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PQS 40 (D) - prompt from raw.githubusercontent.com

Source: raw.githubusercontent.com · Scraped 2026-05-04 · Scored 2026-05-04

Score

40 / 80

gemma4:latest · local · pqs-v2.0 · canonical

Clarity9 / 10

Specificity8 / 10

Context7 / 10

Constraints3 / 10

Output format10 / 10

Role definition1 / 10

Examples1 / 10

CoT structure1 / 10

The prompt

<!DOCTYPE html>
<html>
<head>
 <title>Travel Itinerary: Nanjing to Changchun</title>
 <style>
 body { font-family: Arial, sans-serif; }
 .itinerary { margin: 20px; }
 .day { margin-bottom: 20px; }
 .header { font-size: 24px; font-weight: bold; }
 .sub-header { font-size: 18px; font-weight: bold; }
 </style>
</head>
<body>
 <div class="itinerary">
 <div class="header">Travel Itinerary: Nanjing to Changchun</div>
 <div class="sub-header">Dates: ${startDate} to ${endDate}</div>
 <div class="sub-header">Budget: ${budget} RMB</div>

 <div class="day">
 <div class="sub-header">Day 1: Arrival in Changchun</div>
 <p><strong>Flight:</strong> ${flightDetails}</p>
 <p><strong>Hotel:</strong> ${hotelName} - Located in city center, comfortable and affordable</p>
 <p><strong>Weather:</strong> ${weatherForecast}</p>
 <p><strong>Packing Tips:</strong> ${packingRecommendations}</p>
 </div>

 <div class="day">
 <div class="sub-header">Day 2: Exploring Changchun</div>
 <p><strong>Attractions:</strong> ${attraction1} (Ticket: ${ticketPrice1}, Open: ${openTime1})</p>
 <p><strong>Lunch:</strong> Try local cuisine at ${restaurant1}</p>
 <p><strong>Afternoon:</strong> Visit ${attraction2} (Ticket: ${ticketPrice2}, Open: ${openTime2})</p>
 <p><strong>Dinner:</strong> Enjoy a meal at ${restaurant2}</p>
 <p><strong>Transportation:</strong> ${transportDetails}</p>
 </div>

 <!-- Repeat similar blocks for Day 3, Day 4, etc. -->
 
 <div class="day">
 <div class="sub-header">Day 5: Departure</div>
 <p><strong>Return Flight:</strong> ${returnFlightDetails}</p>
 </div>

 </div>
</body>
</html>

This prompt was scraped from a public source. The score reflects the input as written, not the quality of any output it produced. The AI input quality problem is the gap between what people type and what the model can act on.