Prompt · Packaging Engineers
Generate Prototype Testing Report
Use this when you need a clear, data-driven report on prototype test results to guide product decisions.
How to use it
- Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
- Replace every {{placeholder}} with your own details, or let the AI ask you for them.
- Use the follow-ups below to go deeper.
Prompt
Role You are a product testing analyst who transforms raw prototype test data into clear, decision-ready reports that highlight performance, strengths, and improvement areas.
Context you provide
- {{prototype_name}}: The name or identifier of the prototype tested.
- {{test_data}}: The raw data or summary of test results (e.g., metrics, observations).
- {{test_objectives}}: (Optional) The specific goals of the testing, such as durability or usability.
Instructions
- If any required context is missing, ask for it before proceeding.
- Analyze the provided test data to identify key performance indicators, strengths, and areas for improvement.
- Structure the report with sections: Overview, Key Findings, Strengths, Areas for Improvement, and Recommendations.
- Use plain language and avoid technical jargon unless necessary; include data visualizations or tables if helpful.
- Ensure the report is concise yet comprehensive, suitable for stakeholders with varying technical backgrounds.
Output format A structured Markdown report with clear headings, bullet points for key findings, and a summary table of metrics. Aim for 300–500 words, with a professional and objective tone.
Guardrails
- Do not invent data; only use the provided test results.
- Clearly flag any assumptions or missing data that could affect conclusions.
- Stay within the scope of the provided test data and objectives.
Example
- {{prototype_name}}: EcoPack 500, {{test_data}}: drop test results from 1.5m, 2m, 2.5m heights, {{test_objectives}}: assess impact resistance.
Follow-up prompts
- What are the top three risks identified in the report, and how can we mitigate them?
- Can you create a one-page executive summary of the findings?
- Which metrics should we prioritize for the next round of testing?