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Found 59 Skills
Carto integration. Manage data, records, and automate workflows. Use when the user wants to interact with Carto data.
Convert a photo of a person into a Pixar-style 3D cartoon character, then animate it using a reference dance or motion video.
Generate a working geospatial app powered by CARTO and deck.gl — basemap, layers (vector / H3 / quadbin / raster), widgets, filters, legend, inputs, optional chat-with-map agent, and the right auth strategy (public token, OAuth, SSO, or M2M).
Maps and documents codebases of any size by orchestrating parallel subagents. Creates docs/CODEBASE_MAP.md with architecture, file purposes, dependencies, and navigation guides. Updates CLAUDE.md with a summary. Use when user says "map this codebase", "cartographer", "/cartographer", "create codebase map", "document the architecture", "understand this codebase", or when onboarding to a new project. Automatically detects if map exists and updates only changed sections.
Codebase mapping and documentation using parallel AI subagents. Invoke for: map this codebase, document architecture, understand codebase, onboarding to new project, create CODEBASE_MAP.md, generate architecture diagrams.
Preview an existing saved CARTO Builder map inline in the chat via the CARTO MCP server's load_builder_map tool. Use whenever the user references a saved Builder map — by URL, by ID, or by name (resolved via list_maps first). Renders a lightweight read-only preview (layers, basemap, viewport, popups, legend). Widgets, SQL parameters, map description, and other Builder-only features are NOT included; the user can click "Open in Builder" for the full experience. Triggers on "show me the X map", "open the Y map", "preview the Z map", and post-CLI-creation inline previews of a freshly-created map. Distinct from carto-create-builder-maps (CLI authoring), carto-render-inline-map (ad-hoc deck.gl spec), and carto-develop-app (developer app).
Builds routing and origin-destination analysis workflows in CARTO. Triggers when the user mentions routing, route calculation, travel time, travel distance, OD matrix, origin-destination, isoline, isochrone, isodistance, catchment area, reachable area, drive time polygon, walk time polygon, service area, accessibility analysis, travel time matrix, distance matrix, commute patterns, trip flow, OD flow, mobility patterns, taxi trips, ride patterns, route geometry, shortest path, network distance, or wants to compute routes, generate isolines, build travel matrices, or analyze movement patterns between origins and destinations.
Generate visual concept maps, flowcharts, architecture diagrams, and relationship diagrams from structured notes or technical content using Mermaid syntax. Use when the user has lecture notes, study materials, or technical documentation and wants visual diagrams to aid understanding. Produces multiple diagram types: concept hierarchy maps, process flowcharts, architecture diagrams, comparison matrices, timeline diagrams, and mind maps. Trigger phrases: 'create diagrams from notes', 'visualize concepts', 'concept map', 'make flowcharts', 'diagram this', 'visual notes'.
Expert guidance on map design principles, color theory, visual hierarchy, typography, and cartographic best practices for creating effective and beautiful maps with Mapbox. Use when designing map styles, choosing colors, or making cartographic decisions.
Discover and subscribe to external spatial datasets via CARTO Data Observatory and partner catalogs.
Import geospatial files into the data warehouse via CARTO, export results back out, and prepare tilesets for fast map rendering.
Builds Moran's I spatial autocorrelation workflows in CARTO. Triggers when the user mentions spatial autocorrelation, Moran's I, spatial dependency, spatial correlation, spatial outliers, HH HL LH LL quadrants, high-high clusters, low-low clusters, spatial weight matrix, "is there clustering", "are values spatially correlated", local indicators of spatial association, LISA, spatial randomness test, or wants to determine whether a variable exhibits spatial clustering, dispersion, or randomness across a gridded dataset. Also relevant when the user needs to classify locations into cluster types (HH, HL, LH, LL) rather than just identifying hotspots and coldspots.