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research-attractions

Automate tourist attraction research and structured documentation for travel itineraries.

Updated Apr 28, 2026
Search Tags:#automation#research#itinerary#tourism#travel#data-synthesis
One-click install
npx skills add https://github.com/escapevelocitylabs/myfootmarks --skill research-attractions
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: research-attractions
Source: https://github.com/escapevelocitylabs/myfootmarks/tree/main/skills/research-attractions
Command: npx skills add https://github.com/escapevelocitylabs/myfootmarks --skill research-attractions

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill solves the challenge of manually researching and vetting tourist attractions by automating the discovery, verification, and structured organization of landmarks, museums, and points of interest tailored to specific traveler profiles.

Core Features & Use Cases

  • Context-Aware Discovery: Filters attractions based on traveler interests, ages, and destination regions to ensure high-relevance recommendations.
  • Structured Data Synthesis: Produces both human-readable markdown and machine-consumable YAML, enabling seamless integration into trip-planning pipelines.
  • Use Case: A user planning a family trip to Rome can use this skill to generate a list of kid-friendly museums and historic sites that avoid scheduling conflicts with other planned events.

Quick Start

Run the research-attractions skill to generate a curated list of top-rated landmarks for the current trip destination.

Frequently Asked Questions about research-attractions

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate research for tourist attractions and landmarks for a travel itinerary?▼

Automating tourist attraction research cross-references destination data with traveler interests and event schedules to prioritize verified recommendations. This skill structures discovery to filter museums and landmarks based on context-aware traveler profiles.

What is the best way to curate personalized tourist attractions for a trip?▼

Curating personalized tourist attractions is done by filtering points of interest based on traveler ages, destination regions, and specific interests. This approach ensures high-relevance recommendations while avoiding scheduling conflicts with existing planned events.

Do I need external web search and image resolution services to research attractions?▼

External web search and image resolution services are required dependencies to research attractions effectively. This skill requires integration with these external services to provide verified metadata and visual context for each recommended location.

Can I get machine-readable YAML data for tourist attractions to integrate into trip planning?▼

You can get machine-readable YAML data for tourist attractions alongside human-readable markdown. This structured data synthesis enables seamless integration of verified landmarks and points of interest into automated trip-planning pipelines.

How does context-aware discovery filter kid-friendly museums and historic sites?▼

Context-aware discovery filters kid-friendly museums and historic sites by matching traveler profiles, ages, and destination regions against available attraction data. This ensures high-relevance recommendations tailored to specific family trip requirements.

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