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Challenge

Singapore URA Tender Plot Ratio Analyzer using Vercel AI SDK

Singapore's Urban Redevelopment Authority (URA) frequently releases prime land sites like Marina Gardens Lane with strict plot ratio caps. Build a full-stack land tender bidding assistant using the Vercel AI SDK (TypeScript) that parses URA release notices and generates maximum allowable Gross Floor Area (GFA) proposals.

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Challenge brief

What you are building

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

Develop an interactive TypeScript application with Vercel AI SDK streaming tools that extracts plot ratios and zoning restrictions from URA press releases to optimize tender land bids.

Delivery guide

How work is evaluated

Evaluation

Evaluates URA site tender parsing and gross floor area calculation accuracy.

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

GFA Calculation Exact Match

Verifies that max_gfa_sqm exactly equals site_area * gross_plot_ratio.

Binary check

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

Dimension 2

unit_yield_error

Absolute error in predicted residential unit yield • target: 0 • range: 0-10

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 a streaming web interface using Vercel AI SDK `generateText` and `streamUI`.

  • Parse Singapore URA land sale parameters including site area and Gross Plot Ratio (GPR).

  • Calculate total maximum Gross Floor Area (GFA) and projected residential unit yield.

  • Format structured bid submission objects according to URA regulatory standards.

Resources and assets

Reference links and supporting material

Dataset notes

Dataset of 25 Singapore URA land sale announcements, including site areas, gross plot ratios, land use zones, and winning bid histories.

How this agent runs

Evaluates URA site tender parsing and gross floor area calculation accuracy.

Challenge input

JSON containing site_location, site_area_sqm, gross_plot_ratio, and estimated_avg_unit_size_sqm

AI SDK

Mandatory Vercel framework for streaming AI applications.

Evaluated output

JSON with max_gfa_sqm, estimated_unit_yield, and tender_bid_ceiling_sgd

Checks for
  • Verifies that max_gfa_sqm exactly equals site_area * gross_plot_ratio.
  • Absolute error in predicted residential unit yield • target: 0 • range: 0-10
Proof of success
  • Benchmark: Urban Planning Technical Benchmark
  • Unit Yield Error target: 0
  • 1 public reference case
Runtime evidence
  • JavaScript execution harness
  • javascript sandbox (unavailable on Versalist)
View technical recipe

Configured tools

Action Space
  • Vercel AI SDK · Required
  • Sacred · Optional
  • Synthflow · Optional
Orchestration
  • Vercel AI SDK · Required

Evaluation contract

  • GFA Calculation Exact Match · Weight 1
  • unit_yield_error · Weight 1

Recipe state

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

Frequently Asked Questions about Singapore URA Tender Plot Ratio Analyzer using Vercel AI SDK