Gourmet Research

Gourmet Research

Expert workflow for building high-quality, evidence-based food recommendations through systematic research, scoring, and documentation.

When to Use This Skill

• Researching dining options for a new city
• Creating structured food recommendations
• Evaluating restaurants, cafes, or dessert venues systematically
• Managing food research documentation with 6-file progressive disclosure structure
• Applying standardized 50-point scoring rubric to food venues

Core Workflow

Follow these steps sequentially for each city:

1. Initialize City Research

Create overview.md with:

• Travel dates, accommodation info
• City-specific food highlights (signature dishes, local specialties)
• Research strategy and priorities
• Progress checklist

Run 3-4 web searches to collect 20+ initial candidates. Record in inbox.md for fast capture.

Time: 30 minutes

2. Discover Candidates

Transfer top 3-5 candidates from inbox to candidates.md table with status: inbox.

Required table fields:

• name, category (restaurant|cafe|dessert), area, type
• google_maps_url (must be real link: maps.app.goo.gl or search API format)
• status (inbox | researching | shortlisted | rejected | top)
• sources, notes (Traditional Chinese)

Time: 20 minutes

3. Collect Evidence

For each candidate, research thoroughly and add detailed section to notes.md:

Required sources (minimum 4):

1. Google Maps (rating + review count)
2. Tripadvisor or aggregator
3. Reddit (local sentiment)
4. Food/travel guide (Michelin, TimeOut, blogs)

Document:

• Ratings from each source with URLs
• Recurring pros/cons
• Practical info: reservation requirements, hours, queue times, closures
• Handle conflicts/uncertainty explicitly (mark: unknown, conflicting, unverified)

Time: 15-20 minutes per place

4. Score with Rubric

Apply 50-point scoring system in notes.md for each researched place:

Components (0-10 each):

• Taste/Quality: Food quality, authenticity, execution
• Value: Price vs quality, portion size
• Convenience: Location, reservation ease, access
• Consistency: Reliability across reviews, time periods
• Risk (10=low risk): Likelihood of disappointment

Interpretation:

• 40+: Excellent → Top Pick
• 35-39: Very good → Top Pick
• 30-34: Good → Backup
• <30: Consider exclusion

Add total score to candidates.md table for quick reference.

Time: 10 minutes per place

5. Make Decisions

Apply promotion/exclusion thresholds:

Promote to top-places.md:

• Score ≥35 → Top Pick
• Score 30-34 → Backup

Exclude (mark rejected):

• Score <25 → Automatic exclusion
• Hard triggers: tourist trap evidence, hygiene concerns, severe service issues, practical impossibility

Update candidates.md: status: top or status: rejected

Time: 5 minutes per place

6. Triage Rejections

For rejected candidates:

• Update candidates.md: status: rejected
• Add entry to excluded.md with clear reason
• Never delete entries - always document exclusions

Time: 5 minutes per rejected place

7. Finalize Recommendations

Create/update top-places.md with:

Required sections:

1. Top Picks (35+): Name, score, area, type, google_maps_url, justification, constraints
2. Backups (30-34): Same format
3. Dining Strategy: Time planning, reservation strategy, budget, transportation
4. To-Do: Confirm closures, make reservations, plan schedule

List in descending score order within each section.

Time: 30 minutes

8. Verify Completion

Run completion checks:

# All should return 0 except top-places (should return 4)
grep -E "\| inbox \||status:?\s*inbox" gourmet/[city]/candidates.md | wc -l
grep -E "^#.*待決定|^#.*[Uu]ndecided|TODO|PENDING" gourmet/[city]/excluded.md | wc -l
grep -E "^## (Top Picks|Backups|Dining Strategy|To-Do)" gourmet/[city]/top-places.md | wc -l
grep "\[ \]" gourmet/[city]/overview.md | wc -l

Completion criteria (all required):

• ✅ No status: inbox in candidates.md
• ✅ No pending decisions in excluded.md
• ✅ top-places.md has: Top Picks + Backups + Dining Strategy + To-Do
• ✅ overview.md checklist fully checked [x]

Update PROGRESS.md status accordingly.

Time: 10 minutes

Progressive Disclosure Architecture

The 6-file structure provides layered information access:

Key principles:

• Start with conclusions, then provide evidence (inverted pyramid)
• Use summaries in higher layers (top-places, candidates)
• Keep full details in lower layers (notes)
• Link between layers: "See notes.md for evidence"
• Never duplicate information across files

Quality Standards

Research requirements:

• Minimum 4+ sources per place
• Every score justifiable with documented evidence
• Document uncertainty explicitly (use labels: unknown, conflicting, unverified, seasonal, outdated)
• Fewer, high-confidence picks over many uncertain ones
• Full traceability from recommendation to evidence

Critical rules:

• Never delete candidates.md entries (use status: rejected + excluded.md)
• Never fabricate facts or reviews
• Clearly distinguish source reports vs. your synthesis
• Test all Google Maps links
• Use Traditional Chinese for content; English for structured fields

File Structure Per City

Required directory structure:

gourmet/YYYY-MM-DD-city/
├── overview.md
├── inbox.md
├── candidates.md
├── notes.md
├── top-places.md
└── excluded.md

Templates available at repository root: /templates/*.md

References

For detailed guidance on specific aspects:

• scoring-guide.md: Comprehensive rubric with examples for each component
• quality-checklist.md: Verification steps, common pitfalls, best practices

Quick Examples

Example query: "Research dining options for Florence, February 19-22"

Response:

1. Create overview.md with Florence context (Tuscan cuisine highlights: bistecca, ribollita, lampredotto)
2. Run web searches for top restaurants, trattorias, gelaterias
3. Add 5 priority candidates to candidates.md
4. Research each with 4+ sources, document in notes.md
5. Apply 50-point scoring
6. Promote 35+ to top-places.md with dining strategy
7. Verify completion criteria met