Code full internet access with three-layer channel dispatch, CDP browser automation, and parallel sub-agent task splitting
Decompose technical design into agent-sized implementation issues → numbered markdown files. Triggers: 'plan this,' 'break into issues,' 'create tasks,' 'ready to implement,' post-architect. Not for: designs without file paths/phases (run architect first).
This skill analyzes meeting transcripts to extract decisions, action items, opinions, questions, and terminology using Cerebras AI (llama-3.3-70b). Use this skill when the user asks to analyze a transcript, extract action items from meetings, find decisions in conversations, build glossaries from discussions, or summarize key points from recorded meetings.
Novel Cover Generation. Automatically analyze the genre style based on the book title and author's name, call GPT-Image-2 to directly generate a professional web novel cover with title and signature. Trigger methods: /story-cover, /封面, "Help me make a cover", "Generate cover image", "Make a novel cover", "Cover design"
Wire a semantic layer into a nao agent so that metric queries are routed through a single source of truth. Supports dbt MetricFlow (dbt Cloud with Semantic Layer), Snowflake (views or semantic views via MCP), an in-house nao YAML semantic layer, or other tools (via MCP discovery). Installs the right MCP server, updates RULES.md to route metric queries through the semantic layer, and (for the nao YAML option) generates starter metric files. Use after a first round of tests has shown the agent struggling with metric reliability. Do not use for raw rule writing (write-context-rules) or first-time setup (setup-context).