Enhance analysis quality: Improve prompts and system instructions for better insights

- Enhanced AnalysisAgent system prompt for sophisticated, actionable analysis
- Added comprehensive monetization analysis template with strategic focus
- Improved chunk processing prompts to maintain quality across large documents
- Enhanced hierarchical summarization with strategic business analysis focus
- Upgraded all prompts to provide deeper insights, specific recommendations, and strategic value
- Focus on quantifiable insights, implementation strategies, and business opportunities

agents.py

@@ -79,35 +79,38 @@ class AnalysisAgent(BaseAgent):
         # Use standard token allocation
         max_tokens = Config.OPENAI_MAX_TOKENS
         
-        system = """You are AnalysisAgent: produce stunning, visually rich, and highly engaging insights. 
+        system = """You are AnalysisAgent: an expert analyst who produces deeply insightful, actionable, and contextually relevant analysis.
 
-CRITICAL VISUAL FORMATTING REQUIREMENTS:
-- Use beautiful section headers with emojis and clear hierarchy
-- Create visually appealing bullet points with icons (• ✅ ❌ ⚠️ 💡 🎯 📊)
-- Use tables extensively for data comparison and organization
-- Include progress bars, metrics cards, and visual separators
-- Use **bold** for key concepts, numbers, and important data
-- Create infographic-style summaries with visual elements
-- Use color coding and visual hierarchy throughout
-- Include actionable insights with clear visual indicators
+ANALYSIS APPROACH:
+- Provide sophisticated, nuanced insights that go beyond surface-level observations
+- Identify underlying patterns, implications, and strategic opportunities
+- Connect concepts to real-world applications and business value
+- Offer specific, actionable recommendations with clear implementation paths
+- Consider multiple perspectives and potential challenges
+- Provide evidence-based conclusions with supporting rationale
 
-CONTENT REQUIREMENTS:
-- Be concise but comprehensive - every word counts
-- Use simple language with technical depth when needed
-- Include specific numbers, percentages, and metrics prominently
-- Provide clear next steps with visual callouts
-- Structure information for instant scanning and understanding
-- Focus on what matters most with visual emphasis
-- Create engaging, professional presentations
+CONTENT STRUCTURE:
+- Start with a compelling executive summary that captures the essence
+- Organize insights by strategic importance and implementation priority
+- Include specific examples, case studies, and concrete applications
+- Highlight unique opportunities and competitive advantages
+- Address potential risks, challenges, and mitigation strategies
+- Provide clear next steps with timelines and success metrics
 
-VISUAL ELEMENTS TO USE:
-- 📊 Data visualizations and metrics
-- 🎯 Key insights with visual emphasis
-- ✅ Success indicators and achievements
-- ⚠️ Important warnings and considerations
-- 💡 Actionable recommendations
-- 📈 Trends and comparisons
-- 🔍 Detailed analysis sections"""
+QUALITY STANDARDS:
+- Be precise and specific rather than generic
+- Include quantifiable insights where possible (ROI, market size, timelines)
+- Reference industry best practices and benchmarks
+- Consider scalability, feasibility, and resource requirements
+- Provide context for why recommendations matter
+- Connect analysis to broader market trends and opportunities
+
+FORMATTING:
+- Use clear headings with strategic focus
+- Include bullet points for easy scanning
+- Highlight key insights with **bold** text
+- Use emojis sparingly for visual appeal (🎯 💡 📊 ⚡ ✅)
+- Structure information by priority and actionability"""
         
         try:
             response = await call_openai_chat(
@@ -152,7 +155,28 @@ VISUAL ELEMENTS TO USE:
         metadata['total_chunks'] = len(chunks)
         chunk_results = []
         
-        system = "You are AnalysisAgent: produce concise insights and structured summaries. Adapt your language and complexity to the target audience. Provide clear, actionable insights with appropriate examples and analogies for complex topics."
+        system = """You are AnalysisAgent: an expert analyst producing sophisticated insights from document content.
+
+ANALYSIS APPROACH:
+- Provide deep, nuanced insights that identify underlying patterns and strategic opportunities
+- Connect concepts to real-world applications and business value
+- Offer specific, actionable recommendations with clear implementation paths
+- Consider multiple perspectives and potential challenges
+- Provide evidence-based conclusions with supporting rationale
+
+CHUNK ANALYSIS FOCUS:
+- Extract the most important insights from this specific section
+- Identify key concepts, data points, and implications
+- Note any unique opportunities or competitive advantages mentioned
+- Highlight specific examples, case studies, or applications
+- Consider how this content relates to broader strategic themes
+
+OUTPUT FORMAT:
+- Start with key insights from this chunk
+- Include specific examples and concrete applications
+- Note strategic implications and opportunities
+- Highlight any unique value propositions or competitive advantages
+- Keep analysis focused and actionable"""
         
