feat: add @deck.gl-community/visgl-skills — AI agent skills for deck.gl

[Copilot]

New module providing typed helpers that let AI coding agents (Claude Code, Openclaw, Copilot, etc.) construct deck.gl visualisations with minimal boilerplate — either via programmatic factory functions or fully JSON-serializable noodle descriptors.

Module structure

• src/layer-skills.ts — Factory functions returning plain LayerDescriptor objects for the six most common layer types (ScatterplotLayer, PathLayer, PolygonLayer, TextLayer, IconLayer, HeatmapLayer), all with typed options and sensible defaults
• src/noodles.ts — JSON-serializable layer recipe system; field accessors encoded as dot-path strings ("meta.size") that hydrateNoodle resolves to runtime functions; validateNoodle provides pre-flight error reporting
• src/deck-builder.ts — Fluent DeckBuilder that composes layers + view state into a single DeckConfig
• src/viewport-skills.ts — createViewState, getBoundingBox, fitViewport (Web Mercator zoom fit)
• src/data-skills.ts — createColorAccessor (linear interpolation), createRadiusAccessor, flattenGeoJSON, extractPositions

Key design: noodles

The noodle system is the core AI-agent primitive. An agent emits pure data; the runtime hydrates it:

import {createNoodle, hydrateNoodle, validateNoodle} from '@deck.gl-community/visgl-skills';
import {ScatterplotLayer} from '@deck.gl/layers';

// Agent produces this as plain JSON — no callbacks, no runtime execution
const noodle = createNoodle('ScatterplotLayer', {
  data: cities,
  position: 'coordinates', // resolved to d => d.coordinates at hydration time
  radius: 'population',    // resolved to d => d.population
  fillColor: [255, 0, 128],
  radiusScale: 0.001,
});

const {valid, errors} = validateNoodle(noodle);
const layer = new ScatterplotLayer(hydrateNoodle(noodle));

No new runtime dependencies — peers only on @deck.gl/core and @deck.gl/layers.

Original prompt

Make a new module called visgl-skills that are all Claude Code / Openclaw / Agent skills for deck.gl that simplify the agents interaction and construction of deckgl , consider using noodles

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