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Add cellular network architecture analysis and adaptation guide#4

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belkmouf:claude/learn-agent-architecture-ZxC2J
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Add cellular network architecture analysis and adaptation guide#4
belkmouf wants to merge 2 commits intosands-lab:mainfrom
belkmouf:claude/learn-agent-architecture-ZxC2J

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Summary

This PR adds comprehensive documentation for adapting the NIKA agent architecture to wireless telecom/cellular networks (4G/5G). The analysis document provides a detailed roadmap for extending the existing network troubleshooting framework to support cellular-specific domains including RAN (Radio Access Network), Core Network Functions, and transport layers.

Key Changes

  • Architecture Analysis Document (docs/AGENT_ARCHITECTURE_ANALYSIS.md):

    • Overview of current NIKA architecture and core components
    • Detailed explanation of key patterns: multi-agent workflows (LangGraph), specialized sub-agents, MCP tool exposure, and fault injection systems
    • Component mapping between NIKA's wired network model and cellular network equivalents
    • Proposed cellular agent architecture with domain-specific agents (RadioDiagnosisAgent, CoreDiagnosisAgent)
  • Cellular-Specific MCP Tools:

    • RAN MCP Server: gNB metrics, UE measurements, handover history, interference analysis, RRC state tracking, beam alignment
    • Core Network MCP Server: AMF status, PDU session info, subscriber profiles, user plane tracing, network slice statistics, authentication checks
    • Telemetry MCP Server: PM counters, active alarms, KPI trends, event correlation
  • Cellular Problem Categories:

    • RF interference, coverage holes, capacity exhaustion, hardware failures, handover issues
    • Authentication/session/mobility management failures
    • Backhaul/fronthaul issues, transport failures
    • Slice SLA violations, QoS degradation, security threats
  • Implementation Roadmap:

    • 5-phase plan: Environment setup → MCP tools → Agent development → Problem library → Integration & benchmarking
    • File structure and technology stack recommendations
    • Example cellular scenarios (urban macro, rural, enterprise campus, highway mobility, stadium, IoT)

Notable Details

  • Maintains NIKA's modular design philosophy while extending it to cellular domains
  • Proposes specialized diagnosis agents for RAN and Core network layers, reflecting the distinct expertise required
  • Includes example system prompts and tool definitions ready for implementation
  • Provides clear mapping between existing NIKA components and their cellular equivalents
  • Recommends open-source cellular simulators (UERANSIM, Open5GS, srsRAN) compatible with the existing architecture

Purpose

This document serves as a design specification and implementation guide for teams looking to build AI-powered troubleshooting agents for cellular networks using the NIKA framework as a foundation.

https://claude.ai/code/session_01Qr4uiSXnGDrYU97og9wAex

…aptation

Document the NIKA agent architecture patterns and provide detailed guidance
for adapting the framework to wireless telecom/cellular networks including:
- Multi-agent workflow with LangGraph
- MCP tool exposure patterns
- Cellular-specific MCP server designs (RAN, Core, Telemetry)
- Problem categories for cellular troubleshooting
- Implementation roadmap and technology recommendations

https://claude.ai/code/session_01Qr4uiSXnGDrYU97og9wAex
Major additions:
- Hierarchical orchestrator-expert pattern for deeper troubleshooting
- 5 specialized expert agents: RAN, Core, Transport, Security, QoS
- Complete LangGraph workflow with parallel expert execution
- Cross-domain correlation and iterative analysis capabilities
- Human-in-the-loop support for critical issues
- Comprehensive MCP tool reference (50+ tools across 6 servers)
- Expanded cellular problem categories with root cause taxonomy
- Complete file structure for implementation
- Implementation roadmap with timeline

The architecture mirrors real telecom NOC operations with L1/L2/L3
escalation and domain experts collaborating on complex issues.

https://claude.ai/code/session_01Qr4uiSXnGDrYU97og9wAex
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