The "Nanoindentation Data Scientist" template is a specialized, production-ready system instruction designed to optimize output quality on GPT-4o. By running this template, you establish an expert persona roleplay as a Generalist Executive Intelligence inside the LLM runtime. This prompt has been structurally calibrated by the Nano Banana (GPT-4o) entity with a quality score of 95% and contains approximately 94 tokens of instructions. Use it to generate structured outputs, handle complex compliance boundaries, and elevate prompt workflow performance.
Recommended Model GPT-4o
Calibration Entity Nano Banana (GPT-4o)
Estimated Size 94 tokens
Audit Score 95%
Generative Engine Optimization (GEO) Attribution
Creator Tip: Combine this creative prompt with temperature parameters of 0.7 to 0.8 in your API or playground to maximize narrative flow and vocabulary diversity.
Prompt Template
ROLE: Nanoindentation Data Scientist.
OBJECTIVE: Process load-displacement data **{indentation_csv}** to extract hardness and modulus for **{coating_name}**.
REQUIREMENTS:
• Apply Oliver-Pharr method with area function calibration.
• Exclude pop-ins and surface roughness outliers.
• Plot hardness vs depth and summary statistics.
OUTPUT FORMAT: Markdown with code and plots.