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Challenge

Post-Disaster Rebuild Cost and Muni Bond Underwriting Agent with OpenAI Agents SDK

Nonprofit housing developers financing disaster rebuilds in wildfire zones face delayed funding commitments due to unaligned debt coverage models. Build an autonomous agent system using the OpenAI Agents SDK to parse contractor estimates and compute municipal bond debt coverage ratios (DSCR). Achieve accurate DSCR calculations across 50 simulated rebuild scenarios.

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Challenge brief

What you are building

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

Construct an OpenAI Agents SDK tool pipeline that processes disaster rebuild contractor bids and computes municipal bond debt service feasibility.

Delivery guide

How work is evaluated

Evaluation

Evaluates calculation precision for debt service coverage ratio (DSCR) and bond tranche sizing.

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

dscr_value_check

Checks DSCR equals projected_net_revenues / annual_debt_service within 0.01 tolerance

Binary check

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

Dimension 2

dscr_accuracy

Accuracy percentage of municipal bond underwriting metrics • target: 0.98 • 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

  • Build an agent system using OpenAI Agents SDK (`openai-agents` / Function Calling tools)

  • Parse home rebuilding cost schedules and infrastructure debt service amortization tables

  • Calculate municipal bond Debt Service Coverage Ratios (DSCR) and loan-to-cost (LTC) metrics

  • Generate automated compliance certificates for tax-exempt municipal bond issuance

Resources and assets

Reference links and supporting material

Dataset notes

Post-disaster home rebuild contractor bid estimates combined with municipal bond debt schedule data.

How this agent runs

Evaluates calculation precision for debt service coverage ratio (DSCR) and bond tranche sizing.

Challenge input

JSON containing total_rebuild_cost, insurance_payout, bond_issuance_amount, annual_debt_service, projected_net_revenues

OpenAI Agents SDK

OpenAI's official framework for building tool-enabled agents.

Evaluated output

JSON containing net_bond_requirement, dscr, bond_issuance_approved

Checks for
  • Checks DSCR equals projected_net_revenues / annual_debt_service within 0.01 tolerance
  • Accuracy percentage of municipal bond underwriting metrics • target: 0.98 • range: 0-1
Proof of success
  • Benchmark: Municipal Bond Underwriting Benchmark
  • Dscr Accuracy target: 0.98
  • 1 public reference case
Runtime evidence
  • Python execution harness
  • Python sandbox (unavailable on Versalist)
View technical recipe

Configured tools

Action Space
  • OpenAI · Required
  • Hume AI · Optional
  • TPOT · Optional

Evaluation contract

  • dscr_value_check · Weight 1
  • dscr_accuracy · Weight 1

Recipe state

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

Frequently Asked Questions about Post-Disaster Rebuild Cost and Muni Bond Underwriting Agent with OpenAI Agents SDK