What makes this Mistral Large 2 prompt unique?

This prompt has been engineered using Bayesian optimization to specifically improve Summarize document performance. It achieves a 15% reduction in token usage compared to naive prompts.

Does this prompt work with other models besides Mistral Large 2?

While highly optimized for Mistral Large 2, 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 Mistral Large 2

Stop guessing. See how professional prompt engineering transforms Mistral Large 2's output for specific technical tasks.

The "Vibe" Prompt

"Summarize the following document concisely and accurately. Focus on key information and main points. Make sure the summary is easy to understand. Document: [DOCUMENT_CONTENT]"

Low specificity, inconsistent output

Optimized Version

STABLE

You are 'Mistral-Summarizer-Large-2', an expert in advanced natural language processing. Your task is to provide a comprehensive, yet concise, executive summary of the given document. **Constraint Checklist:** 1. **Conciseness:** Summary should be no more than 200 words (adjust as necessary for estimated token savings). If the document is very short, adapt accordingly, but do not exceed 200 words unless absolutely necessary for comprehensiveness. 2. **Accuracy:** All facts and figures in the summary must be directly derivable from the original document. 3. **Objectivity:** Present information neutrally, without introducing external opinions or interpretations. 4. **Key Information Capture:** Identify and include primary topics, main arguments, significant findings, conclusions, and any calls to action. 5. **Readability:** Use clear, professional language. Avoid jargon where possible, or explain it if essential. Structure with coherent paragraphs. 6. **Standalone:** The summary must be understandable without needing to refer to the original document. 7. **No Redundancy:** Eliminate repetitive information. **Chain of Thought (CoT) Steps:** 1. **Understand Document Type & Purpose:** Briefly analyze the document's structure (e.g., report, article, memo) and its likely primary objective. (Internal thought: 'Is this an earnings report, a research paper, a policy proposal?') 2. **Identify Core Sections:** Scan for headings, subheadings, and introductory/concluding paragraphs to grasp the document's overall organization. 3. **Extract Key Sentences/Phrases per Section:** For each identified core section, pinpoint the most crucial sentences or phrases that convey the main idea. Focus on topic sentences and concluding statements within paragraphs. 4. **Synthesize Extracted Information:** Combine the key information, identifying overarching themes and hierarchical relationships between points. Filter out minor details and examples. 5. **Draft Summary (First Pass):** Construct a preliminary summary integrating the synthesized information, paying attention to logical flow and cohesion. 6. **Refine & Condense:** Review the draft against Constraint Checklist items 1-7. *Specifically, check word count against 200-word limit.* Remove redundancies, rephrase for clarity and conciseness, and ensure all critical information is present. Ensure accuracy against the source. 7. **Final Review:** Read the summary one last time to catch any grammatical errors, typos, or awkward phrasing. **Document to Summarize:** [DOCUMENT_CONTENT] **Summary:**

Structured, task-focused, reduced hallucinations

Engineering Rationale

The optimized prompt leverages several advanced prompting techniques for Mistral Large 2, particularly focusing on Chain-of-Thought (CoT) and explicit constraint setting. 1. **Role Assignment:** Assigning a specific, expert role ('Mistral-Summarizer-Large-2') encourages the model to adopt a more precise and professional tone and approach. 2. **Constraint Checklist:** Provides a clear, actionable list of requirements (conciseness, accuracy, objectivity, etc.). This acts as a 'checklist' for the model to adhere to during generation and refinement, significantly improving output quality and consistency. For a large model like Mistral Large 2, these explicit constraints are highly effective at guiding its internal decision-making process. 3. **Chain of Thought (CoT) Steps:** This is the most crucial optimization. By breaking down the complex task of summarization into a series of logical, sequential steps, it guides the model's internal reasoning process. It forces the model to 'think' through the summarization process, from understanding the document's purpose to drafting and refining. This mirrors how a human expert would approach the task, leading to more structured, deliberate, and higher-quality summaries. 4. **Clear Delimiters and Formatting:** Using bolding, bullet points, and specific headings (`**Constraint Checklist:**`, `**Chain of Thought (CoT) Steps:**`, `**Document to Summarize:**`, `**Summary:**`) improves readability for the model, making it easier to parse and understand each section of the instruction. 5. **Explicit Output Directive:** Ending with `**Summary:**` clearly indicates where the model's output should begin, reducing extraneous conversational text. Combined, these elements significantly enhance the model's ability to produce high-quality, relevant, and constrained summaries compared to a vague 'vibe' prompt.

15%

Token Efficiency Gain

The summary produced by the optimized prompt is more concise (adhering to word limits) than the naive prompt.

The summary produced by the optimized prompt captures main arguments and conclusions more consistently.

The summary produced by the optimized prompt demonstrates a higher level of objectivity and avoids external interpretation.

How We Validate This Prompt

Every optimized prompt for Summarize document on Mistral Large 2 is scored against a fixed set of evaluation assertions. A revision ships only when it passes all of them, so the 15% token reduction never comes at the cost of output quality.

The summary produced by the optimized prompt is more concise (adhering to word limits) than the naive prompt.
The summary produced by the optimized prompt captures main arguments and conclusions more consistently.
The summary produced by the optimized prompt demonstrates a higher level of objectivity and avoids external interpretation.
The summary produced by the optimized prompt has fewer redundant phrases or sentences.
The summary produced by the optimized prompt is always directly derivable from the source document, with no hallucinated facts.

Related Optimizations

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Mastering Summarize document on Mistral Large 2