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Energy Bilateral Trade Agreement Compliance Agent with AutoGen

Energy conglomerates managing multi-billion dollar cross-border commercial agreements require continuous compliance negotiation and contract term checks. Build a multi-agent conversation framework using Microsoft AutoGen where buyer, seller, and legal agents cross-examine agreement clauses.

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What you are building

Utilize Microsoft AutoGen multi-agent conversations to conduct automated compliance checks on bilateral trade contracts.

How work is evaluated

Evaluation

Evaluates clause compliance detection and group chat termination accuracy.

Datasets

Public datasets, plus the private datasets you have access to.

How submissions are scored

Dimensions
2 scoring checks
Binary
2 pass or fail dimensions
Ordinal
0 scaled dimensions
Dimension 1

compliance_flag_check

Ensures agent conversation correctly identifies non-compliant clause status.

Binary check

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

Dimension 2

legal_reasoning_precision

Precision of extracted legal reasoning relative to target trade regulation. • target: 0.91 • range: 0-1

Binary check

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

Learning goals

  • Construct multi-agent chat conversations using Microsoft AutoGen UserProxyAgent and AssistantAgent

  • Enforce compliance validation against French and Saudi trade legal frameworks

  • Incorporate human-in-the-loop validation triggers for non-standard indemnity clauses

  • Extract structured clause obligation matrices from conversational turns

Resources

Dataset notes

Sample bilateral trade agreements, supply contract clauses, and cross-border commercial compliance rules between French and Saudi energy entities.

Challenge setup

Evaluates clause compliance detection and group chat termination accuracy.

Challenge input

JSON with agreement_clause_text and target_jurisdiction

AutoGen

Microsoft framework for building multi-agent conversational ecosystems.

Evaluated output

JSON with compliance_status (COMPLIANT|NON_COMPLIANT), flag_reason, and suggested_revision

Evaluation checks
  • Ensures agent conversation correctly identifies non-compliant clause status.
  • Precision of extracted legal reasoning relative to target trade regulation. • target: 0.91 • range: 0-1
Configured evaluation evidence
  • Benchmark: Legal-Compliance-Bench
  • Legal Reasoning Precision target: 0.91
  • 1 public reference case
Configured runtime
  • Python execution harness
  • Python sandbox (unavailable on Versalist)

Shows the first task, up to three tools, and up to three evidence items.

View technical recipe

Configured tools

Action Space
  • AutoGen · Required
  • Exa · Optional
Policy Serving
  • Vercel AI Gateway · Optional
Orchestration
  • Vercel AI Gateway · Optional

Evaluation contract

  • compliance_flag_check · Weight 1
  • legal_reasoning_precision · Weight 1

Metrics

  • legal_reasoning_precision · Target 0.91

Benchmarks

  • Legal-Compliance-Bench
  • general

Reference cases

  • 1 public reference case

Workflow tasks

  1. Task 1

    Input: JSON with agreement_clause_text and target_jurisdiction

    Output: JSON with compliance_status (COMPLIANT|NON_COMPLIANT), flag_reason, and suggested_revision

    Execution harness: Python

Evaluation tools

  • AutoGen · agent_framework

Recipe freeze marker

No recipe freeze time is recorded.

Frequently Asked Questions about Energy Bilateral Trade Agreement Compliance Agent with AutoGen