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Pydantic AI Agent Initialization

Inspect the original prompt language first, then copy or adapt it once you know how it fits your workflow.

Linked challenge: Singapore URA Land Tender Valuation Engine using Pydantic AI & AI21 Studio

Format
Code-aware
Lines
8
Sections
4
Linked challenge
Singapore URA Land Tender Valuation Engine using Pydantic AI & AI21 Studio

Prompt source

Original prompt text with formatting preserved for inspection.

8 lines
4 sections
No variables
0 checklist items
Build a Pydantic AI agent using AI21 Studio as the underlying model provider to evaluate Singapore URA tender sites:

from pydantic_ai import Agent
from pydantic import BaseModel

class URABidOutput(BaseModel):
    max_gfa_sqm: float
    total_tender_bid_sgd: float
    compliance_flag: bool

# Configure agent with system prompt and type-safe tools

Adaptation plan

Keep the source stable, then change the prompt in a predictable order so the next run is easier to evaluate.

Keep stable

Hold the task contract and output shape stable so generated implementations remain comparable.

Tune next

Update libraries, interfaces, and environment assumptions to match the stack you actually run.

Verify after

Test failure handling, edge cases, and any code paths that depend on hidden context or secrets.