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Found 1,991 Skills
Complete Hindsight documentation for AI agents. Use this to learn about Hindsight architecture, APIs, configuration, and best practices.
Helps deploying VoltDB cluster on Kubernetes. Use when user wants to create scripts creating clusters on Kubernetes with Volt's releases. Use when user asks to create terraform, helmfile or helm scripts. Use when user want to create configuration as code.
Bun as runtime, package manager, bundler, and test runner. When to choose Bun vs Node, migration notes, and Vercel support.
Deploy, discover, and invoke trusted micro-apps. Built-in discovery, trust scoring, and payments.
Use to call the VIOS REST API (sensor list, timelines, clip extraction, snapshots, add/delete sensors and streams). Not for VLM inference or search.
Build and publish a Gradio demo on Hugging Face Spaces for a user-provided LoRA. Use when someone asks to create, generate, ship, or publish a Space, demo, Gradio app, or playground for a LoRA — including LoRAs for Qwen-Image, Qwen-Image-Edit, LTX-Video, Wan, FLUX, SDXL, or other diffusion base models. Also triggers when someone describes a LoRA they trained or hosts on the Hub and wants to share it. Covers picking the right base pipeline and `diffusers` inference recipe, designing a UI tailored to the LoRA's task and inputs (Union/multi-task control, edit, video, image, etc.), respecting model-card recommendations (trigger words, steps, guidance, LoRA scale, example inputs), and shipping to ZeroGPU hardware as a private Space by default.
Define an entire Cargo workspace in code — connectors, models, plays, tools, agents, MCP servers, context, capacities, territories, segments, folders, files, workers, apps — and deploy it declaratively with `cargo-ai cdk` (init → types → plan → deploy), the way you'd manage cloud infra with Pulumi or the AWS CDK. Use when the user wants to manage Cargo resources as code: reproducibly, version-controlled, in git, from a template, or across environments. Routes to authoring/deploy/typing guides (Level 2), recipes (Level 2.5), and references. For one-off imperative operations (create one connector, read a model, run a workflow), use the matching capability skill instead.
Set up Prometheus for comprehensive metric collection, storage, and monitoring of infrastructure and applications. Use when implementing metrics collection, setting up monitoring infrastructure, or configuring alerting systems.
Serverless GPU cloud platform for running ML workloads. Use when you need on-demand GPU access without infrastructure management, deploying ML models as APIs, or running batch jobs with automatic scaling.
Deploy and manage relational databases using RDS with Multi-AZ, read replicas, backups, and encryption. Use for PostgreSQL, MySQL, MariaDB, and Oracle.
N8N Documentation - Workflow automation platform with AI capabilities
Expert-level Node.js backend development with Express, async patterns, streams, performance optimization, and production best practices