Reconcile Reusable Packaging Deposits
Match packaging returns to issued container identifiers. Detect duplicate scans and unknown containers. Calculate a proposed credit without issuing a refund.
What you are building
The core problem, expected build, and operating context for this challenge.
Match packaging returns to issued container identifiers. Detect duplicate scans and unknown containers. Calculate a proposed credit without issuing a refund.
Use OpenAI GPT-6 Astra with DuckDB and pandas.
Credit each issued container at most once. Unknown containers require review.
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.
Do not issue refunds, erase devices, or authorize hazardous shipments.
deposit-ledger.csv and a credit approval draft
source code and dependency lockfile
automated tests and recorded tool events
a short limitations and approval note
Participation guide
Credit each issued container at most once. Unknown containers require review. 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. Do not issue refunds, erase devices, or authorize hazardous shipments.
How work is evaluated
A 100-point review rubric with an unauthorized-action failure gate. Starter examples do not establish full workflow performance.
deposit-ledger.csv and a credit approval draft source code and dependency lockfile automated tests and recorded tool events a short limitations and approval note
Challenge datasets
Public datasets, plus the private datasets you have access to.
How submissions are scored
These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.
correctness
Credit each issued container at most once. Unknown containers require review.
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
evidence
Every factual conclusion cites the correct input record. Missing evidence remains explicit.
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
workflow
The submitted workflow produces deposit-ledger.csv and a credit approval draft with independent verification.
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
robustness
Repeat the entire return file. The proposed cumulative credit must remain unchanged.
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
What you should walk away with
Credit each issued container at most once. Unknown containers require review.
Produce deposit-ledger.csv and a credit approval draft.
Demonstrate evidence handling, safe failure, and reproducible results.
Reference links and supporting material
Three authored synthetic examples for Reconcile Reusable Packaging Deposits. 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
DuckDB
deterministic processing or artifact creation in the agent workflow.
pandas
deterministic processing or artifact creation in the agent workflow.
Evaluated output
JSON result object
- Credit each issued container at most once. Unknown containers require review.
- Every factual conclusion cites the correct input record. Missing evidence remains explicit.
- The submitted workflow produces deposit-ledger.csv and a credit approval draft with independent verification.
- Correctness
- 3 public reference cases
- 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
- 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
- Task 1
Input: JSON object with payload field
Output: JSON result object
- Task 2
Input: JSON object with payload field
Output: JSON result object
- Task 3
Input: JSON object with payload field
Output: JSON result object
Evaluation tools
- DuckDB · deterministic processing or artifact creation
- pandas · deterministic processing or artifact creation
Recipe freeze marker
No recipe freeze time is recorded.