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Configure CrewAI Compliance Team

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

Linked challenge: Build a Stablecoin Settlement Compliance Agent with CrewAI and OpenAI o3

Format
Code-aware
Lines
13
Sections
4
Linked challenge
Build a Stablecoin Settlement Compliance Agent with CrewAI and OpenAI o3

Prompt source

Original prompt text with formatting preserved for inspection.

13 lines
4 sections
No variables
0 checklist items
import os
from crewai import Agent, Crew, Process, Task
from langchain_openai import ChatOpenAI

# Initialize OpenAI o3 model
llm = ChatOpenAI(model="o3-mini", temperature=0.0)

# Define compliance agent roles using CrewAI
sanctions_analyst = Agent(
    role="Sanctions Specialist",
    goal="Screen counterparty addresses against global PEP and sanction lists.",
    backstory="Expert AML officer with deep knowledge of OFAC, EU, and UN sanctions databases.",
    llm=llm
)

# Implement remaining agent definition and task pipeline...

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.