mapbox-store-locator-patterns

Common style patterns, layer configurations, and recipes for typical mapping scenarios including restaurant finders, real estate, data visualization, navigation, delivery/logistics, and more.

Integration patterns for Mapbox MCP Server in AI applications and agent frameworks. Covers runtime integration with pydantic-ai, mastra, LangChain, and custom agents. Use when building AI-powered applications that need geospatial capabilities.

Navigation implementation patterns for turn-by-turn directions, route optimization, real-time traffic, multi-stop routing, and voice guidance across web, iOS, and Android platforms

Complete workflow for implementing Mapbox search in applications - from discovery questions to production-ready integration with best practices

Expert guidance on choosing the right Mapbox search tool and parameters for geocoding, POI search, and location discovery

Security best practices for Mapbox access tokens, including scope management, URL restrictions, rotation strategies, and protecting sensitive data. Use when creating, managing, or advising on Mapbox token security.

Performance optimization patterns for Mapbox GL JS web applications. Covers initialization waterfalls, bundle size, rendering performance, memory management, and web optimization. Prioritized by impact on user experience.

Official integration patterns for Mapbox GL JS across popular web frameworks (React, Vue, Svelte, Angular). Covers setup, lifecycle management, token handling, search integration, and common pitfalls. Based on Mapbox's create-web-app scaffolding tool.

Rigor Explore compatible skill slug for meaningful and potentially novel deep learning research candidates. Use when the researcher has chosen the task family, dataset, benchmark, evaluation method, provided SOTA references, and wants …

Rigor Reproduce compatible skill slug for README-first deep learning repository reproduction. Use when the user wants an end-to-end, minimal-trustworthy flow that reads the repository first, selects the smallest documented inference or evaluation …

Rigor Train skill for deep learning research repositories. Use when a documented or selected training command should be run conservatively for startup verification, short-run verification, full kickoff, or resume, with command, config …

Rigor Improve / Rigor Explore run leaf skill for bounded exploratory evidence in deep learning research repositories. Use when the researcher explicitly authorizes exploratory runs such as small-subset validation, short-cycle guess-and-check, batch …

Search, scrape, crawl, extract structured data, and monitor web pages via the ScrapeGraph AI CLI.

Web search and content extraction with Tavily and Exa via inference.sh CLI. Apps: Tavily Search, Tavily Extract, Exa Search, Exa Answer, Exa Extract. Capabilities: AI-powered search, content extraction, direct answers, research.

When the user wants to create sales collateral, pitch decks, one-pagers, objection handling docs, or demo scripts. Also use when the user mentions 'sales deck,' 'pitch deck,' 'one-pager,' 'leave-behind,' 'objection handling,' 'deal-specific …

When the user wants to conduct, analyze, or synthesize customer research. Use when the user mentions "customer research," "ICP research," "talk to customers," "analyze transcripts," "customer interviews," "survey analysis," "support ticket analysis," …