What makes this Gemini 1.5 Pro prompt unique?

This prompt has been engineered using Bayesian optimization to specifically improve Summarize document performance. It achieves a 0% reduction in token usage compared to naive prompts.

Does this prompt work with other models besides Gemini 1.5 Pro?

While highly optimized for Gemini 1.5 Pro, the underlying structural patterns (identity enforcement, task delimitation) are highly effective across most frontier models including GPT-4 and Llama 3.

How do I use this optimized template?

You can copy the "Optimized Version" directly into your application code or use the "Optimize with this synthesis" button to import it into our managed optimizer environment.

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Prompt Engineering Guide

Mastering Summarize document
on Gemini 1.5 Pro

Stop guessing. See how professional prompt engineering transforms Gemini 1.5 Pro's output for specific technical tasks.

The "Vibe" Prompt

"Summarize this document for me."

Low specificity, inconsistent output

Optimized Version

STABLE

Please act as an expert summarizer. Your goal is to provide a concise, accurate, and comprehensive summary of the provided document. Prioritize key facts, conclusions, and any actionable insights. The summary should be approximately 3-5 sentences long, unless the document is exceptionally long, in which case you may extend to 7 sentences. Do not introduce new information or opinions. Present the summary directly without conversational filler. Here is the document: [DOCUMENT_CONTENT] Summary:

Structured, task-focused, reduced hallucinations

Engineering Rationale

The optimized prompt provides clear instructions on the role, goal, desired length (with a flexible range), key information to prioritize, constraints (no new info/opinions), and output format (direct summary). This structured approach reduces ambiguity and guides the model towards generating a higher-quality, more consistent summary. The 'expert summarizer' role prompt and the call for 'actionable insights' also nudge the model towards more insightful outputs. The chain-of-thought isn't explicitly 'chain-of-thought' in the typical sense of breaking down a complex problem into steps, but rather guiding the *output generation process* with detailed instructions that lead to a better summary.

Token Efficiency Gain

The optimized prompt consistently produces summaries that are within the specified sentence length range for typical documents.

The optimized prompt's summaries are more likely to contain actionable insights when present in the document compared to the naive prompt.

The optimized prompt's summaries are less likely to include conversational filler or introduce external information.

How We Validate This Prompt

Every optimized prompt for Summarize document on Gemini 1.5 Pro is scored against a fixed set of evaluation assertions. A revision ships only when it passes all of them, so the 0% token reduction never comes at the cost of output quality.

The optimized prompt consistently produces summaries that are within the specified sentence length range for typical documents.
The optimized prompt's summaries are more likely to contain actionable insights when present in the document compared to the naive prompt.
The optimized prompt's summaries are less likely to include conversational filler or introduce external information.
The optimized prompt consistently provides a more 'comprehensive' summary as defined by covering key facts and conclusions than the naive prompt.

Related Optimizations

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Optimize your own Summarize document prompt

Run any prompt through the same optimizer that produced this Gemini 1.5 Pro guide — clarity, structure, and token efficiency in one pass.

Open the Optimizer

Mastering Summarize document on Gemini 1.5 Pro