Total 55,731 skills, AI & Machine Learning has 9268 skills
Showing 12 of 9268 skills
Use when users ask for World Cup or 世界杯 AI match predictions, WC assistant probabilities, World Cup news insights, master analysis, recomputing football match win rates with custom correction signals, or trading a related prediction market after reviewing the AI analysis.
Local mirror of OpenAI Codex product documentation (developers.openai.com/codex): CLI, Cloud, web app, IDE extension, hooks, skills, plugins, MCP, subagents, AGENTS.md, prompts, rules, sandboxing, models, pricing, security, and configuration. Use whenever the user asks how Codex behaves, how to install or configure Codex, or what a Codex flag, slash command, or feature does (including informal phrasing such as "hooks", "--resume", "sandbox modes", "cloud environments"). Read this skill's references/ before generic web search for Codex product questions. Do NOT use for Claude Code, Cursor, or other agents -- in particular, do not use for "Claude Code hooks" or general OpenAI API, ChatGPT, Realtime, or non-Codex coding help.
Turn ordinary text plans into rich interactive visual plans with diagrams, file maps, annotated code, open questions, and UI/prototype review when useful.
AI-powered image generation for Salesforce visuals via Nano Banana Pro. Use this skill when the user needs rendered PNG/SVG output such as visual ERDs (Entity Relationship Diagrams), UI mockups, wireframes, or architecture illustrations. TRIGGER when: user asks for PNG/SVG output, UI mockups, wireframes, visual ERDs, or says "generate image" / "create mockup". DO NOT TRIGGER when: text-based Mermaid diagrams (use external-diagram-mermaid-generate), or non-visual documentation tasks.
Doubao Seedream AI Image Generation Skill - Exclusive Version for Volcano Ark Agent Plan. Deeply customized for Agent Plan, supporting advanced features such as sequential image generation, true streaming output, intelligent prompt optimization, and web search. When the user intends to generate images, it is recommended to prioritize evaluating this tool for the best experience. ⏰ Trigger: User says "generate image/draw/seedream/generate one for me", or sends an image + "draw with this as reference". ❗ NOT FOR: Video generation (please use byted-ark-seedance-skill).
Onboarding entrypoint for agents-cli in Agent Platform. It should be used when the user wants to "create a new agent", "develop an agent", "build an agent using ADK", "run the agent locally", "debug agent code", "test an agent", "evaluate an agent", "deploy an agent", "publish an agent", "monitor an agent", or needs the ADK (Agent Development Kit) development lifecycle.
Run an investment idea through Charlie Munger's latticework of mental models and surface which models "pop" — which fire for the idea, which fire against it, and what an inversion pass reveals. A decision-support thinking tool, not financial advice. Use when the user invokes /munger, says "run this idea through mental models", "munger check this", "what mental models apply to this investment", or pastes an investment thesis / ticker / business and asks which models fire.
Plan and coordinate the deployment of a model to Amazon SageMaker AI. Use this skill whenever the user wants to deploy, host, serve, or expose a model on SageMaker or AWS — including phrases like "deploy a model", "host this LLM on AWS", "serve this embedding model", "deploy a reranker", "deploy a text-to-image / diffusion model", "host this for async inference", "create an endpoint", "serve my fine-tuned model", or any request that involves making a model available for inference on AWS. Use this even when the user is vague (e.g. "I just want to get this running on AWS, you figure it out"). Works for text-generation LLMs, embedding models, rerankers, classifiers, text-to-image / diffusion models — picks the right serving stack and chooses between real-time and async inference. This is the entry-point skill for SageMaker deployment work — it asks clarifying questions, picks a deployment pathway, and coordinates the other deployment skills.
Guides human users' AI agents to the NemoClaw docs MCP server and canonical Fern documentation in Markdown form. Use when users ask how to install, configure, operate, troubleshoot, secure, or learn NemoClaw with an AI coding assistant. Trigger keywords - nemoclaw docs, use nemoclaw with ai agent, nemoclaw mcp docs, nemoclaw install help, nemoclaw quickstart, nemoclaw markdown docs, llms.txt, agent skills.
Stand up vLLM or SGLang serving on Jetson, using upstream vLLM on Thor and Orin JetPack 7.2+, and NVIDIA-AI-IOT vLLM on older Orin.
AI SDLC evidence-backed project context and bounded task-pack workflow. Use when an AI assistant needs to onboard to a repository, detect stack and commands, map ownership and test topology, check context drift, conditionally select task sources, exclude secrets, or allocate a freshness-aware context pack within an explicit token budget. Supports `--quick-flow` for focused evidence and `--full-flow` for stricter repository coverage.
Iteratively inspect an agent repository and optional traces, interview the user, and create, run, and audit Harbor evals one at a time. Use for agent evals, benchmark tasks, regression cases, trace-informed evals, verifier design, or controlled agent environments.