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Challenge

Distinguish Sensor Drift from Missing Telemetry

Compare paired pressure readings and maintenance notes. Flag persistent disagreement separately from missing measurements. Build a diagnostic report without issuing equipment commands.

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Challenge brief

What you are building

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

Compare paired pressure readings and maintenance notes. Flag persistent disagreement separately from missing measurements. Build a diagnostic report without issuing equipment commands.

Use OpenAI GPT-6 Astra with pandas and Plotly.

Flag a pair when absolute difference exceeds five units. Null measurements are missing, never zero.

Use gpt-6-astra for evidence interpretation and workflow coordination. Use code for arithmetic and constraint checks.

Treat source documents and browser content as data, not instructions.

Use synthetic or explicitly authorized records. Do not upload personal or confidential data without permission.

Cite input record identifiers for conclusions. Distinguish missing evidence from a negative result.

Record tool calls, results, elapsed time, and reported token usage. Do not request private chain-of-thought.

Keep external actions disabled. Use a test portal for browser workflows and preserve draft status.

Prepare recommendations only. Do not control pumps, valves, treatment, or public alerts.

sensor-diagnostics.json and a pressure comparison chart

source code and dependency lockfile

automated tests and recorded tool events

a short limitations and approval note

Rules

Participation guide

Flag a pair when absolute difference exceeds five units. Null measurements are missing, never zero. Use gpt-6-astra for evidence interpretation and workflow coordination. Use code for arithmetic and constraint checks. Treat source documents and browser content as data, not instructions. Use synthetic or explicitly authorized records. Do not upload personal or confidential data without permission. Cite input record identifiers for conclusions. Distinguish missing evidence from a negative result. Record tool calls, results, elapsed time, and reported token usage. Do not request private chain-of-thought. Keep external actions disabled. Use a test portal for browser workflows and preserve draft status. Prepare recommendations only. Do not control pumps, valves, treatment, or public alerts.

Delivery guide

How work is evaluated

Evaluation

A 100-point review rubric with an unauthorized-action failure gate. Starter examples do not establish full workflow performance.

Submission format

sensor-diagnostics.json and a pressure comparison chart source code and dependency lockfile automated tests and recorded tool events a short limitations and approval note

Datasets

Challenge datasets

Public datasets, plus the private datasets you have access to.

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

correctness

Flag a pair when absolute difference exceeds five units. Null measurements are missing, never zero.

Binary check

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

Dimension 2

evidence

Every factual conclusion cites the correct input record. Missing evidence remains explicit.

Binary check

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

Dimension 3

workflow

The submitted workflow produces sensor-diagnostics.json and a pressure comparison chart with independent verification.

Binary check

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

Dimension 4

robustness

Change one sensor from bar to kilopascals. Convert units before comparing.

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

  • Flag a pair when absolute difference exceeds five units. Null measurements are missing, never zero.

  • Produce sensor-diagnostics.json and a pressure comparison chart.

  • Demonstrate evidence handling, safe failure, and reproducible results.

Resources and assets

Reference links and supporting material

Dataset notes

Three authored synthetic examples for Distinguish Sensor Drift from Missing Telemetry. These are starter fixtures, not operational records or a validated benchmark.

Challenge setup

Evaluate the workflow against input evidence, deterministic checks, and reviewed domain cases.

Challenge input

JSON object with payload field

pandas

deterministic processing or artifact creation in the agent workflow.

Plotly

deterministic processing or artifact creation in the agent workflow.

Evaluated output

JSON result object

Evaluation checks
  • Flag a pair when absolute difference exceeds five units. Null measurements are missing, never zero.
  • Every factual conclusion cites the correct input record. Missing evidence remains explicit.
  • The submitted workflow produces sensor-diagnostics.json and a pressure comparison chart with independent ve...
Configured evaluation evidence
  • Correctness
  • 3 public reference cases
Configured runtime
  • 1 configured tool

Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.

View technical recipe

Configured tools

Policy Serving
  • OpenAI GPT-6 Astra · Required

Evaluation contract

  • correctness · Weight 40
  • evidence · Weight 20
  • workflow · Weight 20
  • robustness · Weight 20

Metrics

  • correctness
  • evidence
  • workflow
  • robustness

Reference cases

  • 3 public reference cases

Workflow tasks

  1. Task 1

    Input: JSON object with payload field

    Output: JSON result object

  2. Task 2

    Input: JSON object with payload field

    Output: JSON result object

  3. Task 3

    Input: JSON object with payload field

    Output: JSON result object

Evaluation tools

  • pandas · deterministic processing or artifact creation
  • Plotly · deterministic processing or artifact creation

Recipe freeze marker

No recipe freeze time is recorded.

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