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Challenge

AutoGen Multi-Agent UK Planning Portal Zoning Document Reviewer

Deploy a collaborative AutoGen multi-agent system to automate UK Planning Portal document verification and local development plan checking. The multi-agent workflow converses to resolve zoning discrepancies, verifying structural filings and outputting fully structured policy compliance evaluations.

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Challenge brief

What you are building

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

Uses Microsoft AutoGen multi-agent conversational patterns to orchestrate automated verification of UK planning applications against municipal frameworks.

Delivery guide

How work is evaluated

Evaluation

Evaluates multi-agent conversation resolution and statutory policy check precision.

Datasets

Challenge datasets

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

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

Policy Breach Detection

Verifies that conservation area height limits are correctly identified

Binary check

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

Dimension 2

Agent Conversation Efficiency

Number of multi-agent turns required to achieve correct consensus • target: 4 • range: 2-10

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

  • Configure AutoGen multi-agent group chats with specialized planner roles

  • Automate cross-validation between UK planning applications and local policy documents

  • Implement human-in-the-loop triggers when policy ambiguity is detected

  • Generate formal approval recommendation notices with statutory clause citations

Resources and assets

Reference links and supporting material

Dataset notes

40 UK planning permission applications paired with local authority development framework constraints.

Challenge setup

Evaluates multi-agent conversation resolution and statutory policy check precision.

Challenge input

JSON containing application_id, proposed_extension_sqm, conservation_area (bool), and roofline_height_m

AutoGen

Orchestrates multi-agent conversation and consensus building.

Evaluated output

JSON containing compliance_status, flagged_policy_breaches, and agent_consensus_summary

Evaluation checks
  • Verifies that conservation area height limits are correctly identified
  • Number of multi-agent turns required to achieve correct consensus • target: 4 • range: 2-10
Configured evaluation evidence
  • Benchmark: MultiAgentPolicyCheck-UK
  • Agent Conversation Efficiency target: 4
  • 1 public reference case
Configured runtime
  • Python execution harness
  • Python sandbox (unavailable on Versalist)

Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.

View technical recipe

Configured tools

Action Space
  • AutoGen · Required
  • Larridin · Optional
  • Hamming · Optional

Evaluation contract

  • Policy Breach Detection · Weight 1
  • Agent Conversation Efficiency · Weight 1

Metrics

  • Agent Conversation Efficiency · Target 4

Benchmarks

  • MultiAgentPolicyCheck-UK
  • general

Reference cases

  • 1 public reference case

Workflow tasks

  1. Task 1

    Input: JSON containing application_id, proposed_extension_sqm, conservation_area (bool), and roofline_height_m

    Output: JSON containing compliance_status, flagged_policy_breaches, and agent_consensus_summary

    Execution harness: Python

Evaluation tools

  • AutoGen · Multi-Agent Framework

Recipe freeze marker

No recipe freeze time is recorded.

Frequently Asked Questions about AutoGen Multi-Agent UK Planning Portal Zoning Document Reviewer