Add skill: mapbox-tiling-service-patterns

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## Summary

Mapbox Tiling Service (MTS) is how developers publish custom vector tilesets at scale, but the recipe authoring, validation, and publishing workflow is complex and Mapbox-specific. AI assistants have essentially no useful knowledge here.

## Topics to cover

- **Recipe authoring** - layer definitions, feature filters, zoom level configuration, simplification
- **Tileset sources** - uploading GeoJSON/CSV/Shapefile as a tileset source via the API
- **Publishing and updating** - creating, publishing, and updating tilesets; tracking job status
- **Validation** - common recipe errors, size limits, attribute type constraints
- **Using tilesets in styles** - referencing MTS tilesets in Mapbox Studio and GL JS
- **Update pipelines** - automating tileset updates when source data changes (CI/CD patterns)
- **Cost and performance** - understanding processing time, tile counts, and when MTS is the right choice vs. uploading GeoJSON directly

## Key patterns a skill should teach

- Minimal viable recipe structure for common use cases (point data, polygon data, line data)
- How to check tileset processing status and handle failures
- The `source-layer` name convention and how it maps to recipe layer IDs
- When to use MTS vs. the Uploads API vs. serving your own tiles

## Why this matters

MTS is the right solution for large or frequently-updated datasets, but developers often reach for GeoJSON uploads instead because they don't know the workflow. A skill here would steer developers toward the correct tool for their data scale.

No files, tests, or entry points are named. Use the topic list as the outline, beginning with recipe authoring and the MTS API workflow, then cover validation, style usage, update pipelines, and trade-offs. Done means the skill explains the listed patterns, status and failure handling, source-layer conventions, and when to choose MTS, the Uploads API, or self-hosted tiles.

Written by the indexing model from the issue text.