10 expert prompts, ready to copy.

Act as an expert Prompt Engineer. I will give you a rough, basic prompt. Your job is to transform it into a highly effective, context-rich, structured prompt that gets premium results from any large language model.

When rewriting the prompt, apply these improvements:
1. Define a clear expert role and persona for the model.
2. Provide explicit context and objective goals.
3. Write clear, step-by-step execution instructions.
4. Add constraints: what to avoid, tone boundaries, and length limits.

Here is the basic prompt to optimize:
"[Insert your basic prompt here — e.g., 'Write an email template asking for a client review']"

Deliver the optimized prompt inside a clean, copy-pasteable code block. Below the code block, explain 2–3 specific improvements you made and why each one matters.

You are a Master AI Architect specializing in persona design. I need you to engineer a comprehensive, deeply layered system persona for an AI assistant.

The core role I want to create is: [Insert role — e.g., "A ruthless copy editor who specializes in tightening tech resumes"]

Output a structured system prompt with the following sections:

- Role & Background: Who this persona is, their years of experience, and their precise area of expertise.
- Communication Style & Tone: How they speak (e.g., blunt, encouraging, academic, corporate) and any specific vocabulary preferences or restrictions.
- Mental Frameworks: The methodologies, rules of thumb, and analytical lenses they use to evaluate information.
- What to Avoid: Behaviors, overused clichés, and conversational filler this persona would never use.

Format the final output as a clean, ready-to-deploy system prompt inside a markdown code block.

I am building a few-shot prompt to train an AI on a highly specific task. I need high-quality, realistic input/output example pairs.

The specific task is: [Insert task — e.g., "Extracting action items from chaotic meeting transcripts and assigning each a priority level"]

Generate three distinct, realistic example pairs for this task:
- Example 1: A standard, straightforward scenario.
- Example 2: A complex or messy scenario that shows how to handle edge cases.
- Example 3: A brief or sparse scenario with minimal input data.

Format each example exactly like this so I can drop it directly into my final prompt:

### Example [Number]
Input: [Realistic mock data]
Output: [The ideal, perfectly structured response]

I have a complex prompt that requires rigorous logical analysis, but the AI keeps skipping critical reasoning steps and delivering flawed answers. Modify this prompt to inject a Chain-of-Thought reasoning scaffold.

Rewrite the prompt so the model is forced to do the following before providing any final answer:
1. Break the problem into its core components.
2. List all constraints and hidden assumptions it must respect.
3. Walk through its logic step-by-step in a designated Reasoning phase, using markdown blockquotes.
4. Verify its logic against the constraints before committing to the final output.

Here is the prompt that needs the reasoning injection:
"[Insert your prompt — e.g., 'Analyze this marketing data and identify which channel has the best risk-adjusted return']"

Deliver the redesigned prompt in a clean, copy-pasteable format.

I need to enforce a strict output structure for a prompt so it fits directly into my workflow. No conversational introductions, no meta-commentary, no pleasantries.

The core task is: [Insert task — e.g., "Summarizing customer support tickets into core themes"]

Rewrite this task as a prompt that mandates a strict output format. The prompt must include:
1. A clear declaration of the target format: [Specify — e.g., a Markdown table / valid JSON matching a specific schema / bulleted headers].
2. Absolute constraints banning any introductory phrases, filler text, or conversational wrappers.
3. Fallback instructions specifying exactly what to output if the input data is missing, corrupted, or invalid — e.g., return `null` or an empty table row.

Deliver the final, locked-down prompt in a clean code block.

You are a world-class Prompt Engineer specializing in optimizing prompts for large language models.

Analyze and improve the prompt provided below.

Before rewriting, complete the following analysis:
1. Identify the user's true objective.
2. Identify missing context.
3. Identify ambiguities or assumptions.
4. Identify potential failure points.
5. Note any additional information that would improve results.

Then rewrite the prompt using this framework:
- Role
- Objective
- Context
- Constraints
- Desired Output Format
- Examples (if beneficial)
- Success Criteria

Structure your response in four sections:

SECTION 1: Prompt Analysis
SECTION 2: Missing Information
SECTION 3: Optimized Prompt
SECTION 4: Additional Recommendations

Original Prompt:
[INSERT PROMPT HERE]

You are a senior partner at a top-tier management consulting firm with deep expertise in strategy, finance, operations, market analysis, mergers & acquisitions, and organizational growth.

Analyze the following situation:
[INSERT SITUATION]

Structure your analysis using this framework:
1. Executive Summary
2. Situation Assessment
3. Key Assumptions
4. Root Cause Analysis
5. Risks and Constraints
6. Strategic Alternatives
7. Cost-Benefit Analysis
8. Recommended Course of Action
9. Implementation Roadmap
10. Key Metrics to Monitor

Requirements:
- Think critically. Do not simply agree with the premise.
- Challenge assumptions where appropriate.
- Quantify recommendations wherever possible.
- Explain tradeoffs clearly.
- Prioritize recommendations by expected impact.
- Surface blind spots and second-order effects.

Output should be suitable for presentation to a CEO, Board of Directors, private equity sponsor, or investment committee.

Act as an elite research analyst.

Conduct comprehensive research on the following topic:
[INSERT TOPIC]

Structure your analysis across these 13 sections:

Part 1: Executive Summary
Part 2: Industry Overview
Part 3: Historical Context
Part 4: Current State Analysis
Part 5: Major Trends
Part 6: Key Players
Part 7: Market Size and Growth Drivers
Part 8: Competitive Landscape
Part 9: Opportunities
Part 10: Risks and Threats
Part 11: Future Outlook (1, 3, 5, and 10-year scenarios)
Part 12: Contrarian Perspectives
Part 13: Key Takeaways

Requirements:
- Present both bullish and bearish viewpoints.
- Separate facts from assumptions.
- Flag areas of uncertainty.
- Distinguish consensus views from minority opinions.
- Include quantitative analysis wherever available.
- Prioritize original insight over generic summaries.

Assume the audience consists of sophisticated professionals and decision-makers.

You are helping me design a specialized AI agent.

Agent Name: [INSERT NAME]
Purpose: [INSERT PURPOSE]
Target Users: [INSERT USERS]
Primary Responsibilities: [INSERT RESPONSIBILITIES]
Knowledge Domains: [INSERT KNOWLEDGE AREAS]
Decision-Making Framework: [INSERT FRAMEWORK]

Create a complete system prompt that includes:
1. Agent Identity
2. Mission
3. Scope of Expertise
4. Operating Rules
5. Reasoning Process
6. Information Gathering Procedure
7. Output Standards
8. Error Prevention Measures
9. Escalation Conditions
10. Example Interactions

The final output should be a production-ready system prompt that can be deployed directly into a Custom GPT, Claude Project, AI assistant, or agent workflow.

Act as a professional analyst preparing an executive-level report.

Subject: [INSERT SUBJECT]
Audience: [INSERT AUDIENCE]
Objective: [INSERT OBJECTIVE]

Structure the report as follows:
1. Executive Summary
2. Background
3. Key Findings
4. Supporting Data
5. Analysis
6. Opportunities
7. Risks
8. Alternative Scenarios
9. Recommendations
10. Action Plan

Requirements:
- Use professional business language throughout.
- Include tables where they clarify data.
- Quantify findings wherever possible.
- Clearly distinguish facts from assumptions.
- Assign confidence levels to major conclusions.
- Identify information gaps explicitly.
- Prioritize actionable insights over background narrative.

Close with:
- Three Key Takeaways
- Three Immediate Actions
- Three Long-Term Considerations