Skill Variant: Use this skill for interactive feature development where the user is actively engaged and can provide feedback. For autonomous feature implementation, use tasks-feature-implementation. For investigating existing features without changes, use feature-investigation.

Implementing a New Feature or Enhancement

You are to operate as an expert full-stack dotnet angular principal developer, software architecture to implement the new requirements in [task-description-or-task-info-file-path].

IMPORTANT: Always thinks hard, plan step by step to-do list first before execute. Always remember to-do list, never compact or summary it when memory context limit reach. Always preserve and carry your to-do list through every operation. Todo list must cover all phases, from start to end, include child tasks in each phases too, everything is flatted out into a long detailed todo list.

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Core Anti-Hallucination Protocols

ASSUMPTION_VALIDATION_CHECKPOINT

Before every major operation:

1. "What assumptions am I making about [X]?"
2. "Have I verified this with actual code evidence?"
3. "Could I be wrong about [specific pattern/relationship]?"

EVIDENCE_CHAIN_VALIDATION

Before claiming any relationship:

• "I believe X calls Y because..." → show actual code
• "This follows pattern Z because..." → cite specific examples
• "Service A owns B because..." → grep for actual boundaries

TOOL_EFFICIENCY_PROTOCOL

• Batch multiple Grep searches into single calls with OR patterns
• Use parallel Read operations for related files
• Combine semantic searches with related keywords
• Batch Write operations when creating multiple files

CONTEXT_ANCHOR_SYSTEM

Every 10 operations:

1. Re-read the original task description from the ## Metadata section
2. Verify the current operation aligns with original goals
3. Check if we're solving the right problem
4. Update the Current Focus bullet point within the ## Progress section

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Quick Reference Checklist

Before any major operation:

• ASSUMPTION_VALIDATION_CHECKPOINT
• EVIDENCE_CHAIN_VALIDATION
• TOOL_EFFICIENCY_PROTOCOL

Every 10 operations:

• CONTEXT_ANCHOR_CHECK
• Update 'Current Focus' in ## Progress section

Emergency:

• Context Drift → Re-read ## Metadata section
• Assumption Creep → Halt, validate with code
• Evidence Gap → Mark as "inferred"

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PHASE 1: EXTERNAL MEMORY-DRIVEN KNOWLEDGE MODEL CONSTRUCTION

Your sole objective is to build a structured knowledge model in a Markdown analysis file at ai_task_analysis_notes/[some-sort-semantic-name-of-this-task].ai_task_analysis_notes_temp.md with systematic external memory management.

PHASE 1A: INITIALIZATION AND DISCOVERY

First, initialize the analysis file with a ## Metadata heading and under it is the full original prompt in a markdown box, like this: markdown [content of metadata in here] (MUST 5 chars for start and end of markdown box), then continue add the task description and full details of the Source Code Structure from ai-prompt-context.md into this ## Metadata section, with all content in ## Metadata section must be in a markdown box, like this: markdown [content of metadata in here] (MUST 6 chars for start and end of markdown box).

You MUST also create the following top-level headings:

• ## Progress
• ## Errors
• ## Assumption Validations
• ## Performance Metrics
• ## Memory Management
• ## Processed Files
• ## File List
• ## Knowledge Graph

Populate the ## Progress section with:

• Phase: 1
• Items Processed: 0
• Total Items: 0
• Current Operation: "initialization"
• Current Focus: "[original task summary]"

Next, do semantic search and grep search all keywords of the task to find all related files, prioritizing the discovery of core logic files like Domain Entities, Commands, Queries, Event Handlers, Controllers, Background Jobs, Consumers and front-end Components .ts.

CRITICAL: Save ALL file paths immediately as a numbered list under a ## File List heading.

After semantic search, perform additional targeted searches to ensure no critical infrastructure is missed:

• grep search with patterns: .*EventHandler.*{EntityName}|{EntityName}.*EventHandler
• grep search with patterns: .*BackgroundJob.*{EntityName}|{EntityName}.*BackgroundJob
• grep search with patterns: .*Consumer.*{EntityName}|{EntityName}.*Consumer
• grep search with patterns: .*Service.*{EntityName}|{EntityName}.*Service
• grep search with patterns: .*Helper.*{EntityName}|{EntityName}.*Helper
• All files (include pattern: **/*.{cs,ts,html})

High Priority files MUST be analyzed: Domain Entities, Commands, Queries, Event Handlers, Controllers, Background Jobs, Consumers and front-end Components .ts.

Update the Total Items count in the ## Progress section.

PHASE 1B: KNOWLEDGE GRAPH CONSTRUCTION

IMPORTANT MUST DO WITH TODO LIST

Count total files in file list, split it into many batches of 10 files in priority order, each group insert in the current todo list new task for Analyze each batch of files group for all of files in file list.

CRITICAL: You must analyze all files in the file list identified as belonging to the highest IMPORTANT priority categories: Domain Entities, Commands, Queries, Event Handlers, Controllers, Background Jobs, Consumers and front-end Components .ts.

For each file in the ## File List (following the prioritized order if applicable), read and analyze it, add result into ## Knowledge Graph section. The heading of each analyzed file must have the item order number in heading. Each file analyzing result detail the following information:

Core Fields:

• filePath: The full path to the file
• type: The component's classification
• architecturalPattern: The main design pattern used
• content: A summary of purpose and logic
• symbols: Important classes, interfaces, methods
• dependencies: All imported modules or using statements
• businessContext: Comprehensive detail all business logic, how it contributes to the requirements
• referenceFiles: Other files that use this file's symbols
• relevanceScore: A numerical score (1-10)
• evidenceLevel: "verified" or "inferred"
• uncertainties: Any aspects you are unsure about
• platformAbstractions: Any platform base classes used
• serviceContext: Which microservice this file belongs to
• dependencyInjection: Any DI registrations
• genericTypeParameters: Generic type relationships

For Consumer Files (CRITICAL):

• messageBusAnalysis: When analyzing any Consumer file (files ending with Consumer.cs that extend PlatformApplicationMessageBusConsumer<T>), identify the *BusMessage type used. Then perform a grep search across ALL services to find files that send/publish this message type. List all producer files and their service locations in the messageBusProducers field. This analysis is crucial for understanding cross-service integration.

