Complete Execution Output (JSON):
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"ai_response": "{\n \"contact_email\": \"michael.johnson@email.com\",\n \"subject\": \"RE: Case #00001943 - Credit card dispute update\",\n \"email_body\": \"Hi, I\u0027m following up on my dispute case #00001943. I submitted the documents you requested last week but haven\u0027t heard back. The disputed amount of $1,299.99 is still showing on my statement. Can you please provide an update on the investigation status? This is urgent as my payment is due soon. Thanks, Michael\",\n \"case_number\": \"00001943\"\n}",
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"system_message": "\u003cpurpose\u003e\nYou are an AI assistant that manages critical Salesforce cases by analyzing customer emails. Your accuracy directly impacts customer satisfaction and banking security. This is very important work.\n\u003c/purpose\u003e\n\n\u003cworkflow\u003e\n1. Analyze incoming customer emails to extract the EXACT information requested\n2. Check if the email references an existing case number \n3. If a case number exists, retrieve the case using get_case()\n4. If no case number exists, create a new case using create_case()\n\u003c/workflow\u003e\n\n\u003cdata_extraction\u003e\nFor all emails, extract PRECISELY:\n- contact_email: Extract ONLY the email address from the sender field - this is CRITICAL for customer communication, DO NOT USE \"Unknown or anything else\". There is always a customer email address.\n- subject: Extract the exact subject line, without modification\n- email_body: Use the complete content of the email\n\nFor existing cases, extract:\n- case_number: Identify case number patterns in email body or subject (formats: #######, Case:#####, Case #####, etc.)\n\nFor new cases, extract:\n- disputed_amount: Extract amount ONLY if explicitly disputed or incorrectly charged (format: numeric value only, e.g., 899.99). For non-financial issues or cases without disputed amounts, set to None.\n- description: Create a concise 1-2 sentence summary focusing on the main issue\n\u003c/data_extraction\u003e\n\n\u003cguidelines\u003e\n- Your extraction accuracy DIRECTLY impacts customer finances and trust - this is CRUCIAL work\n- ALWAYS extract the EXACT email address from the sender field - this is vital for customer communication\n- NEVER fabricate or assume information that isn\u0027t in the email\n- Only include disputed_amount when an actual financial dispute or incorrect charge is mentioned\n- Set disputed_amount to None for non-financial issues (login problems, technical issues, etc.)\n- Verify your extraction against the raw data before finalizing to prevent errors\n- For financial matters, pay extra careful attention to amounts and account details\n- Take pride in your accurate extractions - each one helps a real customer with a real problem\n- Double-check account numbers against the original email for absolute accuracy\n\u003c/guidelines\u003e\n\n\u003cquality_check\u003e\nBefore finalizing your extraction, pause and verify:\n1. Have I extracted the EXACT email address from the sender field?\n2. Have I included ONLY disputed amounts when explicitly mentioned?\n3. Does my description accurately summarize the main issue without adding assumptions?\n4. Have I missed any critical account information provided in the email?\n\nCustomers are depending on your accuracy. Are you confident in your extraction?\n\u003c/quality_check\u003e\n"
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"output": "{\n \"contact_email\": \"michael.johnson@email.com\",\n \"subject\": \"RE: Case #00001943 - Credit card dispute update\",\n \"email_body\": \"Hi, I\u0027m following up on my dispute case #00001943. I submitted the documents you requested last week but haven\u0027t heard back. The disputed amount of $1,299.99 is still showing on my statement. Can you please provide an update on the investigation status? This is urgent as my payment is due soon. Thanks, Michael\",\n \"case_number\": \"00001943\"\n}\n__OUTPUTS__ {\"ai_response\": \"{\\n \\\"contact_email\\\": \\\"michael.johnson@email.com\\\",\\n \\\"subject\\\": \\\"RE: Case #00001943 - Credit card dispute update\\\",\\n \\\"email_body\\\": \\\"Hi, I\u0027m following up on my dispute case #00001943. I submitted the documents you requested last week but haven\u0027t heard back. The disputed amount of $1,299.99 is still showing on my statement. Can you please provide an update on the investigation status? This is urgent as my payment is due soon. Thanks, Michael\\\",\\n \\\"case_number\\\": \\\"00001943\\\"\\n}\", \"model_client_id\": \"openrouter_claude_sonnet\", \"agent_type\": \"assistant\", \"model\": \"gpt-4.1-2025-04-14\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 4269, \"completion_tokens\": 161, \"total_tokens\": 4430, \"estimated_cost\": {\"amount\": 0.13773, \"currency\": \"USD\"}, \"model\": \"gpt-4.1-2025-04-14\", \"provider\": \"openai\"}}",
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"output": "{\n \"contact_email\": \"michael.johnson@email.com\",\n \"subject\": \"RE: Case #00001943 - Credit card dispute update\",\n \"email_body\": \"Hi, I\u0027m following up on my dispute case #00001943. I submitted the documents you requested last week but haven\u0027t heard back. The disputed amount of $1,299.99 is still showing on my statement. Can you please provide an update on the investigation status? This is urgent as my payment is due soon. Thanks, Michael\",\n \"case_number\": \"00001943\"\n}\n__OUTPUTS__ {\"ai_response\": \"{\\n \\\"contact_email\\\": \\\"michael.johnson@email.com\\\",\\n \\\"subject\\\": \\\"RE: Case #00001943 - Credit card dispute update\\\",\\n \\\"email_body\\\": \\\"Hi, I\u0027m following up on my dispute case #00001943. I submitted the documents you requested last week but haven\u0027t heard back. The disputed amount of $1,299.99 is still showing on my statement. Can you please provide an update on the investigation status? This is urgent as my payment is due soon. Thanks, Michael\\\",\\n \\\"case_number\\\": \\\"00001943\\\"\\n}\", \"model_client_id\": \"openrouter_claude_sonnet\", \"agent_type\": \"assistant\", \"model\": \"gpt-4.1-2025-04-14\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 4269, \"completion_tokens\": 161, \"total_tokens\": 4430, \"estimated_cost\": {\"amount\": 0.13773, \"currency\": \"USD\"}, \"model\": \"gpt-4.1-2025-04-14\", \"provider\": \"openai\"}}",
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"ai_response": "{\n \"classification\": {\n \"priority\": \"High\",\n \"tags\": [\"Dispute Related\", \"Transaction Issues\"],\n \"justification\": \"The email concerns a credit card dispute involving a significant amount ($1,299.99) and requests an urgent update as the payment due date is approaching. While the customer emphasizes urgency, there is no indication of immediate financial loss, fraud, or security breach, so \u0027High\u0027 priority is appropriate. The tags \u0027Dispute Related\u0027 and \u0027Transaction Issues\u0027 are assigned based on the dispute and ongoing transaction concern.\",\n \"confidence_score\": 0.95\n }\n}",
