Municipal Debt Housing Recovery Underwriting Agent with Claude SDK
Municipal bond financing for disaster housing requires multi-factor wildfire risk and bond debt service evaluation. Build a Claude Agents SDK system with extended thinking to analyze bond prospectuses and rebuilding schedules, delivering full risk-adjusted municipal yield profiles.
What you are building
Construct an autonomous underwriting assistant using Claude Agents SDK featuring extended thinking and tool use for debt coverage validation.
How work is evaluated
Evaluates accuracy of bond debt service coverage calculation under wildfire delay stress testing.
Datasets
Public datasets, plus the private datasets you have access to.
How submissions are scored
dscr_stress_test
Stressed DSCR must be strictly less than base DSCR when delay > 0
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
underwriting_precision
Accuracy of debt service computations against benchmark bond models • target: 0.96 • range: 0-1
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
Learning goals
Deploy a Claude Agents SDK agent utilizing extended thinking capabilities.
Parse municipal bond offering prospectuses and disaster rebuilding risk disclosures.
Model debt service coverage ratios (DSCR) under insurance payout lag scenarios.
Synthesize risk-adjusted yield profiles with step-by-step reasoning logs.
Resources
Synthetic municipal bond prospectus disclosures, disaster insurance payout schedules, and home rebuilding timelines.
Challenge setup
Evaluates accuracy of bond debt service coverage calculation under wildfire delay stress testing.
Challenge input
JSON containing bond_issuance_amount, coupon_rate, annual_repayment_cap, insurance_delay_months
Claude Agents SDK
Framework assignment for Anthropic agent development.
Evaluated output
JSON with base_dscr, stressed_dscr, default_risk_flag boolean
- Stressed DSCR must be strictly less than base DSCR when delay > 0
- Accuracy of debt service computations against benchmark bond models • target: 0.96 • range: 0-1
- Benchmark: Claude-Finance-Bench
- Underwriting Precision target: 0.96
- 1 public reference case
- Python execution harness
- Python sandbox (unavailable on Versalist)
Shows the first task, up to three tools, and up to three evidence items.
View technical recipe
Configured tools
- Aim · Required
- Weights & Biases · Optional
- Ellipsis · Optional
Evaluation contract
- dscr_stress_test · Weight 1
- underwriting_precision · Weight 1
Metrics
- underwriting_precision · Target 0.96
Benchmarks
- Claude-Finance-Bench
- general
Reference cases
- 1 public reference case
Workflow tasks
- Task 1
Input: JSON containing bond_issuance_amount, coupon_rate, annual_repayment_cap, insurance_delay_months
Output: JSON with base_dscr, stressed_dscr, default_risk_flag boolean
Execution harness: Python
Evaluation tools
- Claude Agents SDK · Agent Framework
Recipe freeze marker
No recipe freeze time is recorded.