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.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionmapbox-search-integrationExecute the skills CLI command in your project's root directory to begin installation:
Fetches mapbox-search-integration from mapbox/mapbox-agent-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate mapbox-search-integration. Access via /mapbox-search-integration in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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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.
User says things like:
This skill complements mapbox-search-patterns:
mapbox-search-patterns = Tool and parameter selectionmapbox-search-integration = Complete implementation workflowBefore jumping into code, ask these questions to understand requirements:
Ask: "What do you want users to search for?"
Common answers and implications:
Follow-up if not stated initially: "Are your users searching for points of interest data? Restaurants, stores, categories of businesses?"
Implications:
Ask: "Where will users be searching?"
Common answers and implications:
country parameter, better results, lower costbbox parameter for bounding box constraintcountry array parameterFollow-up: "Do you need to limit results to a specific area?" (delivery zone, service area, etc.)
Ask: "How will users interact with search?"
Common answers and implications:
auto_complete: true and session-based pricing (most cost-efficient for autocomplete). Implement debouncing.Ask: "What platform is this for?"
Common answers and implications:
session_token on every suggest/retrieve request).Ask: "What happens when a user selects a result?"
Common answers and implications:
Ask: "How many searches do you expect per month?"
Implications:
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.
Use when (any of these):
Prefer SDKs over direct API calls for web integration:
Use ONLY when:
Do NOT recommend Geocoding API when:
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
React Integration → Load references/react-search.md
iOS → Load references/ios-search.md
Android → Load references/android-search.md
Node.js → Load references/nodejs-search.md
Best Practices → Load references/best-practices.md
Common Pitfalls → Load references/pitfalls.md
Framework Hooks → Load references/framework-hooks.md
Testing and Monitoring → Load references/testing-monitoring.md
Before launching, verify:
Configuration:
Implementation:
UX:
Performance:
Testing:
Monitoring:
Works with:
User says: "I need location search"
Remember: The best search implementation asks the right questions first, then builds exactly what the user needs - no more, no less.
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
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Useful defaults in mapbox-search-integration — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
mapbox-search-integration is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Registry listing for mapbox-search-integration matched our evaluation — installs cleanly and behaves as described in the markdown.
We added mapbox-search-integration from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Keeps context tight: mapbox-search-integration is the kind of skill you can hand to a new teammate without a long onboarding doc.
Useful defaults in mapbox-search-integration — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend mapbox-search-integration for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
mapbox-search-integration fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
mapbox-search-integration has been reliable in day-to-day use. Documentation quality is above average for community skills.
mapbox-search-integration reduced setup friction for our internal harness; good balance of opinion and flexibility.
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