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gourmet-research

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Gourmet Research

Overview

Template-first workflow for traceable, comparable, auditable food recommendations across cities. Keep evidence, scores, and decisions synchronized.

Core Rules (Non-Negotiable)

  • If the user has not specified an output language, ask once at project start and record it in overview.md.
  • Use gourmet/<city-slug>/ with 6 files: overview.md, inbox.md, candidates.md, notes.md, top-places.md, excluded.md.
  • Never fabricate sources, ratings, or claims. Use unknown when missing.
  • Prefer original-language place names (not translated) unless the user requests otherwise.
  • Preserve audit trail: never delete candidates; mark rejected and record why in excluded.md.
  • Default minimum sources = 4. If the locale is information-sparse, allow 3 only when you record evidence: limited with the reason and attempted sources.

Template-First Workflow (Summary)

  1. Initialize: Ask for output language + city, then copy templates from assets/templates/ into the city folder.
  2. Normalize: Update language/city placeholders in the copied files before research begins.
  3. Discovery: Capture raw ideas in inbox.md, then move top candidates into candidates.md with status: inbox.
  4. Evidence: For each candidate, write a full evidence block in notes.md with sources + practical constraints.
  5. Score: Apply the 50-point rubric and justify each component in notes.md.
  6. Decide: Promote to Top Picks (>=35), Backups (30-34), or reject (<30).
  7. Publish: Update top-places.md and excluded.md to match decisions.
  8. Verify: Ensure no inbox statuses remain and required sections exist.

Ranking Retrieval (When user asks for “highest score”)

Before extracting any “top N” list, confirm the scope:

  • Geography: Okinawa prefecture vs main island only vs specific subarea.
  • Category: overall vs cuisine category.
  • Source URL: must match the user’s intent exactly.

Checklist (must pass):

  1. URL matches the requested scope (prefecture vs category).
  2. If “main island only” is required, exclude island subareas (A4705/A4706).
  3. Page title confirms the intended ranking.
  4. Language modal handled so list items actually render.

If static scraping fails or content is blocked, use Playwright to load the page, close the language modal (日本語), and then extract items.

Evidence & Negative Review Rules

  • Sources must include: Maps + local reviews + guide/editorial + official channel (where available).
  • Negative review analysis is conditional: perform a focused negative review pass when risk signals appear in any source.
    • Risk signals: repeated service complaints, hygiene/safety concerns, tourist-trap claims, extreme queue issues, inconsistent ratings, unclear hours/reservations.
    • If triggered: add a Negative reviews subsection in notes.md, adjust Risk/Consistency/Value as needed, and sync scores/status across files.

Locale-Specific Source Suggestions (Optional)

LocaleLocal reviewsAggregatorGuides/editorial
JapanTabelog, RettyGoogle MapsMichelin, local food media
KoreaNaver Map, Kakao MapGoogle MapsMichelin, local food media
TaiwanGoogle Maps, iPeenOpenRiceLocal food media
Hong KongOpenRiceGoogle MapsMichelin, local food media
SingaporeOpenRiceGoogle MapsMichelin, local food media
EuropeGoogle MapsTripadvisorMichelin, local city guides
North AmericaGoogle Maps, YelpTripadvisorEater, local food media
Latin AmericaGoogle MapsTripadvisorLocal city guides
SEA (general)Google MapsTripadvisorLocal food media

Scoring (50-Point Rubric)

  • Taste/Quality (0-10)
  • Value (0-10)
  • Convenience (0-10)
  • Consistency (0-10)
  • Risk (0-10, higher = lower risk)

Thresholds:

  • Top Picks: >=35
  • Backups: 30-34
  • Reject: <30 (or hard exclusion: hygiene/safety/tourist-trap evidence)

Roles (Optional, Compact)

  • Research: find sources + capture evidence.
  • Verify: resolve conflicts, confirm practical constraints.
  • Score: apply rubric + justify.
  • Synthesize: finalize top-places + dining strategy.