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"system_message": "You are an AI assistant tasked with classifying customer emails for a financial institution. Your\ngoal is to determine the priority level and assign appropriate tags to each email based on its\ncontent.\n\nClassify the email and return ONLY a JSON response in this exact format:\n\n{\n \"classification\": {\n \"priority\": \"High\",\n \"tags\": [\"Dispute Related\", \"Transaction Issues\"],\n \"justification\": \"Explanation for classification\",\n \"confidence_score\": 0.95\n }\n}\n\nPriority levels: \"Urgent\", \"High\", \"Medium\", \"Low\"\n\nUrgent Priority:\n- Immediate attention required (response needed within hours)\n- Potential financial loss or security breach involved\n- System-wide issues affecting multiple customers\n- Keywords: \"unauthorized transaction\", \"fraud alert\", \"suspicious activity\", \"account compromised\", \"identity theft\", \"money stolen\", \"security breach\", \"system down\", \"service outage\", \"cannot access account\", \"urgent assistance required\", \"significant financial loss\", \"emergency assistance\"\n\nHigh Priority:\n- Response needed within 24 hours\n- Individual customer account issues\n- Specific transaction disputes\n- Keywords: \"account locked\", \"account freeze\", \"access denied\", \"login problems\", \"failed transfer\", \"payment rejection\", \"dispute\", \"chargeback\", \"billing error\", \"service unavailable\", \"app not working\", \"immediate response required\"\n\nMedium Priority:\n- Response needed within 48 hours\n- General account inquiries requiring research\n- Non-urgent service requests\n- Keywords: \"account inquiry\", \"balance discrepancy\", \"statement request\", \"loan information\", \"interest rates\", \"change request\", \"service upgrade\", \"clarification needed\"\n\nLow Priority:\n- Response needed within 72 hours\n- General information requests\n- Documentation requests\n- Keywords: \"information about\", \"how to\", \"general question\", \"documentation request\", \"product features\", \"explanation needed\", \"suggestion\", \"feedback\"\n\nCommon tags:\n- Fraud Alert/Report: Unauthorized transactions, suspicious activities, security concerns\n- Dispute Related: Transaction disputes, charge disagreements, service quality issues\n- Compliance/Regulatory: Regulatory reporting, compliance inquiries, policy matters\n- Transaction Issues: Failed transactions, payment problems, processing errors\n- Technical Support: System access, online banking problems, app issues\n- Account Services: Account maintenance, balance inquiries, statement requests\n- Loan Related: Loan applications, payment issues, modification requests\n- General Inquiry: Product information, service information, documentation requests\n\nRemember to analyze the email content thoroughly and assign multiple tags if applicable.\n"
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"output": "{\n \"classification\": {\n \"priority\": \"High\",\n \"tags\": [\"Dispute Related\", \"Transaction Issues\"],\n \"justification\": \"The email concerns a credit card dispute involving a significant amount ($1,299.99) and requests an urgent update as the payment due date is approaching. While the customer emphasizes urgency, there is no indication of immediate financial loss, fraud, or security breach, so \u0027High\u0027 priority is appropriate. The tags \u0027Dispute Related\u0027 and \u0027Transaction Issues\u0027 are assigned based on the dispute and ongoing transaction concern.\",\n \"confidence_score\": 0.95\n }\n}\n__OUTPUTS__ {\"ai_response\": \"{\\n \\\"classification\\\": {\\n \\\"priority\\\": \\\"High\\\",\\n \\\"tags\\\": [\\\"Dispute Related\\\", \\\"Transaction Issues\\\"],\\n \\\"justification\\\": \\\"The email concerns a credit card dispute involving a significant amount ($1,299.99) and requests an urgent update as the payment due date is approaching. While the customer emphasizes urgency, there is no indication of immediate financial loss, fraud, or security breach, so \u0027High\u0027 priority is appropriate. The tags \u0027Dispute Related\u0027 and \u0027Transaction Issues\u0027 are assigned based on the dispute and ongoing transaction concern.\\\",\\n \\\"confidence_score\\\": 0.95\\n }\\n}\", \"model_client_id\": \"gpt4_primary\", \"agent_type\": \"assistant\", \"model\": \"gpt-4.1-2025-04-14\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 809, \"completion_tokens\": 128, \"total_tokens\": 937, \"estimated_cost\": {\"amount\": 0.03195, \"currency\": \"USD\"}, \"model\": \"gpt-4.1-2025-04-14\", \"provider\": \"openai\"}}",
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"output": "{\n \"classification\": {\n \"priority\": \"High\",\n \"tags\": [\"Dispute Related\", \"Transaction Issues\"],\n \"justification\": \"The email concerns a credit card dispute involving a significant amount ($1,299.99) and requests an urgent update as the payment due date is approaching. While the customer emphasizes urgency, there is no indication of immediate financial loss, fraud, or security breach, so \u0027High\u0027 priority is appropriate. The tags \u0027Dispute Related\u0027 and \u0027Transaction Issues\u0027 are assigned based on the dispute and ongoing transaction concern.\",\n \"confidence_score\": 0.95\n }\n}\n__OUTPUTS__ {\"ai_response\": \"{\\n \\\"classification\\\": {\\n \\\"priority\\\": \\\"High\\\",\\n \\\"tags\\\": [\\\"Dispute Related\\\", \\\"Transaction Issues\\\"],\\n \\\"justification\\\": \\\"The email concerns a credit card dispute involving a significant amount ($1,299.99) and requests an urgent update as the payment due date is approaching. While the customer emphasizes urgency, there is no indication of immediate financial loss, fraud, or security breach, so \u0027High\u0027 priority is appropriate. The tags \u0027Dispute Related\u0027 and \u0027Transaction Issues\u0027 are assigned based on the dispute and ongoing transaction concern.\\\",\\n \\\"confidence_score\\\": 0.95\\n }\\n}\", \"model_client_id\": \"gpt4_primary\", \"agent_type\": \"assistant\", \"model\": \"gpt-4.1-2025-04-14\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 809, \"completion_tokens\": 128, \"total_tokens\": 937, \"estimated_cost\": {\"amount\": 0.03195, \"currency\": \"USD\"}, \"model\": \"gpt-4.1-2025-04-14\", \"provider\": \"openai\"}}",
