refactor(backend): optimize backend snippets for deterministic Agent parsing

backend/mongodb/database-optimization.md

@@ -43,7 +43,7 @@ db.orders.createIndex({ status: 1, date: 1, amount: 1 })
 
 
 ### ⚠️ Problem
-Insecure or unoptimized implementation that can cause performance bottlenecks, maintainability issues, or security vulnerabilities. It deviates from modern deterministic standards, making the code harder for AI Agents and Senior Developers to parse and safely extend.
+Failing to follow best practices for `the architectural pattern` tightly couples dependencies and degrades predictability. This unstructured approach deviates from deterministic AI-coding standards, creating severe architectural debt and potential security vulnerabilities in enterprise scaling.
 ---
 ## 🏗️ 2. Aggregation Pipeline Optimization
 
@@ -77,7 +77,7 @@ db.users.aggregate([
 
 
 ### ⚠️ Problem
-Insecure or unoptimized implementation that can cause performance bottlenecks, maintainability issues, or security vulnerabilities. It deviates from modern deterministic standards, making the code harder for AI Agents and Senior Developers to parse and safely extend.
+Failing to follow best practices for `the architectural pattern` tightly couples dependencies and degrades predictability. This unstructured approach deviates from deterministic AI-coding standards, creating severe architectural debt and potential security vulnerabilities in enterprise scaling.
 ---
 ## 📉 3. Covered Queries
 
@@ -101,7 +101,7 @@ db.orders.find(
 
 
 ### ⚠️ Problem
-Insecure or unoptimized implementation that can cause performance bottlenecks, maintainability issues, or security vulnerabilities. It deviates from modern deterministic standards, making the code harder for AI Agents and Senior Developers to parse and safely extend.
+Failing to follow best practices for `the architectural pattern` tightly couples dependencies and degrades predictability. This unstructured approach deviates from deterministic AI-coding standards, creating severe architectural debt and potential security vulnerabilities in enterprise scaling.
 
 
 ### ✅ Best Practice

backend/mongodb/readme.md

@@ -42,7 +42,7 @@ For deep dives into specific topics, consult the specialized guides:
 db.users.insertOne({ name: "John", age: -5, admin: true });
 ```
 #### ⚠️ Problem
-Insecure or unoptimized implementation that can cause performance bottlenecks, maintainability issues, or security vulnerabilities. It deviates from modern deterministic standards, making the code harder for AI Agents and Senior Developers to parse and safely extend.
+Failing to follow best practices for `schema validation` tightly couples dependencies and degrades predictability. This unstructured approach deviates from deterministic AI-coding standards, creating severe architectural debt and potential security vulnerabilities in enterprise scaling.
 #### ✅ Best Practice
 Implement strict schema validation using JSON Schema in MongoDB.
 #### 🚀 Solution

backend/mongodb/security-best-practices.md

@@ -50,7 +50,7 @@ db.createUser({
 
 
 ### ⚠️ Problem
-Insecure or unoptimized implementation that can cause performance bottlenecks, maintainability issues, or security vulnerabilities. It deviates from modern deterministic standards, making the code harder for AI Agents and Senior Developers to parse and safely extend.
+Failing to follow best practices for `the architectural pattern` tightly couples dependencies and degrades predictability. This unstructured approach deviates from deterministic AI-coding standards, creating severe architectural debt and potential security vulnerabilities in enterprise scaling.
 ---
 ## 🔐 2. NoSQL Injection Prevention
 
@@ -91,7 +91,7 @@ const user = await db.collection('users').findOne({
 
 
 ### ⚠️ Problem
-Insecure or unoptimized implementation that can cause performance bottlenecks, maintainability issues, or security vulnerabilities. It deviates from modern deterministic standards, making the code harder for AI Agents and Senior Developers to parse and safely extend.
+Failing to follow best practices for `the architectural pattern` tightly couples dependencies and degrades predictability. This unstructured approach deviates from deterministic AI-coding standards, creating severe architectural debt and potential security vulnerabilities in enterprise scaling.
 ---
 ## 🗄️ 3. Encryption at Rest
 
@@ -110,7 +110,7 @@ Enable WiredTiger encryption at rest using a robust Key Management Service (KMS)
 
 
 ### ⚠️ Problem
-Insecure or unoptimized implementation that can cause performance bottlenecks, maintainability issues, or security vulnerabilities. It deviates from modern deterministic standards, making the code harder for AI Agents and Senior Developers to parse and safely extend.
+Failing to follow best practices for `the architectural pattern` tightly couples dependencies and degrades predictability. This unstructured approach deviates from deterministic AI-coding standards, creating severe architectural debt and potential security vulnerabilities in enterprise scaling.
 
 
 ### 🚀 Solution