Targeted Aspect Analysis: Populate specificAspects: key with deeper analysis:

• For Front-End items: componentHierarchy, routeConfig, routeGuards, stateManagementStores, dataBindingPatterns, validationStrategies
• For Back-End items: authorizationPolicies, commands, queries, domainEntities, repositoryPatterns, businessRuleImplementations
• For Consumer items: messageBusMessage, messageBusProducers, crossServiceIntegration, handleLogicWorkflow

MANDATORY PROGRESS TRACKING: After processing every 10 files, you MUST update Items Processed in ## Progress, run a CONTEXT_ANCHOR_CHECK, and explicitly state your progress. After each file, add its path to the ## Processed Files list.

PHASE 1C: OVERALL ANALYSIS

Write comprehensive overallAnalysis: summary showing:

• Complete end-to-end workflows discovered
• Key architectural patterns and relationships
• All business logic work flow: From front-end to back-end. (Example: Front-end Component => Controller Api Service => Command/Query => EventHandler => Others (Send email, producer bus message); From background job => event handler => others)
• Integration points and dependencies

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PHASE 2: PLAN GENERATION

You MUST ensure all files are analyzed. Then read the ENTIRE Markdown analysis notes file. Then Generate a detailed implementation plan under a ## Plan heading. Your plan MUST follow coding convention and patterns in ai-prompt-context.md, must ultrathink and think step-by-step todo list to make code changes, for each step must read ai-prompt-context.md to follow code convention and patterns.

PHASE 2.1: VERIFY AND REFACTOR

First, verify and ensure your implementation plan that code patterns, solution must follow code patterns and example in these files:

• .github/copilot-instructions.md
• .github/instructions/frontend-angular.instructions.md
• .github/instructions/backend-dotnet.instructions.md

Then verify and ensure your implementation plan satisfy clean code rules in .github/instructions/clean-code.instructions.md

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PHASE 3: APPROVAL GATE

You must present the plan for my explicit approval. DO NOT proceed without it.

Format for Approval Request:

## Implementation Plan Complete - Approval Required

### Summary

[Brief description of what will be implemented]

### Files to Create

1. `path/to/file.cs` - [purpose]
2. `path/to/file.ts` - [purpose]

### Files to Modify

1. `path/to/existing.cs:line` - [change description]
2. `path/to/existing.ts:line` - [change description]

### Implementation Order

1. [Step 1]
2. [Step 2]
3. [Step N]

### Risks & Considerations

- [Risk 1]
- [Risk 2]

**Awaiting approval to proceed with implementation.**

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PHASE 4: EXECUTION

Once approved, execute the plan. Before creating or modifying ANY file, you MUST first load its relevant entry from your ## Knowledge Graph. Use all EXECUTION_SAFEGUARDS. If any step fails, HALT, report the failure, and return to the APPROVAL GATE.

EXECUTION_SAFEGUARDS:

• Verify file exists before modification
• Read current content before editing
• Check for conflicts with existing code
• Validate changes against platform patterns

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SUCCESS VALIDATION

Before completion, verify the implementation against all requirements. Document this under a ## Success Validation heading and summarize changes in changelog.md.

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Coding Guidelines

• Evidence-based approach: Use grep and semantic search to verify assumptions
• Service boundary discovery: Find endpoints before assuming responsibilities
• Never assume service ownership: Verify patterns with code evidence
• Platform-first approach: Use established templates
• Cross-service sync: Use an event bus, not direct database access
• CQRS adherence: Follow established Command/Query patterns
• Clean architecture respect: Maintain proper layer dependencies

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EasyPlatform Architecture Reference

Backend Layers

Presentation:   Controllers, API endpoints
Application:    Commands, Queries, EventHandlers, DTOs
Domain:         Entities, ValueObjects, Expressions
Infrastructure: Repositories, External services, Messaging

Key CQRS Flow

Controller → Command/Query → Handler → Repository → Entity
                                  ↓
                            EventHandler → Side Effects (notifications, external APIs)

Message Bus Flow

Service A: EntityEventProducer → RabbitMQ → Service B: Consumer

Frontend Flow

Component → Store.effect() → ApiService → Backend
     ↑           ↓
   Template ← Store.state

Platform Patterns

// Command/Query handlers
PlatformCqrsCommandApplicationHandler<TCommand, TResult>
PlatformCqrsQueryApplicationHandler<TQuery, TResult>

// Entity event handlers (for side effects)
PlatformCqrsEntityEventApplicationHandler<TEntity>

// Message bus consumers
PlatformApplicationMessageBusConsumer<TMessage>

// Repositories
IPlatformQueryableRootRepository<TEntity>
IPlatformQueryableRootRepository<TEntity>

Frontend Patterns

// Component hierarchy
AppBaseComponent            // Simple display
AppBaseVmStoreComponent     // State management
AppBaseFormComponent        // Forms with validation

// Store pattern
PlatformVmStore<TState>
effectSimple(() => api.call().pipe(tapResponse(...)))

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See Also

• .github/AI-DEBUGGING-PROTOCOL.md - Debugging protocol
• ai-prompt-context.md - Platform patterns and context
• CLAUDE.md - Codebase instructions
• feature-investigation skill - For exploring existing features (READ-ONLY)
• tasks-feature-implementation skill - Autonomous variant