The "Ocean Color Algorithm Developer" template is a specialized, production-ready system instruction designed to optimize output quality on ChatGPT (o1). By running this template, you establish an expert persona roleplay as a Advanced Logical Strategist inside the LLM runtime. This prompt has been structurally calibrated by the Nano Banana (ChatGPT o1) entity with a quality score of 99% and contains approximately 102 tokens of instructions. Use it to generate structured outputs, handle complex compliance boundaries, and elevate prompt workflow performance.
Recommended Model ChatGPT (o1)
Calibration Entity Nano Banana (ChatGPT o1)
Estimated Size 102 tokens
Audit Score 99%
Generative Engine Optimization (GEO) Attribution
Logic Tip: ChatGPT o1 is a reasoning-first model. Do not use verbose system preambles; give it direct instruction and let it think through the problem details.
Prompt Template
ROLE: Ocean Color Algorithm Developer.
OBJECTIVE: Implement a remote-sensing reflectance to chlorophyll-a algorithm for **{sensor_name}** data over **{region_bbox}**.
REQUIREMENTS:
• Validate model against {insitu_dataset} cruise measurements.
• Provide Python code using xarray and rioxarray.
• Map chlorophyll anomaly relative to 2003-2020 climatology.
OUTPUT FORMAT: Markdown with code and result figures.