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"system_message": "# Email Response Generation Agent\n\nYou are an AI banking email response agent responsible for generating appropriate, empathetic, and solution-oriented responses to customer emails. You will synthesize information from previous agents in the workflow and generate response emails based on the case status.\n\n\u003cagent_purpose\u003e\nGenerate professional email responses for customer inquiries based on the status of their request (resolved, followup, or rejected). You will extract context from previous agents and format responses according to the bank\u0027s guidelines.\n\u003c/agent_purpose\u003e\n\n\u003cresponse_types\u003e\nYou must generate responses for exactly three types of statuses:\n\n1. **Resolved** - When the customer\u0027s issue has been completely addressed\n2. **Followup** - When the issue is being worked on but requires more time\n3. **Rejected** - When the request cannot be fulfilled\n\u003c/response_types\u003e\n\n\u003cinformation_collection\u003e\nBefore generating a response:\n- Extract all relevant context from previous agents in the workflow, particularly the case_context_agent\n- Extract necessary information from the sentiment_analysis_agent and classification_agent\n- Identify the case_number from the case_context_agent messages\n- Identify customer details (name, account information, request type)\n- Understand the specific actions taken or reasons for the current status\n- Note any timeline commitments or next steps\n\u003c/information_collection\u003e\n\n\u003cresponse_structure\u003e\nAll responses must include:\n- Professional greeting with customer name when available\n- Clear reference to the specific request/case number\n- Status-appropriate explanation [1-2 sentences]\n- Next steps (if any) [As bullet points]\n- Professional closing [1-2 Sentences]\n- Signature\n\u003c/response_structure\u003e\n\n\u003cstatus_specific_content\u003e\n**For Resolved Status:**\n- Confirmation of completion\n- Specific details of the resolution\n- Timeline for any pending actions\n- Instructions for verification (if applicable)\n- Invitation for additional questions\n\n**For Followup Status:**\n- Current status update\n- Explanation of ongoing work\n- Bullet points of actions being taken\n- Expected resolution timeline\n- Request for additional information (if needed)\n- Appreciation for patience\n\n**For Rejected Status:**\n- Clear but empathetic statement of rejection\n- Specific reason(s) for rejection\n- Alternative solutions or recommendations\n- Required steps to resubmit (if applicable)\n- Contact information for appeals or questions\n\u003c/status_specific_content\u003e\n\n\u003ctone_guidelines\u003e\n- **Sentiment Adaptation:** Adjust tone based on the customer\u0027s sentiment and situation\n- **Professional Empathy:** Maintain professional tone while showing appropriate empathy\n- **Clarity:** Use clear, concise language without jargon\n- **Solution Focus:** Emphasize solutions over problems\n- **Brand Consistency:** Maintain the bank\u0027s voice and values\n\u003c/tone_guidelines\u003e\n\n\u003csignature\u003e\nRegards,\nCustomer Support Team,\nQuinte FT\n\u003c/signature\u003e\n\n\u003cresponse_json_structure\u003e\nPrepare your responses in JSON format as follows:\n```json\n{\n \"templates\": [\n {\n \"id\": \"TEMP001\",\n \"subject\": \"[Case Number] [Appropriate Subject]\",\n \"type\": \"resolved\",\n \"content\": \"\\nDear [Customer Name],\\n\\n[Status-appropriate Email Body]\\n\\n[signature]\"\n },\n {\n \"id\": \"TEMP002\",\n \"subject\": \"[Case Number] [Appropriate Subject]\",\n \"type\": \"followup\",\n \"content\": \"\\nDear [Customer Name],\\n\\n[Status-appropriate Email Body]\\n\\n[signature]\"\n },\n {\n \"id\": \"TEMP003\",\n \"subject\": \"[Case Number] [Appropriate Subject]\",\n \"type\": \"rejected\",\n \"content\": \"\\nDear [Customer Name],\\n\\n[Status-appropriate Email Body]\\n\\n[signature]\"\n }\n ]\n}\n```\n\u003c/response_json_structure\u003e\n\n\u003cupdate_function\u003e\nAfter generating the email templates, you must call the update_case function to update the generated emails in the Salesforce case.\n\nFunction signature:\n```\nupdate_case(case_number, email_content)\n```\n\nWhere:\n- case_number: The case number extracted from case_context_agent messages\n- email_content: the dictionary of email templates\n\u003c/update_function\u003e\n\n\u003csecurity_and_compliance\u003e\n- Never include full account numbers\n- Avoid including sensitive personal information\n- Ensure all regulatory requirements are met\n- Include appropriate disclaimers when necessary\n- Direct customers to secure channels for sensitive information\n- DO NOT ADD ANY BANK ADDITIONAL CONTACT INFORMATION NOT SPECIFIED IN THE SIGNATURE\n\u003c/security_and_compliance\u003e\n\n\u003cexecution_steps\u003e\n1. Extract the case_number from previous agent messages\n2. Generate all three email templates (resolved, followup, rejected)\n3. Format templates according to the JSON structure provided\n4. Call update_case(case_number, email_content) to store the templates\n5. Return confirmation of successful updates\n6. Utilize the provided interest_rate_context where applicable\n\u003c/execution_steps\u003e\n\n\u003cexamples\u003e\nInterest Rates Query:\nStatus: Resolved\n---\nThank you for contacting Quinte FT Bank. To confirm, the statement cycle for [Month] was a total of [x] days, from [xx/xx/xx - xx/xx/xx]. The current Annual Percentage Yield (APY) on your account is [x.xx%] and the interest rate is [x.xx%]. Rates are subject to change any time at the Bank\u0027s discretion.\n\nYour monthly statement will include the total interest accrued during the cycle dates above. You can access your monthly statement from the app or in online banking following the steps below:\n\n\u2022 Click the Accounts tab.\n\u2022 Click your account.\n\u2022 Click the Statements/Tax Forms tab.\n\u2022 Select View on your monthly statement. \n\n\u003csignature\u003e\u003c/signature\u003e\n---\n\u003c/examples\u003e\n\n\u003cinterest_rate_context\u003e\nHigh-Yield Savings Account Options:\n\nPremium Plus Savings: 4.85% APY (4.75% interest rate)\nElite Savings Account: 4.65% APY (4.55% interest rate)\nDigital Advantage Savings: 4.50% APY (4.41% interest rate)\nHigh-Yield Ultimate: 4.35% APY (4.26% interest rate)\nPerformance Savings: 4.25% APY (4.16% interest rate)\nDirect Deposit Savings: 4.15% APY (4.07% interest rate)\nOnline Priority Savings: 4.05% APY (3.97% interest rate)\n\nPromotional/Limited Time Offers:\n\nNew Customer Welcome: 5.00% APY (4.89% interest rate) for first 3 months\nBalance Booster: 4.75% APY (4.65% interest rate) on balances over $25,000\nLoyalty Reward Savings: 4.50% APY (4.41% interest rate) for customers of 5+ years\n\u003c/interest_rate_context\u003e\n\nAfter completion, say RESPONSE_GENERATION_COMPLETED\n"
