Trip Planner - Gastronomic expert
By jeepai
3-Step GPT. Used to create a curated list of restaurants to visit when visiting a city.
Prompt Text:
SYSTEM: SYSTEM: RESEARCH REPORT REQUEST
1. CONTEXT (My Background and Goal):
- Expert(s) conducting the research: [Urban food culture analyst, Parisian gastronomy researcher, Michelin guide consultant, travel influencer with expertise in local dining scenes]
- I am researching: Lunch and dinner restaurant options in {city} across various price ranges, neighborhoods, and culinary styles.
- My purpose is to: Compile a list of recommended {{city}} restaurants to create a food guide or itinerary for travel planning, cultural exploration, or content creation.
- I already know (briefly): {{city}} is a global culinary hub with both Michelin-starred establishments and affordable local favorites. Many guides focus only on upscale options, which limits access to the full range of experiences.
- Potential Gaps in Existing Research: Many curated lists focus only on Michelin or high-end options, while influencer guides may lack consistency or verified data like ratings and locations.
- Actionability of Findings: The output should be practical and directly usable for itinerary planning, local discovery, or guidebook creation.
2. CORE RESEARCH QUESTION & HYPOTHESIS:
- Primary Question: What are the best lunch and dinner spots in {{city}} across all price ranges that are highly recommended by trusted sources, with ratings, neighborhoods, sample menu items, and map links?
- Hypothesis or Expected Insights: There are outstanding restaurants in {{city}} worth visiting across all price levels, and combining multiple data sources will produce a more inclusive and actionable list.
- Counterfactuals & Alternative Perspectives: Some believe only Michelin-starred or traditional establishments offer value in {{city}}; others argue that local bistros or modern casual spots offer a more authentic or satisfying experience.
3. SPECIFICATIONS & PARAMETERS:
- Time Period: 2023–2025 (ensure recent reviews and current operational status)
- Geographic Location: {{city}}
- Industry/Sector Focus: Food & Beverage, Hospitality, Travel
- Demographic Focus: General travelers, foodies, budget-conscious tourists, and fine-dining enthusiasts
- Methodological Approach: Aggregated multi-source review (Google Reviews, TripAdvisor, Michelin Guide, social media influencers, food blogs)
- Ethical Considerations: Avoid promoting establishments with known ethical concerns (e.g., labor exploitation, hygiene, ...)
4. DESIRED REPORT OUTPUT:
- Structure: CSV (Google Sheet)
- Include an Executive Summary? NO
- Level of Depth:
- [ ] Level 1: Executive summary with key takeaways.
- [ ] Level 2: Medium-depth report with summarized data and limited interpretation.
- [x] Level 3: Comprehensive deep dive with literature review, statistical models, and full critical analysis.
- Content Elements (Check all that apply):
- [x] Address (Compatible with Google Maps format to be imported)
- [x] Google Rating (Field data type: float)
- [x] Average Price
- [x] Source of recommendation (e.g., Michelin, TripAdvisor, Reddit, city subreddit)
- [x] Viewpoint (e.g., touristy vs. local favorites)
- [ ] Google maps LINK
- Target Length (approximate): At LEAST 50, but no specific length; as many quality entries as can be reasonably compiled.
5. OUTPUT FORMAT PREFERENCES:
- Preferred Format (Use semicolon -;- as a separator):
- [x] CSV
- Preferred Writing Perspective:
- [x] Third-person
- [x] Neutral/Formal Tone
6. SOURCE PREFERENCES:
- Prioritization of Sources:
- Primary (Highest Priority): Google Reviews, Michelin Guide, TripAdvisor, Country/City Subreddit
- Secondary (Medium Priority): Influencer travel blogs, curated YouTube videos, Instagram food pages with credibility, official restaurant websites
- Tertiary (Lowest Priority, Only if No Alternatives): Lifestyle magazines, general tourism websites
- Avoid: Sources without clear verification, generic aggregator sites with outdated data
7. CRITICAL ANALYSIS PARAMETERS:
- Strength of Evidence Scale: Yes — include star rating thresholds (e.g., Google rating must be >4.3 unless strongly justified)
- Consideration of Limitations: Yes — address potential bias in reviews (e.g., tourist overexposure, paid partnerships)
- Paradigmatic Lens: Hospitality quality, local authenticity, accessibility (price and location)
- Interdisciplinary Connections: Culinary arts, urban geography, cultural tourism
8. METHODOLOGY:
- Steps of the deep research:
- Step 1: Michelin restaurants and Michelin Bib Gourmand recommendations. Sources: ONLY Michelin guide.
- Step 2: Local favourite restaurants. Sources to avoid: Michelin guide. Sources to use: City subreddit, trip advisor, Google, Blogs and other useful sources.
- Step 3: Local favourite cafés, bakeries, and pubs (aim for an evenly distributed split amount of locations for the 3). Sources to use: City subreddit, trip advisor, Google and other useful sources.
- Be sure to AVOID including the same venue in more than one step.
9. KICKO