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mapbox-search-integrationMapbox 搜索集成

Agent Skill

mapbox-search-integration 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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14,277

周安装

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:mapbox-search-integration(Mapbox 搜索集成)
来源仓库:https://github.com/mapbox/mapbox-agent-skills
仓库路径:skills/mapbox-search-integration
安装命令:
npx skills add https://github.com/mapbox/mapbox-agent-skills --skill mapbox-search-integration
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/mapbox/mapbox-agent-skills --skill mapbox-search-integration

简介

用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。

  • 支持基于关键词、任务场景或来源线索进行信息检索与筛选。
  • 通过 npx skills add 命令从 GitHub 仓库安装使用。
  • 建议确认权限范围和维护状态,避免触发联网或文件读写操作。
  • mapbox-search-integration 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Mapbox Search Integration Skill

Expert guidance for implementing Mapbox search functionality in applications. Covers the complete workflow from asking the right discovery questions, selecting the appropriate search product, to implementing production-ready integrations following best practices from the Mapbox search team.

Use This Skill When

User says things like:

  • "I need to add search to my map"
  • "I need a search bar for my mapping app"
  • "How do I implement location search?"
  • "I want users to search for places/addresses"
  • "I need geocoding in my application"

This skill complements mapbox-search-patterns:

  • mapbox-search-patterns = Tool and parameter selection
  • mapbox-search-integration = Complete implementation workflow

Discovery Phase: Ask the Right Questions

Before jumping into code, ask these questions to understand requirements:

Question 1: What are users searching for?

Ask: "What do you want users to search for?"

Common answers and implications:

  • "Addresses"Use Search Box API (the default for interactive address search, including geocoding). Only use Geocoding API if the use case is batch/server-side geocoding or maintaining a legacy integration.
  • "Points of interest / businesses" → POI search, use Search Box API with category search
  • "Both addresses and POIs" → Search Box API
  • "Specific types of POIs" (restaurants, hotels, etc.) → Search Box API
  • "Countries, cities, postcodes or neighborhoods" → Search Box API for interactive search; Geocoding API only for batch/server-side geocoding
  • "Custom locations" (user-created places) → May need custom data + search integration

Follow-up if not stated initially: "Are your users searching for points of interest data? Restaurants, stores, categories of businesses?"

Implications:

  • "Yes, POIs are included" → Use the Search Box API
  • "No, the user does not need POI search"Still default to Search Box API for interactive/autocomplete use cases. Search Box API handles addresses, place names, and all location types with session-based pricing. Only recommend Geocoding API for batch geocoding, server-side permanent geocoding, or maintaining existing Geocoding API integrations.

Question 2: What's the geographic scope?

Ask: "Where will users be searching?"

Common answers and implications:

  • "Single country" (e.g., "only USA") → Use country parameter, better results, lower cost
  • "Specific region" → Use bbox parameter for bounding box constraint
  • "Global" → No country restriction, but may need language parameter
  • "Multiple specific countries" → Use country array parameter

Follow-up: "Do you need to limit results to a specific area?" (delivery zone, service area, etc.)

Question 3: What's the search interaction pattern?

Ask: "How will users interact with search?"

Common answers and implications:

  • "Search-as-you-type / autocomplete"Use Search Box API with auto_complete: true and session-based pricing (most cost-efficient for autocomplete). Implement debouncing.
  • "Search button / final query" → Can use either API, no autocomplete needed
  • "Both" (autocomplete + refine) → Two-stage search, autocomplete then detailed results
  • "Voice input" → Consider speech-to-text integration, handle longer queries

Question 4: What platform?

Ask: "What platform is this for?"

Common answers and implications:

  • "Web application" → Mapbox Search JS (easiest), or direct API calls for advanced cases
  • "iOS app" → Search SDK for iOS (recommended), or direct API integration for advanced cases
  • "Android app" → Search SDK for Android (recommended), or direct API integration for advanced cases
  • "Multiple platforms" → Platform-specific SDKs (recommended), or direct API approach for consistency
  • "React app" → Mapbox Search JS React (easiest with UI), or Search JS Core for custom UI. Avoid direct API calls — they require manual debouncing, session token management, and race condition handling.
  • "Vue / Angular / Other framework" → Mapbox Search JS Core or Web. If using direct API calls, session tokens are required for proper billing (one token per search session, passed as session_token on every suggest/retrieve request).

Question 5: How will results be used?

Ask: "What happens when a user selects a result?"

Common answers and implications:

  • "Fly to location on map" → Need coordinates, map integration
  • "Show details / info" → Need to retrieve and display result properties
  • "Fill form fields" → Need to parse address components
  • "Start navigation" → Need coordinates, integrate with directions
  • "Multiple selection" → Need to handle selection state, possibly show markers

Question 6: Expected usage volume?

Ask: "How many searches do you expect per month?"