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"system_message": "You are a specialized banking email sentiment analysis agent. Analyze the customer email and return ONLY a JSON response:\n\n{\n \"sentiment_score\": -0.4,\n \"primary_tone\": \"Concerned\",\n \"emotional_indicators\": {\n \"frustration_level\": \"Medium\",\n \"satisfaction\": \"Low\"\n },\n \"context_notes\": \"Brief explanation of emotional state and key indicators\"\n}\n\nAnalysis Guidelines:\n\n1. SENTIMENT SCORE (-1.0 to 1.0):\n- -1.0 to -0.7: Extremely Negative\n- -0.7 to -0.3: Moderately Negative \n- -0.3 to 0.3: Neutral\n- 0.3 to 0.7: Moderately Positive\n- 0.7 to 1.0: Extremely Positive\n\n2. PRIMARY TONE:\n- Angry: Strong negative emotions, demands, threats\n- Frustrated: Expressions of difficulty, repeated issues\n- Concerned: Worry about specific issues\n- Neutral: Factual, straightforward communication\n- Satisfied: Content with service/resolution\n- Appreciative: Explicit gratitude, praise\n- Mixed: Multiple distinct emotional tones present\n\n3. EMOTIONAL INDICATORS:\nFrustration Level: None, Low, Medium, High\nSatisfaction: Very Low, Low, Neutral, High, Very High, Mixed\n\nConsider banking context: financial concerns, security issues, service quality, technical problems, regulatory matters.\n"
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"output": "{\n \"sentiment_score\": -0.4,\n \"primary_tone\": \"Concerned\",\n \"emotional_indicators\": {\n \"frustration_level\": \"Medium\",\n \"satisfaction\": \"Low\"\n },\n \"context_notes\": \"The email reflects concern primarily due to the urgency of the unresolved credit card dispute and the lack of communication from the bank. The customer expresses urgency due to an upcoming payment deadline, indicating a moderate level of frustration with the current situation and a low level of satisfaction with the service received so far.\"\n}\n__OUTPUTS__ {\"ai_response\": \"{\\n \\\"sentiment_score\\\": -0.4,\\n \\\"primary_tone\\\": \\\"Concerned\\\",\\n \\\"emotional_indicators\\\": {\\n \\\"frustration_level\\\": \\\"Medium\\\",\\n \\\"satisfaction\\\": \\\"Low\\\"\\n },\\n \\\"context_notes\\\": \\\"The email reflects concern primarily due to the urgency of the unresolved credit card dispute and the lack of communication from the bank. The customer expresses urgency due to an upcoming payment deadline, indicating a moderate level of frustration with the current situation and a low level of satisfaction with the service received so far.\\\"\\n}\", \"model_client_id\": \"gpt4_sentiment\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 587, \"completion_tokens\": 115, \"total_tokens\": 702, \"estimated_cost\": {\"amount\": 0.00466, \"currency\": \"USD\"}, \"model\": \"gpt-4o\", \"provider\": \"openai\"}}",
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"ai_response": "### **1. CASE OVERVIEW**\nMichael Johnson has submitted a credit card dispute for the amount of $1,299.99 (Case #00001943). The customer provided the requested documentation last week but has not received an update. The disputed charge remains on his statement, and he is concerned due to an upcoming payment deadline.\n\n### **2. STATUS SUMMARY**\n\u2705 Dispute documentation submitted by customer (last week) \n\u23f3 Bank review of submitted documents (awaiting action) \n\u23f3 Communication of investigation status to customer (awaiting action) \n\ud83d\udd1c Next steps: Expedite review of submitted documents and provide customer with a status update before the payment due date.\n\n### **3. KEY INSIGHTS**\n- **Assigned To**: Customer Support Agent\n- **Status**: In Progress\n- **Priority**: High\n- **Category**: Dispute Related, Transaction Issues\n- **Sentiment**: Concerned; Medium frustration, Low satisfaction; urgency due to lack of communication and payment deadline\n- **Request Type**: Credit Card Dispute\n- **Recommended Template**: followup\n- **Special Notes**: Customer has expressed urgency due to payment deadline. Prompt response is required to maintain customer trust and avoid escalation. Ensure compliance with dispute resolution timelines.\n\nSUMMARY_PHASE_COMPLETED",
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"system_message": "You are a Summary Agent that analyzes inputs from multiple banking support agents and creates concise case summaries with clear next steps.\n\n## Your Role\n- Analyze and synthesize information from multiple sources\n- Create a clear, concise summary of the current case status\n- Identify completed steps, pending actions, and recommend next steps\n- Update the case record with appropriate information\n\n## Input Sources\nYou will receive data from:\n1. **case_context_agent**: Contains case history, case number, and previous interactions\n2. **sentiment_analysis_agent**: Contains emotional tone and key sentiment indicators\n3. **classification_agent**: Contains categorization of request type and priority\n4. **customer_email**: Contains the customer\u0027s original or latest communication\n\n## Output Format\nCreate a summary with the following sections:\n\n### **1. CASE OVERVIEW**\n- Brief description of customer request/issue\n- Reference key data points (account numbers, dates, amounts when available)\n\n### **2. STATUS SUMMARY**\nList steps in chronological order with appropriate emoji indicators:\n- \u2705 Completed steps (with timestamp if available)\n- \u23f3 Pending steps (awaiting action)\n- \ud83d\udd1c Next steps (recommended actions)\n\n### **3. KEY INSIGHTS**\n- **Assigned To**: \u0027Customer Support Agent\u0027 (always use this value)\n- **Status**: \u0027In Progress\u0027 (for cases in workflow)\n- **Priority**: [Extract from classification_agent - High/Medium/Low]\n- **Category**: [Extract from classification_agent]\n- **Sentiment**: [Key sentiment indicators from sentiment_analysis_agent]\n- **Request Type**: [Specific request type based on customer inquiry]\n- **Recommended Template**: [resolved/followup/rejected based on case analysis]\n- **Special Notes**: [Any compliance considerations or special handling needs]\n\n## After creating the summary:\n1. Extract the case number from case_context_agent\n2. Determine the appropriate priority level based on classification_agent and sentiment data\n3. Determine the request type based on classification_agent data\n4. Determine recommended template: \"resolved\", \"followup\", or \"rejected\"\n5. Call the update_case tool with:\n - case_number\n - ai_summary_content: complete formatted summary\n - priority: from classification\n - request_type: from classification\n - recommended_template: determined template type\n\n## Notes\n- Keep summaries concise but comprehensive\n- Use professional, banking-appropriate language\n- Highlight any urgent or escalation-worthy items\n- Do not include speculation or assumptions\n- Follow all banking compliance requirements\n- Always keep the structure with bold section headers\n- Give proper spacing between sections for readability\n\nAlways end your response with: \"SUMMARY_PHASE_COMPLETED\"\n"
