synth-restaurants

Merge restaurant research markdown files into a canonical recommendation list.

Updated Apr 28, 2026

Search Tags:#research #synthesis #itinerary #travel #restaurants #data-merging

Ready to run

npx skills add https://github.com/escapevelocitylabs/myfootmarks --skill synth-restaurants

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: synth-restaurants
Source: https://github.com/escapevelocitylabs/myfootmarks/tree/main/skills/synth-restaurants
Command: npx skills add https://github.com/escapevelocitylabs/myfootmarks --skill synth-restaurants

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill solves the issue of scattered restaurant research by merging base findings with specialized recommendations into a single, canonical document.

Core Features & Use Cases

Intelligent Merging: Automatically deduplicates restaurant entries while preserving the strongest justifications and notes from multiple sources.
Conflict Resolution: Prioritizes specialized research (like kid-friendly or local-cuisine) over general base research to ensure the most accurate recommendations.
Use Case: After researching general dining and kid-friendly spots for a trip, use this skill to create a single, clean list that combines all relevant details and contact information for your final itinerary.

Quick Start

Run the synth-restaurants skill to merge all existing restaurant research files into a final canonical list for the current trip.

Frequently Asked Questions about synth-restaurants

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

FAQPage Schema

How do I consolidate fragmented restaurant research into a single itinerary?▼

You can consolidate fragmented restaurant research by merging multiple markdown research files into a single canonical recommendation list, automatically deduplicating entries and synthesizing justifications based on source priority and specialization.

How does data merging handle duplicate restaurant entries from multiple sources?▼

Data merging handles duplicate restaurant entries by prioritizing specialized research, such as kid-friendly or local-cuisine recommendations, over general base research to preserve the strongest justifications and notes in the final output.

What is the best way to deduplicate restaurant recommendations for trip planning?▼

The best way to deduplicate restaurant recommendations is to synthesize justifications from multiple source files, prioritizing specialized research over general base research to ensure the most accurate recommendations for your final itinerary.

Do I need specific directory structures to merge restaurant research files?▼

Yes, you need access to trip metadata and research files within the myfootmarks directory structure to successfully merge restaurant research files and generate the final canonical list output.

Can I combine general dining and kid-friendly restaurant research into one list?▼

Yes, you can combine general dining and kid-friendly restaurant research into one list by merging the base findings with specialized recommendations, ensuring all relevant details and contact information are integrated for your trip.

What are the limitations of synthesizing restaurant research from markdown files?▼

A limitation of synthesizing restaurant research is that it requires markdown files organized within the myfootmarks directory structure, and it relies on source priority logic to resolve conflicts rather than manual selection.