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Challenge

Claude Agents SDK Network Switch Diagnostics Engine with Neurolink

Unannounced industrial switch failures erode operator situational awareness and compromise safety logic. Construct an autonomous network diagnostics agent using Claude Agents SDK and Neurolink to analyze switch packet drops and PLC logic alarms. The solution must identify safety-critical switch failures and isolate fault roots with 95% accuracy.

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Challenge brief

What you are building

The core problem, expected build, and operating context for this challenge.

Deploy Claude Agents SDK extended thinking with Neurolink stream analysis to trace industrial network switch failures affecting safety controls.

Delivery guide

How work is evaluated

Evaluation

Evaluates the agent's root-cause accuracy and fault detection speed across simulated OT switch topology failures.

Datasets

Shared data for this challenge

Review public datasets and any private uploads tied to your build.

Evaluation rubric

How submissions are scored

These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.

Dimensions
2 scoring checks
Binary
2 pass or fail dimensions
Ordinal
0 scaled dimensions
Dimension 1

critical_fault_identification

Ensures all critical safety loop impacts are correctly identified

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Dimension 2

root_cause_accuracy

Percentage of correct root cause diagnoses • target: 0.95 • range: 0-1

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Learning goals

What you should walk away with

  • Configure Claude Agents SDK extended thinking for complex network topology reasoning

  • Integrate Neurolink for real-time packet loss and industrial Ethernet log parsing

  • Differentiate between physical switch failures and malicious network traffic disruptions

  • Generate actionable operator recommendations to maintain situational awareness

Resources and assets

Reference links and supporting material

Dataset notes

Network event log repository capturing industrial switch degradation, port dropping, and correlated PLC safety trip flags.

How this agent runs

Evaluates the agent's root-cause accuracy and fault detection speed across simulated OT switch topology failures.

Challenge input

JSON containing syslogs, port status tables, and PLC alarm state transitions

Claude Agents SDK

Assigned framework for reasoning over complex system topologies.

Neurolink

Assigned tool for processing high-velocity stream events.

Evaluated output

JSON with root_cause_device (string), fault_type (string), impacted_safety_loops (list), severity (string)

Checks for
  • Ensures all critical safety loop impacts are correctly identified
  • Percentage of correct root cause diagnoses • target: 0.95 • range: 0-1
Proof of success
  • Benchmark: OT Network Resilience Benchmark
  • Root Cause Accuracy target: 0.95
  • 1 public reference case
Runtime evidence
  • Python execution harness
  • Python sandbox (unavailable on Versalist)
View technical recipe

Configured tools

Action Space
  • Neurolink · Required
  • Claude Code · Optional
Observation
  • Claude Code · Optional
Policy Serving
  • Claude 4.1 Opus · Optional

Evaluation contract

  • critical_fault_identification · Weight 1
  • root_cause_accuracy · Weight 1

Recipe state

This is a preview. The configuration can change before the evaluation recipe is locked.

Frequently Asked Questions about Claude Agents SDK Network Switch Diagnostics Engine with Neurolink