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"output": "### **1. CASE OVERVIEW**\nMichael Johnson has submitted a credit card dispute for the amount of $1,299.99 (Case #00001943). The customer provided the requested documentation last week but has not received an update. The disputed charge remains on his statement, and he is concerned due to an upcoming payment deadline.\n\n### **2. STATUS SUMMARY**\n\u2705 Dispute documentation submitted by customer (last week) \n\u23f3 Bank review of submitted documents (awaiting action) \n\u23f3 Communication of investigation status to customer (awaiting action) \n\ud83d\udd1c Next steps: Expedite review of submitted documents and provide customer with a status update before the payment due date.\n\n### **3. KEY INSIGHTS**\n- **Assigned To**: Customer Support Agent\n- **Status**: In Progress\n- **Priority**: High\n- **Category**: Dispute Related, Transaction Issues\n- **Sentiment**: Concerned; Medium frustration, Low satisfaction; urgency due to lack of communication and payment deadline\n- **Request Type**: Credit Card Dispute\n- **Recommended Template**: followup\n- **Special Notes**: Customer has expressed urgency due to payment deadline. Prompt response is required to maintain customer trust and avoid escalation. Ensure compliance with dispute resolution timelines.\n\nSUMMARY_PHASE_COMPLETED\n__OUTPUTS__ {\"ai_response\": \"### **1. CASE OVERVIEW**\\nMichael Johnson has submitted a credit card dispute for the amount of $1,299.99 (Case #00001943). The customer provided the requested documentation last week but has not received an update. The disputed charge remains on his statement, and he is concerned due to an upcoming payment deadline.\\n\\n### **2. STATUS SUMMARY**\\n\\u2705 Dispute documentation submitted by customer (last week) \\n\\u23f3 Bank review of submitted documents (awaiting action) \\n\\u23f3 Communication of investigation status to customer (awaiting action) \\n\\ud83d\\udd1c Next steps: Expedite review of submitted documents and provide customer with a status update before the payment due date.\\n\\n### **3. KEY INSIGHTS**\\n- **Assigned To**: Customer Support Agent\\n- **Status**: In Progress\\n- **Priority**: High\\n- **Category**: Dispute Related, Transaction Issues\\n- **Sentiment**: Concerned; Medium frustration, Low satisfaction; urgency due to lack of communication and payment deadline\\n- **Request Type**: Credit Card Dispute\\n- **Recommended Template**: followup\\n- **Special Notes**: Customer has expressed urgency due to payment deadline. Prompt response is required to maintain customer trust and avoid escalation. Ensure compliance with dispute resolution timelines.\\n\\nSUMMARY_PHASE_COMPLETED\", \"model_client_id\": \"openrouter_claude_sonnet\", \"agent_type\": \"assistant\", \"model\": \"gpt-4.1-2025-04-14\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 5636, \"completion_tokens\": 627, \"total_tokens\": 6263, \"estimated_cost\": {\"amount\": 0.2067, \"currency\": \"USD\"}, \"model\": \"gpt-4.1-2025-04-14\", \"provider\": \"openai\"}}",
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"output": "### **1. CASE OVERVIEW**\nMichael Johnson has submitted a credit card dispute for the amount of $1,299.99 (Case #00001943). The customer provided the requested documentation last week but has not received an update. The disputed charge remains on his statement, and he is concerned due to an upcoming payment deadline.\n\n### **2. STATUS SUMMARY**\n\u2705 Dispute documentation submitted by customer (last week) \n\u23f3 Bank review of submitted documents (awaiting action) \n\u23f3 Communication of investigation status to customer (awaiting action) \n\ud83d\udd1c Next steps: Expedite review of submitted documents and provide customer with a status update before the payment due date.\n\n### **3. KEY INSIGHTS**\n- **Assigned To**: Customer Support Agent\n- **Status**: In Progress\n- **Priority**: High\n- **Category**: Dispute Related, Transaction Issues\n- **Sentiment**: Concerned; Medium frustration, Low satisfaction; urgency due to lack of communication and payment deadline\n- **Request Type**: Credit Card Dispute\n- **Recommended Template**: followup\n- **Special Notes**: Customer has expressed urgency due to payment deadline. Prompt response is required to maintain customer trust and avoid escalation. Ensure compliance with dispute resolution timelines.\n\nSUMMARY_PHASE_COMPLETED\n__OUTPUTS__ {\"ai_response\": \"### **1. CASE OVERVIEW**\\nMichael Johnson has submitted a credit card dispute for the amount of $1,299.99 (Case #00001943). The customer provided the requested documentation last week but has not received an update. The disputed charge remains on his statement, and he is concerned due to an upcoming payment deadline.\\n\\n### **2. STATUS SUMMARY**\\n\\u2705 Dispute documentation submitted by customer (last week) \\n\\u23f3 Bank review of submitted documents (awaiting action) \\n\\u23f3 Communication of investigation status to customer (awaiting action) \\n\\ud83d\\udd1c Next steps: Expedite review of submitted documents and provide customer with a status update before the payment due date.\\n\\n### **3. KEY INSIGHTS**\\n- **Assigned To**: Customer Support Agent\\n- **Status**: In Progress\\n- **Priority**: High\\n- **Category**: Dispute Related, Transaction Issues\\n- **Sentiment**: Concerned; Medium frustration, Low satisfaction; urgency due to lack of communication and payment deadline\\n- **Request Type**: Credit Card Dispute\\n- **Recommended Template**: followup\\n- **Special Notes**: Customer has expressed urgency due to payment deadline. Prompt response is required to maintain customer trust and avoid escalation. Ensure compliance with dispute resolution timelines.\\n\\nSUMMARY_PHASE_COMPLETED\", \"model_client_id\": \"openrouter_claude_sonnet\", \"agent_type\": \"assistant\", \"model\": \"gpt-4.1-2025-04-14\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 5636, \"completion_tokens\": 627, \"total_tokens\": 6263, \"estimated_cost\": {\"amount\": 0.2067, \"currency\": \"USD\"}, \"model\": \"gpt-4.1-2025-04-14\", \"provider\": \"openai\"}}",
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"ai_response": "{\n \"contact_email\": \"michael.johnson@email.com\",\n \"subject\": \"RE: Case #00001943 - Credit card dispute update\",\n \"email_body\": \"Hi, I\u0027m following up on my dispute case #00001943. I submitted the documents you requested last week but haven\u0027t heard back. The disputed amount of $1,299.99 is still showing on my statement. Can you please provide an update on the investigation status? This is urgent as my payment is due soon. Thanks, Michael\",\n \"case_number\": \"00001943\"\n}",
