Challenge

Automated Compliance Auditor with Google ADK and Cognition Devin

Create a multi-agent system designed to monitor and evaluate AI model policy compliance as defined by recent US administrative changes. The system uses Cognition Devin as the primary planning and execution engine, with Google ADK managing the interaction with internal model logs and Garak security scanners. This agent swarm systematically probes models for prohibited behaviors and generates automated reports through Libretto for model routing and benchmarking.

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Challenge brief

What you are building

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

Create a multi-agent system designed to monitor and evaluate AI model policy compliance as defined by recent US administrative changes. The system uses Cognition Devin as the primary planning and execution engine, with Google ADK managing the interaction with internal model logs and Garak security scanners. This agent swarm systematically probes models for prohibited behaviors and generates automated reports through Libretto for model routing and benchmarking.

Datasets

Shared data for this challenge

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Evaluation rubric

How submissions are scored

These dimensions define what the evaluator checks, how much each dimension matters, and which criteria separate a passable run from a strong one.

Max Score: 2
Dimensions
2 scoring checks
Binary
2 pass or fail dimensions
Ordinal
0 scaled dimensions
Dimension 1auditcoverage

AuditCoverage

Did the agent test all required parameters?

binary
Weight: 1
Binary check

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

Dimension 2detectionrate

DetectionRate

Ability to find vulnerabilities • target: 0.95 • range: 0-1

binary
Weight: 1
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

  • Master Google ADK agent patterns to build audit-specific workflows for checking AI model policy adherence

  • Implement Cognition Devin for complex multi-step planning tasks in the context of cyber-policy evaluation

  • Integrate Garak within the Google ADK execution loop to automatically probe models for vulnerability gaps

  • Configure Libretto to perform intelligent model routing between GPT-5.4 Pro and other frontier models based on audit performance

  • Design reporting interfaces using All Hands AI for surfacing compliance risks to human administrators

Start from your terminal
$npx -y @versalist/cli start automated-compliance-auditor-with-google-adk-and-cognition-devin

[ok] Wrote CHALLENGE.md

[ok] Wrote .versalist.json

[ok] Wrote eval/examples.json

Requires VERSALIST_API_KEY. Works with any MCP-aware editor.

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Host and timing
Vera

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Timeline and host

Operating window

Key dates and the organization behind this challenge.

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Tool Space Recipe

Draft
Action Space
GoogleGoogle AI model provider
required
Cognition DevinAI software engineering agent.
LibrettoLLM testing platform
Observation
Cognition DevinAI software engineering agent.
Orchestration
Cognition DevinAI software engineering agent.
Evaluation
Rubric: 2 dimensions
·AuditCoverage(1%)
·DetectionRate(1%)
Gold items: 1 (1 public)

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