Total 57,445 skills, AI & Machine Learning has 9558 skills
Showing 12 of 9558 skills
Put the USER into a ~45s Japanese-anime football short as the hero — from their photo + their favorite team + the opponent. Anime-fies the user's face into a consistent character sheet, designs a dramatic 3-act match (come on → equalizer → winner) with the user scoring, writes three 15s cel-shaded scene prompts (CAPS names + Japanese dialogue), generates them on Seedance off the sheets, and stitches them. A Japanese-anime football short built on the Pika MCP, but the star is YOU. Triggers: "/anime-soccer", "put me in an anime soccer video", "make me the anime football hero", "anime match with my photo". Requires the Pika MCP.
阿里云百炼托管 Agent 声明式基础设施入口：用户要创建agent、初始化 agents.yaml、校验或预览 agent 配置变更、 创建/更新/销毁百炼托管 Agent、和托管 agent 对话、查会话事件历史、导入或取消跟踪远端资源时使用 `bl managed-agent`。以 agents.yaml 为唯一事实源做 IaC：init 建脚手架、validate 离线校验、plan 预览 diff、 apply / destroy 变更远端资源且必须带 `--yes`，务必先 plan 给用户看 diff 再让其确认。 反触发：调用已上线的百炼应用/智能体走 bailian-app-call 或 `bl app`；宿主 agent 自身的记忆、技能、 子代理不走本 skill；生图生视频走 bailian-gen。 官方安装：`npx skills add modelstudioai/cli --all -g`（与共享协议 bailian-protocol 同装）。
Dynamic Apps: Deploy an AI-generated backend for every user.
Designs, builds, and deploys AI agents or multi-agent systems on Google Cloud. Provides an interactive workflow to gather requirements, recommend a tailored architecture, and generate deployment instructions. Use when designing or implementing agentic systems on Google Cloud. Don't use for general Google Cloud solution architecture (use google-cloud-solution-architecture instead) or for narrow tasks targeting a single product without agent context.
Discovers requirements, and generates architectural, design, and deployment guidance for a retrieval-augmented generation (RAG)-capable enterprise search system in Google Cloud. Use when users need a vector-enabled SQL database as the store and index for the embedding vectors, an open model and open-source inferencing framework, and Kubernetes containers to host all the application components. DON'T use this skill for fully-managed RAG, or SaaS search services, or when a non-SQL vector database is required.
사용자가 지정한 상위 모델을 Advisor로 세워 현재 작업의 결정점에서 컨설트한다. 접근 확정 전 검토, 완료 선언 전 검증, 막힘 진단에 쓴다. advisor 모델은 디폴트 없이 호출 시 사용자가 직접 지정하며, 미지정이면 동작하지 않는다. 사용자가 /advisor-strategy로 호출한 경우에만 실행한다.
Add AI navigation in Unity 6: bake a NavMesh with the AI Navigation package (NavMeshSurface), move agents with NavMeshAgent.SetDestination, and handle dynamic obstacles. Use when setting up pathfinding, making an enemy chase the player, baking navigation, or when the user mentions NavMesh, NavMeshAgent, NavMeshSurface, NavMeshObstacle, or Unity pathfinding.
Run fable-mode execution discipline on Claude Opus — the strongest staged run available. Routes the task to the @fable-orchestrator agent (Opus, Write-less), which stages the work, delegates artifact production to @fable-worker-sonnet / @fable-worker-haiku, and cold-checks deliverables with @fable-verifier. Trigger when the user explicitly asks for thorough/systematic/"deep work" handling on the strongest model ("fable on opus", "stage this on opus", "deep work mode, opus"). Do NOT use for ordinary single-pass tasks — and prefer fable-sonnet or fable-haiku when the task doesn't need peak reasoning.
Guides the migration of existing AI workloads (Cloud Run, Gemini API, Gemini Enterprise Agent Platform) to self-hosted GKE inference using gcloud and kubectl. Use when the user has an existing AI inference workload (on Cloud Run, the Gemini API, Gemini Enterprise Agent Platform, or a custom VM) and wants to move it to self-hosted inference on GKE, or asks follow-up questions during such a migration (hardware sizing, model staging, manifest generation, validation, traffic cutover). DO NOT use for brand new GKE inference deployments with no existing workload to migrate (use gke-inference instead). DO NOT use if the user intends to automate the migration via the Gemini Cloud Assist MCP server.
agentOS: Agent execution, filesystems, and orchestration.
Use to summarize a recorded video via the LVS summarization microservice (HITL-gated) with a VLM fallback. Not for live RTSP captioning or incident-range reports.
Runs the DEFT embed-then-mine workflow for VCN AOI iterations — embeds the gap-analysis target parquet, embeds a source pool, and mines nearest-neighbour source images for downstream augmentation. Use as the immediate next step after `tao-route-visual-changenet-samples` when expanding a real-image augmentation queue from the mining subset.