Feature/update rules

.gitattributes

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+# Normalize line endings to prevent Windows CRLF issues in Docker containers
+
+# Shell scripts MUST use LF (Linux line endings)
+*.sh text eol=lf
+
+# Python files should use LF
+*.py text eol=lf
+
+# Docker files should use LF
+Dockerfile text eol=lf
+.dockerignore text eol=lf
+docker-compose.yml text eol=lf
+docker-compose.*.yml text eol=lf
+
+# Configuration files should use LF
+*.yaml text eol=lf
+*.yml text eol=lf
+*.json text eol=lf
+*.env text eol=lf
+*.env.* text eol=lf
+
+# Markdown files
+*.md text eol=lf
+
+# XML files (for Maven)
+*.xml text eol=lf
+pom.xml text eol=lf
+
+# Java files
+*.java text eol=lf
+*.drl text eol=lf
+
+# Binary files (don't normalize)
+*.jar binary
+*.war binary
+*.ear binary
+*.pdf binary
+*.png binary
+*.jpg binary
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+*.xlsx binary
+*.xls binary

.gitignore

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 # private files
 **/.env.local
+*.env
+llm.env
 tmp
 TODO.md

API_FIELD_NAMING_CONVENTIONS.md

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+# API Field Naming Conventions
+
+## Important: Field Names Must Match DRL Declarations
+
+When calling the `/api/v1/evaluate-policy` endpoint, **field names in your JSON request must exactly match the field names declared in the DRL rules**.
+
+## Why This Matters
+
+The Drools rule engine uses Java POJOs generated from DRL `declare` statements. For proper deserialization, JSON field names must match the Java field names (which are generated from DRL declarations).
+
+## Current Field Names for Insurance Policies
+
+### Applicant Object
+
+Based on the DRL declaration:
+```drl
+declare Applicant
+    name: String
+    age: int
+    occupation: String
+    healthConditions: String
+    creditScore: int
+    annualIncome: double
+    smoker: boolean
+end
+```
+
+**Correct field names (camelCase):**
+```json
+{
+  "applicant": {
+    "name": "John Doe",
+    "age": 35,
+    "occupation": "Engineer",
+    "healthConditions": "good",
+    "creditScore": 720,
+    "annualIncome": 75000,
+    "smoker": false
+  }
+}
+```
+
+**Incorrect field names (snake_case) - WILL NOT WORK:**
+```json
+{
+  "applicant": {
+    "health_status": "good",      ❌ Use "healthConditions"
+    "credit_score": 720,           ❌ Use "creditScore"
+    "annual_income": 75000,        ❌ Use "annualIncome"
+    "income": 75000                ❌ Use "annualIncome"
+  }
+}
+```
+
+### Policy Object
+
+Based on the DRL declaration:
+```drl
+declare Policy
+    policyType: String
+    coverageAmount: double
+    term: int
+end
+```
+
+**Correct field names:**
+```json
+{
+  "policy": {
+    "policyType": "term_life",
+    "coverageAmount": 500000,
+    "term": 20
+  }
+}
+```
+
+**Note:** The example also shows alternative fields like `termYears` and `type` being used in practice - verify with your actual DRL file which fields are expected.
+
+## Complete Working Example
+
+```json
+{
+  "bank_id": "chase",
+  "policy_type": "insurance",
+  "applicant": {
+    "age": 35,
+    "annualIncome": 75000,
+    "creditScore": 720,
+    "healthConditions": "good",
+    "smoker": false
+  },
+  "policy": {
+    "coverageAmount": 500000,
+    "termYears": 20,
+    "type": "term_life"
+  }
+}
+```
+
+### Expected Response (Approved)
+```json
+{
+  "bank_id": "chase",
+  "container_id": "chase-insurance-underwriting-rules",
+  "decision": {
+    "approved": true,
+    "reason": "Application meets all requirements",
+    "requiresManualReview": false,
+    "premiumMultiplier": 1.0
+  },
+  "status": "success"
+}
+```
+
+## Rejection Examples
+
+### Example 1: Age Too High
+```json
+{
+  "applicant": {
+    "age": 70,  // > 65, will be rejected
+    "annualIncome": 75000,
+    "creditScore": 720,
+    "healthConditions": "good",
+    "smoker": false
+  }
+}
+```
+
+**Response:**
+```json
+{
+  "decision": {
+    "approved": false,
+    "reason": "Applicant age is outside acceptable range"
+  }
+}
+```
+
+### Example 2: Credit Score Too Low
+```json
+{
+  "applicant": {
+    "age": 35,
+    "annualIncome": 75000,
+    "creditScore": 550,  // < 600, will be rejected
+    "healthConditions": "good",
+    "smoker": false
+  }
+}
+```
+
+**Response:**
+```json
+{
+  "decision": {
+    "approved": false,
+    "reason": "Applicant credit score is below minimum requirement"
+  }
+}
+```
+
+### Example 3: Income Too Low
+```json
+{
+  "applicant": {
+    "age": 35,
+    "annualIncome": 20000,  // < 25000, will be rejected
+    "creditScore": 720,
+    "healthConditions": "good",
+    "smoker": false
+  }
+}
+```
+
+**Response:**
+```json
+{
+  "decision": {
+    "approved": false,
+    "reason": "Applicant annual income is below minimum requirement"
+  }
+}
+```
+
+### Example 4: Coverage Too High Relative to Income
+```json
+{
+  "applicant": {
+    "age": 35,
+    "annualIncome": 50000,
+    "creditScore": 720,
+    "healthConditions": "good",
+    "smoker": false
+  },
+  "policy": {
+    "coverageAmount": 600000  // > 10x income (500,000), will be rejected
+  }
+}
+```
+
+**Response:**
+```json
+{
+  "decision": {
+    "approved": false,
+    "reason": "Coverage amount is outside acceptable range"
+  }
+}
+```
+
+## Troubleshooting
+
+### Symptom: Getting unexpected rejections
+**Cause:** Field names don't match DRL declarations, so values aren't being read by rules.
+
+**Solution:** Check your DRL file and ensure JSON field names exactly match the declared field names.
+
+### How to Check Your DRL File
+
+1. Find your deployed DRL file in S3 or the database
+2. Look for `declare` statements
+3. Use those exact field names in your JSON requests
+
+### Example DRL Check
+```bash
+# Get the DRL file from S3
+aws s3 cp s3://uw-data-extraction/generated-rules/chase-insurance-underwriting-rules/latest/*.drl - | grep -A 10 "declare Applicant"
+```
+
+## Best Practices
+
+1. **Always use camelCase** for field names (matches Java conventions)
+2. **Verify field names** against the actual DRL file for your policy
+3. **Test with known values** before integrating
+4. **Check the response** - if fields are missing from the decision object, they weren't properly deserialized
+
+## Updated Documentation
+
+The swagger documentation at `/rule-agent/docs` has been updated with correct examples showing the proper field names.