Total 56,605 skills, AI & Machine Learning has 9428 skills
Showing 12 of 9428 skills
Provides active execution protocols to rigorously audit how code, directory structures, and agent actions comply with the authoritative ecosystem specs. Trigger when validating new skills, plugins, or workflows.
Generate audio visualization videos using each::sense AI. Create waveforms, spectrum analyzers, particle effects, 3D visualizations, and beat-synced animations from audio files.
News briefing. Use this skill whenever the user asks for recent news or headlines. Trigger phrases include: what happened recently, today's highlights, crypto news, any new updates. MCP tools: news_events_get_latest_events, news_feed_search_news, news_feed_get_social_sentiment.
Build and deploy agentic finance applications on the Alva platform. Access 250+ financial data sources (crypto, equities, macro, on-chain, social), run cloud-side analytics, backtest trading strategies, and release interactive playbooks -- all from your AI agents.
Create explainer videos with narration and AI-generated visuals. Triggers on: "解说视频", "explainer video", "explain this as a video", "tutorial video", "introduce X (video)", "解释一下XX（视频形式）".
Execute use when provisioning Vertex AI ADK infrastructure with Terraform. Trigger with phrases like "deploy ADK terraform", "agent engine infrastructure", "provision ADK agent", "vertex AI agent terraform", or "code execution sandbox terraform". Provisions Agent Engine runtime, 14-day code execution sandbox, Memory Bank, VPC Service Controls, IAM roles, and secure multi-agent infrastructure.
Full autonomous engineering workflow using swarm mode for parallel execution
AgentMail MCP server for email tools in AI assistants. Use when setting up AgentMail with Claude Desktop, Cursor, VS Code, Windsurf, or other MCP-compatible clients. Provides tools for inbox management, sending/receiving emails, and thread handling.
Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature.
Package and build custom AI models with Cog for deployment on Replicate. Use when creating a cog.yaml or predict.py, defining model inputs and outputs, loading model weights at setup time, building Docker images for ML models, serving locally with cog serve or cog predict, or porting a HuggingFace, GitHub, or ComfyUI model to run on Replicate. Trigger on phrases like "build a model", "package a model", "create a Cog model", "wrap a model", "containerize an AI model", "predict.py", "cog.yaml", "BasePredictor", or "Cog container", and when referencing cog.run, github.com/replicate/cog, or github.com/replicate/cog-examples. Covers GPU and CUDA setup, pget for fast weight downloads, async predictors with continuous batching, streaming outputs, and cold-boot optimization for image, video, audio, and LLM models. For pushing built models to Replicate, see publish-models. For running existing models, see run-models.
Video generation and transcription workflows via the Venice.ai API.
Generate AI sound effects from text descriptions with ElevenLabs via inference.sh CLI. Capabilities: text-to-sound-effect, custom duration, royalty-free audio. Use for: video production, game audio, podcasts, films, presentations, social media. Triggers: sound effects, sfx, sound generation, ai sound effects, generate sound, foley, audio effects, sound design, text to sound, elevenlabs sound, eleven labs sfx, ambient sound, cinematic sound, game sound effects