Corporate Sale-Leaseback Financial Structuring Agent with Claude Agents SDK
Corporate finance directors lack real-time decision tools to structure sale-leasebacks that optimize corporate liquidity without degrading credit ratings. Build an agent system using the Claude Agents SDK to evaluate corporate property balance sheets and structure lease terms. Achieve automated deal memo generation with 95% financial accuracy.
What you are building
The core problem, expected build, and operating context for this challenge.
Develop an autonomous structuring agent using Anthropic's Claude Agents SDK to compute optimal leaseback rent, cap rate, and lease term durations.
How work is evaluated
Evaluates mathematical correctness of calculated initial rent, sale proceeds, and post-transaction FCCR.
Shared data for this challenge
Review public datasets and any private uploads tied to your build.
How submissions are scored
These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.
rent_calculation_check
Validates initial annual rent = property value * target cap rate within 0.1% tolerance
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
math_precision
Accuracy of financial ratio calculations • target: 0.95 • range: 0-1
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
What you should walk away with
Implement an agent architecture using Claude Agents SDK tool definition protocols
Calculate sale proceeds, initial cap rate, annual rental escalation, and lease duration options
Perform corporate coverage tests (Fixed Charge Coverage Ratio - FCCR post-transaction)
Output structured deal term sheets for corporate real estate decision-making
Reference links and supporting material
Corporate asset balance sheet summaries with property appraisal values and operating earnings.
How this agent runs
Evaluates mathematical correctness of calculated initial rent, sale proceeds, and post-transaction FCCR.
Challenge input
JSON containing property_appraised_value, target_cap_rate, tenant_ebitdar, annual_rent_escalation
Claude Agents SDK
Anthropic agent development framework for tool orchestration.
Evaluated output
JSON containing gross_proceeds, initial_annual_rent, post_tx_fccr, recommended_lease_years
- Validates initial annual rent = property value * target cap rate within 0.1% tolerance
- Accuracy of financial ratio calculations • target: 0.95 • range: 0-1
- Benchmark: Corporate Real Estate Structuring Benchmark
- Math Precision target: 0.95
- 1 public reference case
- Python execution harness
- Python sandbox (unavailable on Versalist)
View technical recipe
Configured tools
- Metaflow · Required
- Sarvam AI · Optional
- Dora · Optional
Evaluation contract
- rent_calculation_check · Weight 1
- math_precision · Weight 1
Recipe state
This is a preview. The configuration can change before the evaluation recipe is locked.