Global Tax & Legal Compliance Advisor Agent
This challenge focuses on developing a sophisticated legal and tax compliance advisor using the OpenAI Agents SDK. The agent will interpret complex regulatory texts, answer specific compliance queries for various jurisdictions, and justify its advice by citing relevant statutes. A core component will be the integration with a simulated MCP knowledge base, powered by Pinecone, to provide the agent with a vast, searchable repository of legal and tax documents. The challenge emphasizes advanced tool use, multi-LLM verification (using GPT-4o for primary analysis and Claude Opus 4.1 for cross-validation), and rigorous evaluation of accuracy and transparency.
What you are building
Develop an autonomous agent using OpenAI Agents SDK and GPT-4o to navigate and advise on global tax and legal compliance, leveraging a simulated MCP knowledge base.
How work is evaluated
The evaluation module will rigorously assess the OpenAI Agents SDK agent's ability to provide accurate, well-justified, and compliant tax and legal advice based on a simulated MCP. Emphasis will be on correctness, completeness, and citation of regulations.
Datasets
Public datasets, plus the private datasets you have access to.
How submissions are scored
CorrectComplianceDecision
Agent's 'is_compliant' decision matches the expected outcome for known scenarios.
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
CitationCount
Advice includes at least 2 relevant citations for complex queries.
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
AdviceCompletenessScore
Expert-rated score for the completeness of the advice (1-5). • target: 4 • range: 1-5
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
ReasoningClarity
Expert-rated score for how clearly the agent justifies its advice (1-5). • target: 4 • range: 1-5
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
Learning goals
Master the OpenAI Agents SDK's function calling and tool definition mechanisms to create robust interactions with external systems.
Design a simulated MCP knowledge base using Pinecone vector database to store and retrieve legal and tax documents, accessible via agent tools.
Develop custom Python tools for the agent to query, extract, and summarize relevant information from the Pinecone-backed MCP.
Implement a multi-LLM strategy where GPT-4o provides primary legal analysis and Claude Opus 4.1 acts as a secondary, independent verifier for critical compliance points.
Craft effective prompts for GPT-4o to ensure accurate interpretation of specific legal clauses and generation of precise compliance advice, citing relevant regulations.
Build an evaluation harness with Testaify to systematically test the agent's responses against a corpus of legal scenarios, measuring accuracy, completeness, and adherence to legal principles.
Implement mechanisms for the agent to explicitly state its reasoning and cite specific regulations to justify its compliance advice.
Resources
Sample data for 2 tasks
Challenge setup
The evaluation module will rigorously assess the OpenAI Agents SDK agent's ability to provide accurate, well-justified, and compliant tax and legal advice based on a simulated MCP. Emphasis will be on correctness, com...
Challenge input
{"query": "string", "country": "string", "context": "string"}
Agent execution
No agent tool is listed for this challenge.
Evaluated output
{"advice": "string", "is_compliant": "boolean", "citations": ["string"]}
- Agent's 'is_compliant' decision matches the expected outcome for known scenarios.
- Advice includes at least 2 relevant citations for complex queries.
- Expert-rated score for the completeness of the advice (1-5). • target: 4 • range: 1-5
- AdviceCompletenessScore target: 4
- 2 public reference cases
- Python execution harness
Shows the first task, up to three tools, and up to three evidence items.
View technical recipe
Configured tools
No tool records are attached.
Evaluation contract
- CorrectComplianceDecision · Weight 1
- CitationCount · Weight 1
- AdviceCompletenessScore · Weight 1
- ReasoningClarity · Weight 1
Metrics
- AdviceCompletenessScore · Target 4
- ReasoningClarity · Target 4
Reference cases
- 2 public reference cases
Workflow tasks
- Task 1
Input: {"query": "string", "country": "string", "context": "string"}
Output: {"advice": "string", "is_compliant": "boolean", "citations": ["string"]}
Execution harness: Python
- Task 2
Input: {"scenario": "string", "country": "string"}
Output: {"compliance_issue_detected": "boolean", "issue_description": "string", "violating_regulations": ["string"]}
Execution harness: Python
Recipe freeze marker
No recipe freeze time is recorded.