Back to challenges
Challenge

Mastra AI MTP Orchestration Pipeline with Braintrust Evaluation

Process automation modularity relies on Module Type Package (MTP) manifests for seamless plug-and-produce integration. Create a TypeScript workflow using Mastra AI and Braintrust to validate MTP state machines and evaluate runtime interface behavior. The orchestration engine must process MTP files and verify inter-module safety logic within 500ms.

EngineeringHosted by Vera
Sign in free to start
Challenge brief

What you are building

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

Build a Mastra AI TypeScript workflow evaluated via Braintrust to parse MTP XML/JSON descriptors and validate plug-and-produce process state compatibility.

Delivery guide

How work is evaluated

Evaluation

Evaluates MTP manifest validation, state machine mapping accuracy, and workflow latency via Braintrust.

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

manifest_validation

Checks if all invalid MTP interface definitions are correctly caught

Binary check

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

Dimension 2

processing_time_ms

Workflow execution duration in milliseconds • target: 200 • range: 0-500

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

  • Design a Mastra AI workflow in TypeScript to process MTP manifest descriptors

  • Integrate Braintrust evaluation logging to measure orchestration accuracy and latency

  • Validate process module state machines (NAMUR NE 148 standard) automatically

  • Verify OPC UA interface tags for seamless plug-and-produce integration

Resources and assets

Reference links and supporting material

Dataset notes

Collection of standard MTP (Module Type Package) definition files for modular chemical dosing, mixing, and heating units.

How this agent runs

Evaluates MTP manifest validation, state machine mapping accuracy, and workflow latency via Braintrust.

Challenge input

JSON containing MTP manifest data (services, eID, OPC UA endpoints)

Mastra AI

Assigned framework for building structured workflows in TypeScript.

Braintrust

Assigned tool for evaluation metrics and workflow instrumentation.

Evaluated output

JSON with is_valid (bool), state_machine_compliant (bool), missing_tags (list), processing_time_ms (int)

Checks for
  • Checks if all invalid MTP interface definitions are correctly caught
  • Workflow execution duration in milliseconds • target: 200 • range: 0-500
Proof of success
  • Benchmark: Modular Automation MTP Benchmark
  • Processing Time Ms target: 200
  • 1 public reference case
Runtime evidence
  • JavaScript execution harness
  • javascript sandbox (unavailable on Versalist)
View technical recipe

Configured tools

Action Space
  • Mastra AI · Required
Observation
  • Braintrust · Optional
Reward / Eval
  • Braintrust · Optional
Orchestration
  • Mastra AI · Required

Evaluation contract

  • manifest_validation · Weight 1
  • processing_time_ms · Weight 1

Recipe state

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

Frequently Asked Questions about Mastra AI MTP Orchestration Pipeline with Braintrust Evaluation