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archetypeai-wifi-demo
archetypeai-wifi-demo contient 16 skills collectées depuis archetypeai, avec une couverture métier par dépôt et des pages de détail sur le site.
Skills dans ce dépôt
Apply DS tokens, components, and patterns to an existing demo initialized with ds-cli init.
Creates composite UI patterns by assembling design system primitives. Use when building reusable components that combine multiple primitives (Card, Button, Input, etc.), creating dashboard widgets, form groups, sensor cards, data displays, or any complex component from existing design system primitives. Also use when the user asks to create a "component" or "widget" that should follow design system conventions.
Scaffolds a full-viewport dashboard layout with no scrolling, a branded menubar with the Archetype AI logo, and panel-based content areas. Use when creating a dashboard UI, building a full-screen layout, setting up a monitoring view, creating a control panel, or when the user asks for a "dashboard", "full-screen layout", "no-scroll UI", or "panel layout".
Deploys a SvelteKit project to Cloudflare Workers with CI/CD auto-deploy on merge to main. Use when deploying a project, setting up wrangler configuration, running a local worker dev server, managing secrets, configuring environments, or when the user mentions "deploy", "cloudflare", "worker", "wrangler", or "production".
Run an Embedding Lens by streaming sensor data from a CSV file. Use when extracting embeddings from time-series CSV data for visualization, clustering, dimensionality reduction, or similarity analysis.
Run an Embedding Lens by streaming real-time data from a physical sensor (BLE, USB, UDP, or recording playback). Use when extracting live embeddings from sensor hardware for real-time visualization or clustering.
Run an Embedding Lens by uploading a CSV file for server-side processing. Use when you want to upload a file and get embeddings without local streaming.
Audits and fixes accessibility issues in projects using shadcn-svelte and the Archetype AI design system. Use when running an a11y audit, fixing WCAG violations, adding aria labels, improving keyboard navigation, fixing focus management, adding screen reader support, or when the user mentions "accessibility", "a11y", "aria", "screen reader", or "keyboard navigation".
Updates a SvelteKit project's metadata including page titles, favicons, meta descriptions, Open Graph tags, and SEO tags. Use when updating the favicon, setting page titles, adding OG tags, fixing SEO metadata, branding a project's tab/title, or when the user mentions "metadata", "favicon", "page title", "OG tags", or "SEO".
Analyze uploaded video files using Newton's activity monitor lens. Server reads the video via video_file_reader and streams results via SSE. Use for batch video analysis, activity detection, or temporal event extraction from video files. NOT for live webcam — use /camera-frame-analysis for that.
Live webcam frame analysis using Newton's vision model via model.query (request/response). Captures frames from a webcam as base64 JPEG and sends them to Newton. Use for live camera analysis, scene description, presence detection, or visual Q&A. NOT for video file uploads — use /activity-monitor-lens-on-video for that.
Simple direct query to Newton model using the /query API endpoint. Test API connectivity, run text queries, or post-process results from other lenses. No lens registration or session needed.
Run a Machine State Lens by streaming sensor data from a CSV file. Use when analyzing time-series CSV data for machine state classification, anomaly detection, or n-shot state recognition from files.
Run a Machine State Lens by streaming real-time data from a physical sensor (BLE, USB, UDP, or recording playback). Use when doing real-time machine state classification from live sensor hardware.
Run a Machine State Lens by uploading a CSV file for server-side processing. Use when you want to upload a file and let the server handle streaming (no local streaming loop needed).
Sets up data visualizations using layerchart and the Chart primitive. Use when creating line charts, scatter plots, area charts, time series visualizations, sensor displays, embedding plots, streaming data charts, or any data visualization component. Also use when the user asks about charting, graphing, plotting data, visualizing metrics, displaying real-time sensor data, or showing scatter/cluster plots.