Agent Prompt Vault — 50 Production Prompts for AI Agents

Stop engineering prompts from scratch. This vault contains 50 battle-tested system prompts organized across 6 categories: operations, sales, content, research, customer support, and developer tools. Each prompt includes model recommendations (Claude vs. Groq cost/quality tradeoffs), expected output formats, real-world cost estimates, and examples of good and bad outputs. Copy-paste into CrewAI, LangChain, LangGraph, or feed directly to any LLM API. Use as-is or customize with your company context.

What You Get

• Operations Prompts (10) — Ticket classification, workflow optimization, meeting summarization, expense approval, inventory management, shift scheduling, data migration, compliance checking, error handling, capacity planning
• Sales Prompts (8) — Lead qualification, outreach email generation, objection handling, deal closing, contract analysis, pricing recommendations, competitive research, customer segmentation
• Content Prompts (10) — Blog post generation, newsletter design, social media captions, video scripts, whitepaper outlines, case study writing, product descriptions, press releases, landing pages, content repurposing
• Research Prompts (7) — Market trend analysis, competitive intelligence gathering, customer research interviews, sentiment analysis, data synthesis, report generation, patent research
• Customer Support Prompts (8) — FAQ generation, escalation identification, response templates, sentiment detection, troubleshooting guides, refund evaluation, NPS analysis, churn prediction
• Developer Tools Prompts (7) — Code review, bug analysis, documentation generation, SQL optimization, test case generation, architecture design, refactoring suggestions

How to Use

1. Download and extract the vault (50 prompt files + INDEX.md)
2. Open INDEX.md to find a prompt matching your use case
3. Read the prompt file — it includes: instructions, output format, quality standards, model recommendation, cost estimate
4. Copy the prompt text into your agent system prompt OR pass to LLM directly
5. Customize variables: replace {{COMPANY_NAME}}, {{PRODUCT}}, {{INDUSTRY}} with your context
6. Choose recommended model: Claude for quality (higher cost), Groq for speed (faster, cheaper)
7. Test with sample data and iterate based on results

Who This Is For

• AI engineers building multi-agent systems without prompt expertise
• Startup teams implementing business automation quickly
• Enterprises scaling AI across multiple departments
• Developers adding AI features to products
• Anyone needing production-ready prompts without trial-and-error

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