本文へ移動
cccskills
無料GitHub で公開

restaurant-reviews

Multi-platform review analysis — pulls Yelp/Google/TripAdvisor reviews, identifies recurring complaints, sentiment patterns, response rate, and rating trajectory

インストール方法を見る

含まれるファイル(1)

  • SKILL.md5.8 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Restaurant Reviews Analysis

You analyze a restaurant's review profile across all major platforms — Google, Yelp, TripAdvisor, OpenTable, and third-party delivery apps — and produce a structured report identifying recurring complaints, recurring praises, owner response performance, and rating trajectory over time.

DISCLAIMER: AI-generated analysis based on publicly available reviews. Always verify with the restaurant owner.


When to use

  • /restaurant reviews <name> — full multi-platform review breakdown
  • "analyze reviews for [name]"
  • "what are people saying about [name]"

Execution Pipeline

Step 1: Locate Listings

WebSearch("[name] [city] google reviews")
WebSearch("[name] [city] yelp")
WebSearch("[name] [city] tripadvisor")
WebSearch("[name] [city] doordash ubereats grubhub reviews")

Capture for each platform:

  • URL
  • Star rating
  • Review count
  • Owner verified Y/N
  • Last owner response date

Step 2: Read Recent Reviews

Read the 20 most recent reviews on each platform (last 90 days where possible). Categorize each as:

  • Positive (4-5 stars)
  • Neutral (3 stars)
  • Negative (1-2 stars)

Step 3: Theme Extraction

Build two lists by tallying common phrases:

Top 5 Recurring Complaints — categories like:

  • Slow service / long wait
  • Cold food / quality issues
  • Pricing / portion size
  • Noise level / atmosphere
  • Parking / location
  • Staff attitude
  • Cleanliness
  • Online ordering / delivery problems
  • Bathroom / facilities
  • Reservation / wait list

Top 5 Recurring Praises:

  • Specific dish names (signature items)
  • Specific staff names (servers, chef, host)
  • Atmosphere / ambiance
  • Value
  • Service speed (positive)
  • Authenticity / quality

Step 4: Owner Response Analysis

For the last 50 reviews across platforms:

  • % of negative reviews with owner reply
  • % of positive reviews with owner reply (yes, this matters)
  • Average response time (days)
  • Response quality: templated vs personalized vs absent

Industry benchmark: top-decile restaurants respond to 100% of negative reviews within 48 hours.

Step 5: Rating Trajectory

Look at rating over time (use the rating history shown on Yelp / Google or infer from recent vs older reviews):

  • 12-month trend: improving / flat / declining
  • Inflection points: any sudden drops or jumps
  • Recent 30-day score vs all-time average

Step 6: Cross-Platform Comparison

PlatformStarsCountLast Owner ReplyResponse Rate (neg)
Google............
Yelp............
TripAdvisor............

Identify gaps: e.g., 4.4 on Google but 3.6 on Yelp = perception gap to investigate.


Output Template

Save to RESTAURANT-REVIEWS-[Name].md:

# Reviews & Reputation Analysis: [NAME]

> **Generated:** [DATE] | **Composite Rating:** [X.X] stars | **Total Reviews:** [N]

**DISCLAIMER: AI-generated review analysis. Always verify with the restaurant owner.**

## Cross-Platform Snapshot

| Platform | Stars | Reviews | Owner Verified | Response Rate (Neg) | Last Owner Reply |
|----------|-------|---------|----------------|---------------------|------------------|
| Google | ... | ... | ... | ... | ... |
| Yelp | ... | ... | ... | ... | ... |
| TripAdvisor | ... | ... | ... | ... | ... |
| DoorDash | ... | ... | n/a | n/a | n/a |

**Perception Gap Notes:** [Any large gaps between platforms and likely reason]

## Rating Trajectory (12 Months)

- **Trend:** [Improving / Stable / Declining]
- **Inflection points:** [Any sudden changes and likely cause]
- **Recent 30 days vs all-time:** [Comparison]

## Top 5 Recurring Complaints

1. **[Theme]** — appears in ~X% of negative reviews. Example quote: "..." Action: [specific fix]
2. **[Theme]** — ...
3. ...

## Top 5 Recurring Praises

1. **[Theme]** — appears in ~X% of positive reviews. Example quote: "..." Action: [how to amplify]
2. ...

## Owner Response Performance

| Metric | Current | Industry Benchmark | Gap |
|--------|---------|---------------------|-----|
| Negative response rate | X% | 100% within 48hr | -X% |
| Positive response rate | X% | 30%+ | ... |
| Average response time | X days | <48 hours | ... |
| Response quality | [Personal/Template/Absent] | Personal | ... |

## Unanswered Critical Reviews (Last 90 Days)

[List up to 10 unanswered 1-2 star reviews with quote + date + platform. These need responses NOW.]

## Reviews Score

| Sub-Dimension | Score | Rationale |
|---------------|-------|-----------|
| Star Rating | X/20 | ... |
| Review Volume & Recency | X/20 | ... |
| Owner Response Rate | X/20 | ... |
| Sentiment Pattern | X/20 | ... |
| Rating Trajectory | X/20 | ... |
| **Total** | **X/100** | |

## Recommended Actions This Week

1. Respond to all unanswered 1-star reviews (see list above). Template provided in `/restaurant respond [name]`.
2. ...
3. ...

## 30-Day Outlook

If owner responds to all backlogged negative reviews and resolves the top complaint, expect:
- Star rating lift: +0.1 to +0.3
- Revenue impact: estimated +$X,XXX/month at current covers

Quality Standards

  • Quote actual review text where possible
  • Use percentages not vague terms ("32% of negatives" not "many negatives")
  • Always include the example quote for each theme
  • Always flag unanswered critical reviews — these are the highest-priority lift
  • Connect every recommendation to a revenue number

DISCLAIMER: For educational/research purposes only. AI-generated analysis.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

Launches 5 parallel AI agents to produce a comprehensive restaurant audit with composite Restaurant Health Score (0-100), grade, and prioritized action plan

日本語の概要は準備中です。原文の説明を表示しています。

zubair-trabzada/ai-restaurant-claude332026年5月21日 更新

Facebook/Instagram ad copy variations — 10+ ad copy variants across happy hour, lunch, weekend brunch, catering, birthday/anniversary angles with A/B testing framework

日本語の概要は準備中です。原文の説明を表示しています。

zubair-trabzada/ai-restaurant-claude332026年5月21日 更新

Top 5 local competitor analysis — menu, pricing, review, social, and SEO comparison with positioning gap identification

日本語の概要は準備中です。原文の説明を表示しています。

zubair-trabzada/ai-restaurant-claude332026年5月21日 更新

Email and SMS sequences — loyalty program emails, birthday emails, win-back campaigns, special event invites, abandoned cart for online orders

日本語の概要は準備中です。原文の説明を表示しています。

zubair-trabzada/ai-restaurant-claude332026年5月21日 更新

Local SEO audit — "best [cuisine] near me" targeting, Google Business Profile optimization, NAP consistency, citation building, restaurant schema markup

日本語の概要は準備中です。原文の説明を表示しています。

zubair-trabzada/ai-restaurant-claude332026年5月21日 更新

Menu engineering analysis — item placement, description quality, pricing psychology, upsell opportunities, photo presence, Kasavana matrix (Stars/Plowhorses/Puzzles/Dogs)

日本語の概要は準備中です。原文の説明を表示しています。

zubair-trabzada/ai-restaurant-claude332026年5月21日 更新

zubair-trabzada のスキルをすべて見る

このスキルの問題を報告する