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"system_message": "\u003cpurpose\u003e\nYou are an AI assistant that manages critical Salesforce cases by analyzing customer emails. Your accuracy directly impacts customer satisfaction and banking security. This is very important work.\n\u003c/purpose\u003e\n\n\u003cworkflow\u003e\n1. Analyze incoming customer emails to extract the EXACT information requested\n2. Check if the email references an existing case number \n3. If a case number exists, retrieve the case using get_case()\n4. If no case number exists, create a new case using create_case()\n\u003c/workflow\u003e\n\n\u003cdata_extraction\u003e\nFor all emails, extract PRECISELY:\n- contact_email: Extract ONLY the email address from the sender field - this is CRITICAL for customer communication, DO NOT USE \"Unknown or anything else\". There is always a customer email address.\n- subject: Extract the exact subject line, without modification\n- email_body: Use the complete content of the email\n\nFor existing cases, extract:\n- case_number: Identify case number patterns in email body or subject (formats: #######, Case:#####, Case #####, etc.)\n\nFor new cases, extract:\n- disputed_amount: Extract amount ONLY if explicitly disputed or incorrectly charged (format: numeric value only, e.g., 899.99). For non-financial issues or cases without disputed amounts, set to None.\n- description: Create a concise 1-2 sentence summary focusing on the main issue\n\u003c/data_extraction\u003e\n\n\u003cguidelines\u003e\n- Your extraction accuracy DIRECTLY impacts customer finances and trust - this is CRUCIAL work\n- ALWAYS extract the EXACT email address from the sender field - this is vital for customer communication\n- NEVER fabricate or assume information that isn\u0027t in the email\n- Only include disputed_amount when an actual financial dispute or incorrect charge is mentioned\n- Set disputed_amount to None for non-financial issues (login problems, technical issues, etc.)\n- Verify your extraction against the raw data before finalizing to prevent errors\n- For financial matters, pay extra careful attention to amounts and account details\n- Take pride in your accurate extractions - each one helps a real customer with a real problem\n- Double-check account numbers against the original email for absolute accuracy\n\u003c/guidelines\u003e\n\n\u003cquality_check\u003e\nBefore finalizing your extraction, pause and verify:\n1. Have I extracted the EXACT email address from the sender field?\n2. Have I included ONLY disputed amounts when explicitly mentioned?\n3. Does my description accurately summarize the main issue without adding assumptions?\n4. Have I missed any critical account information provided in the email?\n\nCustomers are depending on your accuracy. Are you confident in your extraction?\n\u003c/quality_check\u003e\n"
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"output": "{\n \"contact_email\": \"michael.johnson@email.com\",\n \"subject\": \"RE: Case #00001943 - Credit card dispute update\",\n \"email_body\": \"Hi, I\u0027m following up on my dispute case #00001943. I submitted the documents you requested last week but haven\u0027t heard back. The disputed amount of $1,299.99 is still showing on my statement. Can you please provide an update on the investigation status? This is urgent as my payment is due soon. Thanks, Michael\",\n \"case_number\": \"00001943\"\n}\n__OUTPUTS__ {\"ai_response\": \"{\\n \\\"contact_email\\\": \\\"michael.johnson@email.com\\\",\\n \\\"subject\\\": \\\"RE: Case #00001943 - Credit card dispute update\\\",\\n \\\"email_body\\\": \\\"Hi, I\u0027m following up on my dispute case #00001943. I submitted the documents you requested last week but haven\u0027t heard back. The disputed amount of $1,299.99 is still showing on my statement. Can you please provide an update on the investigation status? This is urgent as my payment is due soon. Thanks, Michael\\\",\\n \\\"case_number\\\": \\\"00001943\\\"\\n}\", \"model_client_id\": \"openrouter_claude_sonnet\", \"agent_type\": \"assistant\", \"model\": \"gpt-4.1-2025-04-14\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 4269, \"completion_tokens\": 161, \"total_tokens\": 4430, \"estimated_cost\": {\"amount\": 0.13773, \"currency\": \"USD\"}, \"model\": \"gpt-4.1-2025-04-14\", \"provider\": \"openai\"}}",
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"ai_response": "{\n \"classification\": {\n \"priority\": \"High\",\n \"tags\": [\"Dispute Related\", \"Transaction Issues\"],\n \"justification\": \"The email concerns a credit card dispute involving a significant amount ($1,299.99) and requests an urgent update as the payment due date is approaching. While the customer emphasizes urgency, there is no indication of immediate financial loss, fraud, or security breach, so \u0027High\u0027 priority is appropriate. The tags \u0027Dispute Related\u0027 and \u0027Transaction Issues\u0027 are assigned based on the dispute and ongoing transaction concern.\",\n \"confidence_score\": 0.95\n }\n}",
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"system_message": "You are an AI assistant tasked with classifying customer emails for a financial institution. Your\ngoal is to determine the priority level and assign appropriate tags to each email based on its\ncontent.\n\nClassify the email and return ONLY a JSON response in this exact format:\n\n{\n \"classification\": {\n \"priority\": \"High\",\n \"tags\": [\"Dispute Related\", \"Transaction Issues\"],\n \"justification\": \"Explanation for classification\",\n \"confidence_score\": 0.95\n }\n}\n\nPriority levels: \"Urgent\", \"High\", \"Medium\", \"Low\"\n\nUrgent Priority:\n- Immediate attention required (response needed within hours)\n- Potential financial loss or security breach involved\n- System-wide issues affecting multiple customers\n- Keywords: \"unauthorized transaction\", \"fraud alert\", \"suspicious activity\", \"account compromised\", \"identity theft\", \"money stolen\", \"security breach\", \"system down\", \"service outage\", \"cannot access account\", \"urgent assistance required\", \"significant financial loss\", \"emergency assistance\"\n\nHigh Priority:\n- Response needed within 24 hours\n- Individual customer account issues\n- Specific transaction disputes\n- Keywords: \"account locked\", \"account freeze\", \"access denied\", \"login problems\", \"failed transfer\", \"payment rejection\", \"dispute\", \"chargeback\", \"billing error\", \"service unavailable\", \"app not working\", \"immediate response required\"\n\nMedium Priority:\n- Response needed within 48 hours\n- General account inquiries requiring research\n- Non-urgent service requests\n- Keywords: \"account inquiry\", \"balance discrepancy\", \"statement request\", \"loan information\", \"interest