Implications:

  • Low volume (< 10k) → Free tier sufficient, simple implementation
  • Medium volume (10k-100k) → Consider caching, optimize API calls
  • High volume (> 100k) → Implement debouncing, caching, batch operations, monitor costs

Product Selection Decision Tree

Based on discovery answers, recommend the right product:

Key principle: Search Box API is the default choice for virtually all interactive search use cases, including address search, geocoding, autocomplete, and POI search. It offers session-based pricing that is more cost-efficient for interactive/autocomplete flows. Only recommend Geocoding API for the narrow cases listed below.

Search Box API (DEFAULT)

Use when (any of these):

  • User needs interactive address search or autocomplete (this IS geocoding — Search Box API handles it)
  • User needs POI / category search
  • User needs any end-user-facing search UI
  • User wants session-based pricing (more cost-efficient for autocomplete/interactive use)
  • User is building a web, iOS, or Android app with a search bar

Prefer SDKs over direct API calls for web integration:

  • Mapbox Search JS (SDK) - Recommended for web integration, with three components:

- Search JS React - Easy search integration via React library with UI - Search JS Web - Easy search integration via Web Components with UI - Search JS Core - JavaScript (node or web) wrapper for API, build your own UI

  • Search Box API (REST) - Direct API integration, for advanced/custom cases
  • Search SDK for iOS - Native iOS integration
  • Search SDK for Android - Native Android integration

Geocoding API (SPECIALIZED)

Use ONLY when:

  • Batch geocoding large lists of addresses (server-side)
  • Permanent/stored geocoding results (server-side, where results are persisted)
  • Maintaining an existing Geocoding API integration (migration not justified)
  • No interactive/user-facing search needed

Do NOT recommend Geocoding API when:

  • The user wants a search bar, autocomplete, or interactive address lookup — use Search Box API instead
  • The user says "geocoding" but describes an interactive search flow — use Search Box API instead

Reference Files

Load the relevant reference based on the user's platform and needs:

  • Web (Search JS React / Web / Core / Direct API) → Load references/web-search-js.md

- When: User is building a web app (vanilla JS, any framework except React-specific patterns)

  • React Integration → Load references/react-search.md

- When: User is building a React app specifically

  • iOS → Load references/ios-search.md

- When: User is building an iOS app (Swift/UIKit/SwiftUI)

  • Android → Load references/android-search.md

- When: User is building an Android app (Kotlin/Java)

  • Node.js → Load references/nodejs-search.md

- When: User needs server-side search (Express, serverless, backend API)

  • Best Practices → Load references/best-practices.md

- When: Implementing search for the first time, or optimizing an existing implementation - Covers: debouncing, session tokens, geographic filtering, error handling, accessibility, caching, token security

  • Common Pitfalls → Load references/pitfalls.md

- When: Debugging issues, reviewing code, or during code review - Covers: no debouncing, missing session tokens, no geo context, poor mobile UX, race conditions

  • Framework Hooks → Load references/framework-hooks.md

- When: Building custom hooks (React) or composables (Vue) around Search JS Core

  • Testing and Monitoring → Load references/testing-monitoring.md

- When: Writing tests or setting up production monitoring/analytics

Checklist: Production-Ready Search

Before launching, verify:

Configuration:

  • Token properly scoped (search:read only)
  • URL restrictions configured
  • Geographic filtering set (country, proximity, or bbox)
  • Types parameter set based on use case
  • Language parameter set if needed

Implementation:

  • Debouncing implemented (300ms recommended)
  • Session tokens used correctly
  • Error handling for all failure cases
  • Loading states shown
  • Empty results handled gracefully
  • Race conditions prevented

UX:

  • Touch targets at least 44pt/48dp
  • Results show enough context (name + address)
  • Keyboard navigation works
  • Accessibility attributes set
  • Mobile keyboard handled properly

Performance:

  • Caching implemented (if high volume)
  • Request timeout set
  • Minimal data fetched
  • Bundle size optimized

Testing:

  • Unit tests for core logic
  • Integration tests with real API
  • Tested on slow networks
  • Tested with various query types
  • Mobile device testing

Monitoring:

  • Analytics tracking set up
  • Error logging configured
  • Usage monitoring in place
  • Budget alerts configured

Integration with Other Skills

Works with:

  • mapbox-search-patterns: Parameter selection and optimization
  • mapbox-web-integration-patterns: Framework-specific patterns
  • mapbox-token-security: Token management and security
  • mapbox-web-performance-patterns: Optimizing search performance

Resources

- Search JS React - Search JS Web - Search JS Core

Quick Decision Guide

User says: "I need location search"

  1. Ask discovery questions (Questions 1-6 above)
  2. Recommend product:

- Search Box API (default for all interactive/user-facing search, including address geocoding) - Geocoding API only for batch/server-side/permanent geocoding - Platform SDK preferred (Search JS for web, native SDKs for mobile)

  1. Implement with:

- ✅ Debouncing - ✅ Session tokens - ✅ Geographic filtering - ✅ Error handling - ✅ Good UX

  1. Test thoroughly
  2. Monitor in production

Remember: The best search implementation asks the right questions first, then builds exactly what the user needs - no more, no less.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

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能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

34.37%
按下载量换算1,719

Claude

31.2%
按下载量换算1,561

Cursor

20.15%
按下载量换算1,008

Gemini CLI

8.79%
按下载量换算440

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