         for i, chunk in enumerate(chunks):
             content = f"User prompt: {prompt}\n\nDocument chunk {i+1}/{len(chunks)}:\n{chunk}"

utils/__init__.py

@@ -189,7 +189,7 @@ async def create_hierarchical_summary(chunk_results: List[str], prompt: str, mod
             summary = await call_openai_chat(
                 model=model,
                 messages=[
-                    {"role": "system", "content": "You are a summarization expert. Create concise summaries that capture the most important insights."},
+                    {"role": "system", "content": "You are an expert analyst creating sophisticated summaries. Focus on:\n- Identifying strategic opportunities and competitive advantages\n- Extracting specific, actionable insights with real-world applications\n- Highlighting unique value propositions and market implications\n- Connecting insights to broader business themes and opportunities\n- Providing concrete examples and implementation considerations"},
                     {"role": "user", "content": group_prompt}
                 ],
                 temperature=0.2,
@@ -215,7 +215,7 @@ async def create_hierarchical_summary(chunk_results: List[str], prompt: str, mod
         final_summary = await call_openai_chat(
             model=model,
             messages=[
-                {"role": "system", "content": "You are an expert at creating comprehensive summaries from multiple sources. Synthesize the key insights into a coherent final summary."},
+                {"role": "system", "content": "You are a strategic business analyst creating comprehensive, actionable insights. Your final summary should:\n- Synthesize insights into a coherent strategic narrative\n- Prioritize opportunities by potential impact and feasibility\n- Provide specific, actionable recommendations with clear next steps\n- Include quantifiable insights where possible (market size, ROI, timelines)\n- Address implementation challenges and mitigation strategies\n- Connect all insights to create a unified strategic vision\n- Focus on what matters most for business success"},
                 {"role": "user", "content": final_prompt}
             ],
             temperature=0.2,

utils/prompts.py

@@ -44,6 +44,12 @@ class PromptManager:
             },
             
             # Business Documents
+            "monetization_analysis": {
+                "name": "💰 Monetization Strategy Analysis",
+                "description": "Deep analysis of monetization opportunities and strategies",
+                "template": "Analyze this document for monetization opportunities and provide strategic recommendations:\n\n## 🎯 Core Value Proposition\n- **Unique value**: What makes this monetizable?\n- **Target market**: Who would pay for this?\n- **Competitive advantage**: Why choose this over alternatives?\n- **Market timing**: Is the market ready for this?\n\n## 💰 Revenue Model Opportunities\n- **Direct monetization**: How to charge customers\n  - Subscription models and pricing tiers\n  - One-time purchases and licensing\n  - Usage-based pricing strategies\n- **Indirect monetization**: Adjacent revenue streams\n  - Data monetization opportunities\n  - Partnership and affiliate models\n  - Platform and ecosystem strategies\n\n## 📊 Market Analysis & Sizing\n- **Total Addressable Market (TAM)**: Overall market size\n- **Serviceable Addressable Market (SAM)**: Realistic target\n- **Serviceable Obtainable Market (SOM)**: Achievable share\n- **Market growth trends**: Is the market expanding?\n- **Customer segments**: Different user types and needs\n\n## 🚀 Implementation Strategy\n- **Go-to-market approach**: How to reach customers\n- **Pricing strategy**: Optimal pricing models\n- **Sales channels**: How to sell and distribute\n- **Partnership opportunities**: Strategic alliances\n- **Resource requirements**: What's needed to execute\n\n## ⚡ Quick Wins vs Long-term Plays\n- **Immediate opportunities**: Low-hanging fruit (0-6 months)\n- **Medium-term strategies**: Scalable approaches (6-18 months)\n- **Long-term vision**: Major market positions (18+ months)\n- **Implementation timeline**: Realistic milestones\n\n## ⚠️ Risk Assessment & Mitigation\n- **Market risks**: Competition, regulation, adoption\n- **Technical risks**: Implementation challenges\n- **Financial risks**: Investment requirements\n- **Mitigation strategies**: How to reduce risks\n\n## 📈 Success Metrics & KPIs\n- **Revenue targets**: Specific financial goals\n- **Customer metrics**: Acquisition, retention, growth\n- **Market metrics**: Market share, penetration\n- **Operational metrics**: Efficiency, scalability\n\n## 💡 Strategic Recommendations\n- **Priority ranking**: Which opportunities to pursue first\n- **Resource allocation**: Where to focus efforts\n- **Partnership strategy**: Who to work with\n- **Competitive positioning**: How to differentiate\n- **Next steps**: Specific actions to take",
+                "category": "business"
+            },
             "whitepaper_analysis": {
                 "name": "📄 Whitepaper Analysis",
                 "description": "Comprehensive analysis for whitepapers and research papers",