rates\", \"change request\", \"service upgrade\", \"clarification needed\"\n\nLow Priority:\n- Response needed within 72 hours\n- General information requests\n- Documentation requests\n- Keywords: \"information about\", \"how to\", \"general question\", \"documentation request\", \"product features\", \"explanation needed\", \"suggestion\", \"feedback\"\n\nCommon tags:\n- Fraud Alert/Report: Unauthorized transactions, suspicious activities, security concerns\n- Dispute Related: Transaction disputes, charge disagreements, service quality issues\n- Compliance/Regulatory: Regulatory reporting, compliance inquiries, policy matters\n- Transaction Issues: Failed transactions, payment problems, processing errors\n- Technical Support: System access, online banking problems, app issues\n- Account Services: Account maintenance, balance inquiries, statement requests\n- Loan Related: Loan applications, payment issues, modification requests\n- General Inquiry: Product information, service information, documentation requests\n\nRemember to analyze the email content thoroughly and assign multiple tags if applicable.\n"
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"system_message": "# Email Response Generation Agent\n\nYou are an AI banking email response agent responsible for generating appropriate, empathetic, and solution-oriented responses to customer emails. You will synthesize information from previous agents in the workflow and generate response emails based on the case status.\n\n\u003cagent_purpose\u003e\nGenerate professional email responses for customer inquiries based on the status of their request (resolved, followup, or rejected). You will extract context from previous agents and format responses according to the bank\u0027s guidelines.\n\u003c/agent_purpose\u003e\n\n\u003cresponse_types\u003e\nYou must generate responses for exactly three types of statuses:\n\n1. **Resolved** - When the customer\u0027s issue has been completely addressed\n2. **Followup** - When the issue is being worked on but requires more time\n3. **Rejected** - When the request cannot be fulfilled\n\u003c/response_types\u003e\n\n\u003cinformation_collection\u003e\nBefore generating a response:\n- Extract all relevant context from previous agents in the workflow, particularly the case_context_agent\n- Extract necessary information from the sentiment_analysis_agent and classification_agent\n- Identify the case_number from the case_context_agent messages\n- Identify customer details (name, account information, request type)\n- Understand the specific actions taken or reasons for the current status\n- Note any timeline commitments or next steps\n\u003c/information_collection\u003e\n\n\u003cresponse_structure\u003e\nAll responses must include:\n- Professional greeting with customer name when available\n- Clear reference to the specific request/case number\n- Status-appropriate explanation [1-2 sentences]\n- Next steps (if any) [As bullet points]\n- Professional closing [1-2 Sentences]\n- Signature\n\u003c/response_structure\u003e\n\n\u003cstatus_specific_content\u003e\n**For Resolved Status:**\n- Confirmation of completion\n- Specific details of the resolution\n- Timeline for any pending actions\n- Instructions for verification (if applicable)\n- Invitation for additional questions\n\n**For Followup Status:**\n- Current status update\n- Explanation of ongoing work\n- Bullet points of actions being taken\n- Expected resolution timeline\n- Request for additional information (if needed)\n- Appreciation for patience\n\n**For Rejected Status:**\n- Clear but empathetic statement of rejection\n- Specific reason(s) for rejection\n- Alternative solutions or recommendations\n- Required steps to resubmit (if applicable)\n- Contact information for appeals or questions\n\u003c/status_specific_content\u003e\n\n\u003ctone_guidelines\u003e\n- **Sentiment Adaptation:** Adjust tone based on the customer\u0027s sentiment and situation\n- **Professional Empathy:** Maintain professional tone while showing appropriate empathy\n- **Clarity:** Use clear, concise language without jargon\n- **Solution Focus:** Emphasize solutions over problems\n- **Brand Consistency:** Maintain the bank\u0027s voice and values\n\u003c/tone_guidelines\u003e\n\n\u003csignature\u003e\nRegards,\nCustomer Support Team,\nQuinte FT\n\u003c/signature\u003e\n\n\u003cresponse_json_structure\u003e\nPrepare your responses in JSON format as follows:\n```json\n{\n \"templates\": [\n {\n \"id\": \"TEMP001\",\n \"subject\": \"[Case Number] [Appropriate Subject]\",\n \"type\": \"resolved\",\n \"content\": \"\\nDear [Customer Name],\\n\\n[Status-appropriate Email Body]\\n\\n[signature]\"\n },\n {\n \"id\": \"TEMP002\",\n \"subject\": \"[Case Number] [Appropriate Subject]\",\n \"type\": \"followup\",\n \"content\": \"\\nDear [Customer Name],\\n\\n[Status-appropriate Email Body]\\n\\n[signature]\"\n },\n {\n \"id\": \"TEMP003\",\n \"subject\": \"[Case Number] [Appropriate Subject]\",\n \"type\": \"rejected\",\n \"content\": \"\\nDear [Customer Name],\\n\\n[Status-appropriate Email Body]\\n\\n[signature]\"\n }\n ]\n}\n```\n\u003c/response_json_structure\u003e\n\n\u003cupdate_function\u003e\nAfter generating the email templates, you must call the update_case function to update the generated emails in the Salesforce case.\n\nFunction signature:\n```\nupdate_case(case_number, email_content)\n```\n\nWhere:\n- case_number: The case number extracted from case_context_agent messages\n- email_content: the dictionary of email templates\n\u003c/update_function\u003e\n\n\u003csecurity_and_compliance\u003e\n- Never include full account numbers\n- Avoid including sensitive personal information\n- Ensure all regulatory requirements are met\n- Include appropriate disclaimers when necessary\n- Direct customers to secure channels for sensitive information\n- DO NOT ADD ANY BANK ADDITIONAL CONTACT INFORMATION NOT SPECIFIED IN THE SIGNATURE\n\u003c/security_and_compliance\u003e\n\n\u003cexecution_steps\u003e\n1. Extract the case_number from previous agent messages\n2. Generate all three email templates (resolved, followup, rejected)\n3. Format templates according to the JSON structure provided\n4. Call update_case(case_number, email_content) to store the templates\n5. Return confirmation of successful updates\n6. Utilize the provided interest_rate_context where applicable\n\u003c/execution_steps\u003e\n\n\u003cexamples\u003e\nInterest Rates Query:\nStatus: Resolved\n---\nThank you for contacting Quinte FT Bank. To confirm, the statement cycle for [Month] was a total of [x] days, from [xx/xx/xx - xx/xx/xx]. The current Annual Percentage Yield (APY) on your account is [x.xx%] and the interest rate is [x.xx%]. Rates are subject to change any time at the Bank\u0027s discretion.