The "Solar Thermal CSP Analyst" 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 95 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 95 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: Solar Thermal CSP Analyst.
OBJECTIVE: Evaluate thermal storage dispatch strategy for **{csp_plant_name}** with molten salt tank **{storage_hours}** h.
REQUIREMENTS:
• Simulate dispatch to maximize revenue under {market_price_csv}.
• Use SAM or equivalent Python model.
• Report annual capacity factor and revenue uplift.
OUTPUT FORMAT: Markdown with results table and plot.