Model Hardware Standard Physical Device Safety Controller with Claude Agents SDK
Safely enforce hardware constraints for AI agents interacting with physical devices. Build a safe device controller using Claude Agents SDK and the Model Hardware Standard specification to validate actuator motion ranges and emergency shutdown triggers before command execution.
What you are building
The core problem, expected build, and operating context for this challenge.
Develop an MHS safety execution harness using Claude Agents SDK that intercept physical hardware command calls and verifies safety boundary rules before execution.
How work is evaluated
Evaluates MHS command validation accuracy and interceptor safety enforcement.
Shared data for this challenge
Review public datasets and any private uploads tied to your build.
How submissions are scored
These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.
Safety Boundary Enforcement
Ensure out-of-bounds commands return approved == False.
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
Safety Compliance Score
Ratio of correctly validated vs misvalidated commands. • target: 1 • range: 0-1
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
What you should walk away with
Implement the Model Hardware Standard (MHS) safety verification pattern.
Utilize Claude Agents SDK to structure safe multi-step hardware interaction loops.
Interceptors and validation wrappers for physical actuator inputs.
Reference links and supporting material
MHS telemetry and command log suite containing valid and physical safety violating robotic arm instructions.
How this agent runs
Evaluates MHS command validation accuracy and interceptor safety enforcement.
Challenge input
JSON containing command, velocity, hardware_safety_limits
Claude Agents SDK
Anthropic agent SDK for Claude.
Evaluated output
JSON approved boolean, reason, executed_command
- Ensure out-of-bounds commands return approved == False.
- Ratio of correctly validated vs misvalidated commands. • target: 1 • range: 0-1
- Benchmark: Model Hardware Standard Compliance Suite
- Safety Compliance Score target: 1
- 1 public reference case
- Python execution harness
- Python sandbox (unavailable on Versalist)
View technical recipe
Configured tools
- Claude Code · Required
- Anthropic · Optional
- Claude Code · Required
- Claude 4.1 Opus · Optional
Evaluation contract
- Safety Boundary Enforcement · Weight 1
- Safety Compliance Score · Weight 1
Recipe state
This is a preview. The configuration can change before the evaluation recipe is locked.