America's Test Kitchen UX Research

Modular skill for conducting UX research on any ATK feature or experience area.

When to Use This Skill

Use this skill when:

• Researching user feedback for any ATK feature (equipment, recipes, subscription, app, etc.)
• Gathering app store reviews (iOS/Android)
• Scraping Reddit discussions about ATK
• Collecting BBB complaints and Trustpilot reviews
• Creating UX research reports with findings and recommendations
• Comparing ATK to competitors (NYT Cooking, Serious Eats, etc.)

Quick Start

# Run research on a specific feature area
python3 ~/.claude/skills/atk-ux-research/scripts/atk_research.py --feature "recipes"
python3 ~/.claude/skills/atk-ux-research/scripts/atk_research.py --feature "subscription"
python3 ~/.claude/skills/atk-ux-research/scripts/atk_research.py --feature "app experience"

Feature Areas

equipment

recipes

subscription

app

video

cookbooks

Research Workflow

Phase 1: Data Collection

1.1 App Store Reviews

# iOS App Store
firecrawl https://apps.apple.com/us/app/americas-test-kitchen/id1365223384

# Google Play Store
firecrawl https://play.google.com/store/apps/details?id=com.americastestkitchen.groceryapp

1.2 Review Sites

# Trustpilot
firecrawl https://www.trustpilot.com/review/www.americastestkitchen.com

# BBB Complaints
firecrawl https://www.bbb.org/us/ma/boston/profile/publishers-periodical/americas-test-kitchen-lp-0021-66446/complaints

1.3 Reddit (JSON API)

Reddit blocks standard scrapers. Use the

.json

# Get subreddit posts
curl -s "https://www.reddit.com/r/AmericasTestKitchen/top.json?t=year&limit=25" \
  -H "User-Agent: ux-research/1.0" | python3 -c "
import sys, json
data = json.load(sys.stdin)
for post in data['data']['children']:
    p = post['data']
    print(f\"**{p['title']}** (score: {p['score']}, comments: {p['num_comments']})\")
    print(f\"  https://reddit.com{p['permalink']}\n\")"

# Get thread comments
curl -s "https://www.reddit.com/r/AmericasTestKitchen/comments/THREAD_ID.json?limit=50" \
  -H "User-Agent: ux-research/1.0" | python3 -c "
import sys, json
data = json.load(sys.stdin)
comments = data[1]['data']['children']
for c in comments[:20]:
    if c['kind'] == 't1':
        d = c['data']
        print(f\"**{d['author']}** (score: {d['score']}):\n{d['body'][:500]}\n---\")"

# Search for feature-specific discussions
curl -s "https://www.reddit.com/r/Cooking/search.json?q=america%27s+test+kitchen+FEATURE&restrict_sr=0&limit=20" \
  -H "User-Agent: ux-research/1.0"

Key Subreddits:

• r/AmericasTestKitchen - Dedicated ATK community
• r/Cooking - General cooking discussions
• r/Costco - Cookbook/product finds
• r/BuyItForLife - Equipment durability
• r/AskCulinary - Recipe questions

1.4 Exa Search

# Neural search for user feedback
python3 ~/.claude/skills/exa-search/scripts/exa_search.py \
  "America's Test Kitchen FEATURE user feedback reviews" \
  --category news -n 15

# Research with citations
python3 ~/.claude/skills/exa-search/scripts/exa_research.py \
  "What do users say about America's Test Kitchen FEATURE?" \
  --sources --markdown

1.5 Perplexity MCP

mcp__perplexity__search: "America's Test Kitchen FEATURE user complaints feedback"
mcp__perplexity__get_documentation: "ATK app store reviews analysis"

Phase 2: Analysis

2.1 Quantitative Metrics

2.2 Qualitative Themes

Code feedback into themes:

• Discoverability - Can users find the feature?
• Usability - Is it easy to use?
• Reliability - Does it work consistently?
• Value - Is it worth the price?
• Support - How are issues resolved?

2.3 Severity Classification

Phase 3: Report Generation

Use template at:

~/.claude/skills/atk-ux-research/templates/report-template.md

Report Sections

1. Executive Summary - Key findings, severity table
2. Methodology - Sources, sample sizes, limitations
3. Quantitative Overview - Ratings, complaint distribution
4. Feature Analysis - Deep dive on researched feature
5. User Pain Points - Themed complaints with evidence
6. Positive Feedback - What users appreciate
7. Recommendations - Prioritized improvements
8. Appendix - Source URLs, raw data references

Output Locations

~/Desktop/ATK-UX-Research/
├── reports/                    # Generated reports
│   └── FEATURE-YYYY-MM-DD.md
├── scraped-data/              # Raw scraped content
│   ├── app-store/
│   ├── reddit/
│   └── review-sites/
└── research-plan.md           # Active research plan

Competitor Comparison

When benchmarking, compare against:

Known Limitations

• Facebook Groups: Not accessible via API, requires manual research
• App Store Historical Data: Need AppFollow/Sensor Tower for trends
• Reddit Rate Limits: Use 2-second delays between requests
• Trustpilot: Limited ATK reviews (only 4 as of Jan 2026)

Environment Variables

# Required for full functionality
export EXA_API_KEY="your-key"
export FIRECRAWL_API_KEY="your-key"

Example Usage

Research Equipment Feature

# 1. Gather data
firecrawl https://apps.apple.com/us/app/americas-test-kitchen/id1365223384
firecrawl https://www.trustpilot.com/review/www.americastestkitchen.com

# 2. Search Reddit
curl -s "https://www.reddit.com/r/AmericasTestKitchen/search.json?q=equipment&limit=20" \
  -H "User-Agent: ux-research/1.0"

# 3. Exa research
python3 ~/.claude/skills/exa-search/scripts/exa_research.py \
  "America's Test Kitchen equipment reviews user experience" --sources

# 4. Generate report
# Use report template and synthesize findings

Research Subscription/Billing

# Focus on BBB and cancellation complaints
firecrawl https://www.bbb.org/us/ma/boston/profile/publishers-periodical/americas-test-kitchen-lp-0021-66446/complaints

curl -s "https://www.reddit.com/r/AmericasTestKitchen/search.json?q=cancel+subscription&limit=20" \
  -H "User-Agent: ux-research/1.0"

python3 ~/.claude/skills/exa-search/scripts/exa_research.py \
  "America's Test Kitchen subscription billing complaints auto-renewal" --sources

Integration with Project

This skill outputs to the ATK-UX-Research git repository:

• /Users/tomdimino/Desktop/ATK-UX-Research/

Commit findings after each research session.