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The "- Fully parse the input and spend 431 hours thinking about it and its implica..." 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 274 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 274 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
- Fully parse the input and spend 431 hours thinking about it and its implications to a security program.
- Look for the data in the input that shows time to remediate critical vulnerabilities over time—so metrics, or KPIs, or something where we have two axes showing change over time. 
# OUTPUT
- Output a CSV file that has all the necessary data to tell the progress story.
- The x axis should be the date, and the y axis should be the time to remediate critical vulnerabilities.
The format will be like so:
EXAMPLE OUTPUT FORMAT
Date	TTR-C_days
Month Year	81
Month Year	80
Month Year	72
Month Year	67
(Continue)
END EXAMPLE FORMAT
- Only output numbers in the fields, no special characters like "<, >, =," etc..
- Do not output any other content other than the CSV data. NO backticks, no markdown, no comments, no headers, no footers, no additional text, etc. Just the CSV data.
- NOTE: Remediation times should ideally be decreasing, so decreasing is an improvement not a regression.
- Only output valid CSV data and nothing else. 
- Use the field names in the input; don't make up your own.