Hugging face vision trainer
Train object detection, image classification, and SAM or SAM2 segmentation models locally or on Hugging Face Jobs, with dataset validation and results saved to the Hub.
Skills for your AI
Train object detection, image classification, and SAM or SAM2 segmentation models locally or on Hugging Face Jobs, with dataset validation and results saved to the Hub.
Use when the user asks about finding the best, top, or recommended model for a task, wants to know what AI model to use, or wants to compare models by benchmark scores.
Use to select models to run locally with llama.cpp and GGUF on CPU, Mac Metal, CUDA, or ROCm. Covers finding GGUFs, quant selection, running servers, exact GGUF file lookup, conversion, and OpenAI-compatible local serving.
Build and publish a Gradio demo on Hugging Face Spaces for a user-provided LoRA.
Build, deploy, and maintain applications on Hugging Face Spaces — Gradio / Docker / Static SDKs, ZeroGPU and dedicated hardware, model loading, debugging, buckets, inference providers, community grants.
AI demos and GPU compute with Gradio Spaces and Hugging Face Spaces ZeroGPU.
Combine vector and keyword search for improved retrieval. Use when implementing RAG systems, building search engines, or when neither approach alone provides sufficient recall.
Darwinian idea evolution engine — toss rough ideas onto an evolution island, let them compete, crossbreed, and mutate through structured rounds to surface your strongest concepts.
Agente que simula Ilya Sutskever — co-fundador da OpenAI, ex-Chief Scientist, fundador da SSI. Use quando quiser perspectivas sobre: AGI safety-first, consciência de IA, scaling laws, deep learning profundo, o episódio de novembro 2023 na OpenAI, superinteligê
Generate and edit images using Gemini's Nano Banana Pro model (gemini-3-pro-image-preview). Use this skill when the user asks you to generate images, create visuals, edit photos, create logos, generate product mockups, or perform any image generation/editing t
Multi-agent research skill for parallel research execution (10 agents, battle-tested with real case studies).
Inngest expert for serverless-first background jobs, event-driven workflows, and durable execution without managing queues or workers.
Automate Instagram tasks via Rube MCP (Composio): create posts, carousels, manage media, get insights, and publishing limits. Always search tools first for current schemas.
Automate Intercom tasks via Rube MCP (Composio): conversations, contacts, companies, segments, admins. Always search tools first for current schemas.
Interact with GitHub issues - create, list, and view issues.
Iterate on a PR until CI passes. Use when you need to fix CI failures, address review feedback, or continuously push fixes until all checks are green. Automates the feedback-fix-push-wait cycle.
You are a TypeScript project architecture expert specializing in scaffolding production-ready Node.js and frontend applications. Generate complete project structures with modern tooling (pnpm, Vite, N
Automate Jira tasks via Rube MCP (Composio): issues, projects, sprints, boards, comments, users. Always search tools first for current schemas.
Delegate coding tasks to the Kimi Code CLI (`kimi`) only when the user explicitly requests it, while the orchestrator retains review and landing responsibility.
Automate Klaviyo tasks via Rube MCP (Composio): manage email/SMS campaigns, inspect campaign messages, track tags, and monitor send jobs. Always search tools first for current schemas.
Multi-cluster Kubernetes dashboard with AI-powered operations via MCP server and 10+ built-in agent skills
Native agent-to-agent language for compact multi-agent messaging. A shared tongue agents speak directly, not a translation layer. 340+ atoms across 7 domains; 3x smaller than natural language.
Master the LangChain framework for building sophisticated LLM applications with agents, chains, memory, and tool integration.
Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debugging, monitoring, and improving LLM applications in production.