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Agent Skill · 研究检索

mapbox-search-integration(Mapbox 搜索集成)

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。

mapbox-search-integration 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 9,411。

总安装 14,277周安装 607GitHub Stars 47下载 5,002核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

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。

来源仓库内路径:skills/mapbox-search-integration

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/mapbox/mapbox-agent-skills --skill mapbox-sear…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

mapbox-search-integration 怎么安装?

在终端执行 npx skills add https://github.com/mapbox/mapbox-agent-skills --skill mapbox-search-integra…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

mapbox-search-integration 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

mapbox-search-integration 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

mapbox-search-integration 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

mapbox-search-integration 用的人多吗?

公开数据是累计安装 14,277 次,近一周安装 607 次,下载 5,002 次,GitHub 47 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

mapbox-search-integration 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
mapbox-search-integration

Mapbox 搜索集成 · 本页

14,27747接触敏感数据未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

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.

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

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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