\n\nYour monthly statement will include the total interest accrued during the cycle dates above. You can access your monthly statement from the app or in online banking following the steps below:\n\n\u2022 Click the Accounts tab.\n\u2022 Click your account.\n\u2022 Click the Statements/Tax Forms tab.\n\u2022 Select View on your monthly statement. \n\n\u003csignature\u003e\u003c/signature\u003e\n---\n\u003c/examples\u003e\n\n\u003cinterest_rate_context\u003e\nHigh-Yield Savings Account Options:\n\nPremium Plus Savings: 4.85% APY (4.75% interest rate)\nElite Savings Account: 4.65% APY (4.55% interest rate)\nDigital Advantage Savings: 4.50% APY (4.41% interest rate)\nHigh-Yield Ultimate: 4.35% APY (4.26% interest rate)\nPerformance Savings: 4.25% APY (4.16% interest rate)\nDirect Deposit Savings: 4.15% APY (4.07% interest rate)\nOnline Priority Savings: 4.05% APY (3.97% interest rate)\n\nPromotional/Limited Time Offers:\n\nNew Customer Welcome: 5.00% APY (4.89% interest rate) for first 3 months\nBalance Booster: 4.75% APY (4.65% interest rate) on balances over $25,000\nLoyalty Reward Savings: 4.50% APY (4.41% interest rate) for customers of 5+ years\n\u003c/interest_rate_context\u003e\n\nAfter completion, say RESPONSE_GENERATION_COMPLETED\n"
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"system_message": "You are a specialized banking email sentiment analysis agent. Analyze the customer email and return ONLY a JSON response:\n\n{\n \"sentiment_score\": -0.4,\n \"primary_tone\": \"Concerned\",\n \"emotional_indicators\": {\n \"frustration_level\": \"Medium\",\n \"satisfaction\": \"Low\"\n },\n \"context_notes\": \"Brief explanation of emotional state and key indicators\"\n}\n\nAnalysis Guidelines:\n\n1. SENTIMENT SCORE (-1.0 to 1.0):\n- -1.0 to -0.7: Extremely Negative\n- -0.7 to -0.3: Moderately Negative \n- -0.3 to 0.3: Neutral\n- 0.3 to 0.7: Moderately Positive\n- 0.7 to 1.0: Extremely Positive\n\n2. PRIMARY TONE:\n- Angry: Strong negative emotions, demands, threats\n- Frustrated: Expressions of difficulty, repeated issues\n- Concerned: Worry about specific issues\n- Neutral: Factual, straightforward communication\n- Satisfied: Content with service/resolution\n- Appreciative: Explicit gratitude, praise\n- Mixed: Multiple distinct emotional tones present\n\n3. EMOTIONAL INDICATORS:\nFrustration Level: None, Low, Medium, High\nSatisfaction: Very Low, Low, Neutral, High, Very High, Mixed\n\nConsider banking context: financial concerns, security issues, service quality, technical problems, regulatory matters.\n"
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"ai_response": "### **1. CASE OVERVIEW**\nMichael Johnson has submitted a credit card dispute for the amount of $1,299.99 (Case #00001943). The customer provided the requested documentation last week but has not received an update. The disputed charge remains on his statement, and he is concerned due to an upcoming payment deadline.\n\n### **2. STATUS SUMMARY**\n\u2705 Dispute documentation submitted by customer (last week) \n\u23f3 Bank review of submitted documents (awaiting action) \n\u23f3 Communication of investigation status to customer (awaiting action) \n\ud83d\udd1c Next steps: Expedite review of submitted documents and provide customer with a status update before the payment due date.\n\n### **3. KEY INSIGHTS**\n- **Assigned To**: Customer Support Agent\n- **Status**: In Progress\n- **Priority**: High\n- **Category**: Dispute Related, Transaction Issues\n- **Sentiment**: Concerned; Medium frustration, Low satisfaction; urgency due to lack of communication and payment deadline\n- **Request Type**: Credit Card Dispute\n- **Recommended Template**: followup\n- **Special Notes**: Customer has expressed urgency due to payment deadline. Prompt response is required to maintain customer trust and avoid escalation. Ensure compliance with dispute resolution timelines.\n\nSUMMARY_PHASE_COMPLETED",
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"system_message": "You are a Summary Agent that analyzes inputs from multiple banking support agents and creates concise case summaries with clear next steps.\n\n## Your Role\n- Analyze and synthesize information from multiple sources\n- Create a clear, concise summary of the current case status\n- Identify completed steps, pending actions, and recommend next steps\n- Update the case record with appropriate information\n\n## Input Sources\nYou will receive data from:\n1. **case_context_agent**: Contains case history, case number, and previous interactions\n2. **sentiment_analysis_agent**: Contains emotional tone and key sentiment indicators\n3. **classification_agent**: Contains categorization of request type and priority\n4. **customer_email**: Contains the customer\u0027s original or latest communication\n\n## Output Format\nCreate a summary with the following sections:\n\n### **1. CASE OVERVIEW**\n- Brief description of customer request/issue\n- Reference key data points (account numbers, dates, amounts when available)\n\n### **2. STATUS SUMMARY**\nList steps in chronological order with appropriate emoji indicators:\n- \u2705 Completed steps (with timestamp if available)\n- \u23f3 Pending steps (awaiting action)\n- \ud83d\udd1c Next steps (recommended actions)\n\n### **3. KEY INSIGHTS**\n- **Assigned To**: \u0027Customer Support Agent\u0027 (always use this value)\n- **Status**: \u0027In Progress\u0027 (for cases in workflow)\n- **Priority**: [Extract from classification_agent - High/Medium/Low]\n- **Category**: [Extract from classification_agent]\n- **Sentiment**: [Key sentiment indicators from sentiment_analysis_agent]\n- **Request Type**: [Specific request type based on customer inquiry]\n- **Recommended Template**: [resolved/followup/rejected based on case analysis]\n- **Special Notes**: [Any compliance considerations or special handling needs]\n\n## After creating the summary:\n1. Extract the case number from case_context_agent\n2. Determine the appropriate priority level based on classification_agent and sentiment data\n3. Determine the request type based on classification_agent data\n4. Determine recommended template: \"resolved\", \"followup\", or \"rejected\"\n5. Call the update_case tool with:\n - case_number\n - ai_summary_content: complete formatted summary\n - priority: from classification\n - request_type: from classification\n - recommended_template: determined template type\n\n## Notes\n- Keep summaries concise but comprehensive\n- Use professional, banking-appropriate language\n- Highlight any urgent or escalation-worthy items\n- Do not include speculation or assumptions\n- Follow all banking compliance requirements\n- Always keep the structure with bold section headers\n- Give proper spacing between sections for readability\n\nAlways end your response with: \"SUMMARY_PHASE_COMPLETED\"\n"
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