Quick Reference

ItemRule
City pathgourmet/<city-slug>/
Filesoverview/inbox/candidates/notes/top-places/excluded
Min sources4 (3 only with evidence: limited)
Output languageAsk if not specified
Place namesPrefer original language
Score tiers>=35 Top, 30-34 Backup, <30 Reject

Example (Evidence Block)

### Sakura Teahouse
**Official**: https://example.com
**Maps**: 4.4/5 (820 reviews) - https://maps.app.goo.gl/...
**Local reviews**: 3.7/5 (420 reviews) - https://tabelog.com/...
**Guide/editorial**: https://guide.example.com/...
**Notes**: quiet seating, popular seasonal desserts
**Practical**: reservations recommended, closed Tue
**Score**: Taste 8 / Value 7 / Convenience 6 / Consistency 7 / Risk 7 = **35/50**

Common Mistakes

  • Skipping templates and mixing content across files.
  • Skipping inbox.md and dumping raw ideas into candidates.
  • Translating place names instead of using the original language.
  • Using only one review platform.
  • Pulling the wrong ranking scope (category vs overall, islands included).
  • Changing scores without updating candidates/top-places/excluded.
  • Ignoring unclear hours or reservation policies.

Rationalization Table

ExcuseReality
"It’s just one city; I can skip templates."Templates prevent drift and keep outputs comparable.
"Inbox is optional; I can put everything in candidates."inbox.md keeps raw capture separate and reduces noise.
"There aren’t 4 sources; I’ll guess."Use unknown and mark evidence: limited. Never guess.
"I’ll translate names for clarity."Keep original-language names unless the user asks.
"This ranking page is close enough."Scope mismatch invalidates the answer. Confirm URL and geography.
"Negative reviews are optional."Required when risk signals appear.

Red Flags — Stop and Fix

  • Candidates deleted instead of rejected.
  • Scores updated in notes but not in candidates/top-places.
  • Missing output language decision.
  • Uncited claims or ratings.

References

  • references/repo-spec.md
  • assets/templates/

Source

git clone https://github.com/narumiruna/agent-skills/blob/main/skills/gourmet-research/SKILL.mdView on GitHub

Overview

This skill provides a template-first workflow to create auditable, comparable gourmet recommendations across cities. It enforces an evidence-backed process with six-city-folder templates and a clear audit trail for decisions, scores, and sources.

How This Skill Works

Work starts by initializing a city folder (gourmet/<city-slug>/) with six files. Capture ideas in inbox.md, move top candidates to candidates.md with status: inbox, then write full evidence blocks in notes.md with sources. Apply a 50-point rubric to score, decide between Top Picks, Backups, or reject, and publish updates to top-places.md and excluded.md; finally verify no inbox items remain and all required sections exist.

When to Use It

  • Starting a fresh gourmet city research project for a new city folder.
  • Updating an existing city with new sources, scores, or decisions to reflect current evidence.
  • Auditing the research process to ensure a complete audit trail and non-deletion of candidates.
  • Handling information-sparse locales by marking evidence as limited and documenting attempts.
  • Responding to a request for the highest-scoring results with scope checks (geography/category/source).

Quick Start

  1. Step 1: Initialize project and copy templates to gourmet/<city-slug>/.
  2. Step 2: Normalize placeholders and begin Discovery by adding ideas to inbox.md.
  3. Step 3: Move candidates to candidates.md, write notes with sources, score, decide, and publish to top-places.md.

Best Practices

  • Initialize: ask for output language and city at project start and copy templates from assets/templates/ into gourmet/<city-slug>/.
  • Discovery: capture raw ideas in inbox.md, then move top candidates into candidates.md with status: inbox.
  • Evidence: for each candidate, write a full evidence block in notes.md including sources and practical constraints.
  • Scoring: apply the 50-point rubric and justify each component in notes.md; promote Top Picks, Backups, or reject accordingly.
  • Audit trail: never delete candidates; record reasons for exclusions in excluded.md and ensure minimum sources (4, or 3 with evidence: limited and rationale).

Example Use Cases

  • Create gourmet/tokyo with six files and begin gathering multi-source evidence for restaurant districts.
  • Update gourmet/paris as new local guides publish reviews, re-score candidates, and adjust Top Picks.
  • In gourmet/kyoto mark evidence as limited due to sparse sources and document attempts to gather more data.
  • Publish best results from gourmet/new-york to top-places.md after achieving a score of 35+.
  • Maintain audit integrity in gourmet/melbourne by marking unsuitable candidates as rejected in excluded.md without deleting records.

Frequently Asked Questions

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