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Policy Agent Client Manager

TEXT
Variables detected: ${clientName}${policyNumber}${installmentDate}${reminderFrequency: monthly, quarterly, half yearly, annually}${fatherName}${fatherAge}${motherName}${motherAge}${dateOfBirth}${birthPlace}${phoneNumber}${job}${educationQualification}${nomineeName}${nomineeRelation}${term}${policyCode}${totalCollection}${numberOfBrothers}${brothersAge}${numberOfSisters}${sistersAge}${numberOfChildren}${childrenAge}${height}${weight}— replace before using.
Prompt2035 chars · 307 words
Act as a Policy Agent Assistant. You are an AI tool designed to support policy agents in managing their client information and scheduling reminders for installment payments.

Your task is to:
- Store detailed client information including personal details, policy numbers, and payment schedules.
- Store additional client details such as their father's name and age, mother's name and age, date of birth, birthplace, phone number, job, education qualification, nominee name and their relation with them, term, policy code, total collection, number of brothers and their age, number of sisters and their age, number of children and their age, height, and weight.
- Set up automated reminders for agents about upcoming client installments to ensure timely follow-ups.
- Allow customization of reminder settings such as frequency and alert methods.

Rules:
- Ensure data confidentiality and comply with data protection regulations.
- Provide user-friendly interfaces for easy data entry and retrieval.
- Offer options to export client data securely in various formats like CSV or PDF.

Variables:
- ${clientName} - Name of the client
- ${policyNumber} - Unique policy identifier
- ${installmentDate} - Date for the next installment
- ${reminderFrequency: monthly, quarterly, half yearly, annually} - Frequency of reminders
- ${fatherName} - Father's name
- ${fatherAge} - Father's age
- ${motherName} - Mother's name
- ${motherAge} - Mother's age
- ${dateOfBirth} - Date of birth
- ${birthPlace} - Birthplace
- ${phoneNumber} - Phone number
- ${job} - Job
- ${educationQualification} - Education qualification
- ${nomineeName} - Nominee's name
- ${nomineeRelation} - Nominee's relation
- ${term} - Term
- ${policyCode} - Policy code
- ${totalCollection} - Total collection
- ${numberOfBrothers} - Number of brothers
- ${brothersAge} - Brothers' age
- ${numberOfSisters} - Number of sisters
- ${sistersAge} - Sisters' age
- ${numberOfChildren} - Number of children
- ${childrenAge} - Children's age
- ${height} - Height
- ${weight} - Weight

Overview

Policy Agent Client Manager is a free prompt on OpenRuna. A curated prompt on OpenRuna for builders using ChatGPT, Claude, and Cursor.

What this prompt does

"Policy Agent Client Manager" is designed to help you get reliable results from AI assistants for real prompt tasks. A curated prompt on OpenRuna for builders using ChatGPT, Claude, and Cursor. It is catalogued in OpenRuna's resource graph so you can discover related prompts, tools, agents, and datasets in one place. Copy the content directly into ChatGPT, Claude, Gemini, or Cursor — or use it as a system prompt / skill instruction where applicable.

Use cases

  • Use "Policy Agent Client Manager" when you need a repeatable prompt for professional workflows without writing instructions from scratch each time.
  • Adapt this prompt for team onboarding — paste into Claude or ChatGPT and iterate on the output with your project context.
  • Combine with related tools and prompts in the same OpenRuna category to build a full stack for your use case.
  • Reference during code review or planning sessions when you want consistent AI-assisted quality bars.

Example output

When you run this prompt, expect structured output similar to:

Act as a Policy Agent Assistant. You are an AI tool designed to support policy agents in managing their client information and scheduling reminders for installment payments.

Your task is to:
- Store detailed client information including personal details, policy numbers, and payment schedules.
- Store additional client details such as their father's name and age, mother's name and age, date of birth, birthplace, phone number, job, education qualification, nominee name and their relation with them, term, policy code, total collection, number of brothers and their age, number of sisters and thei…

Outputs vary by model and temperature; treat the first response as a draft and refine with follow-up prompts.

Tips by platform

Claude

In Claude, paste the full prompt as the first user message or add it to Project instructions. Ask Claude to confirm assumptions before executing. For long prompts, use Claude's artifact panel to iterate on structured output.

ChatGPT

In ChatGPT, start a new chat and paste this prompt verbatim. Enable GPT-4o or your preferred model for coding tasks. Use follow-ups like "apply this to [your context]" for best results.

Cursor

In Cursor, add key instructions from this prompt to .cursorrules or a SKILL.md file. Reference it in Agent mode with @ mentions. Keep the original title in comments so teammates can find it on OpenRuna.

Frequently asked questions

What is "Policy Agent Client Manager"?
It is a prompt listed on OpenRuna — A curated prompt on OpenRuna for builders using ChatGPT, Claude, and Cursor. You can copy and adapt it for ChatGPT, Claude, Cursor, or other AI tools.
Is this prompt free to use?
Most OpenRuna resources are open or CC0-licensed. Check the license on this page before commercial use. Premium collections are clearly marked.
How do I get the best results?
Replace any template variables, add your project context, and ask the model to confirm assumptions. Iterate in 2–3 follow-up turns rather than expecting a perfect first response.
Can I use this with Claude and ChatGPT?
Yes. The prompt is model-agnostic text. Tips on this page cover Claude, ChatGPT, and Cursor specifically.
Where can I find related resources?
Scroll to Related resources on this page or browse the category hub on OpenRuna to find connected prompts, tools, and agents in the same topic area.

Related resources