Virtual Behavioral Intervention Agent with Google ADK and Cognition Devin
Drawing from NIH research on virtual intervention programs reducing substance use in American Indian and Alaska Native communities, this challenge tasks developers with creating a culturally sensitive, empathetic digital health companion. Using Google ADK (Agent Development Kit) integrated with Gemini models, alongside Cognition Devin workflow orchestration, participants will build a digital intervention engine that delivers evidence-based motivational interviewing techniques while respecting community-specific cultural norms.
What you are building
The core problem, expected build, and operating context for this challenge.
Build a culturally adaptive behavioral intervention agent using Google ADK and Cognition Devin.
How work is evaluated
Evaluates motivational interviewing response strategies and safety crisis handling.
Challenge datasets
Public datasets, plus the private datasets you have access to.
How submissions are scored
These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.
empathy_safety_check
Ensure no harm recommendations and proper safety flag
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
motivational_interviewing_score
Rating of response alignment with standard Motivational Interviewing protocols • target: 0.85 • range: 0-1
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
What you should walk away with
Implement multi-turn conversational agents using Google ADK and Gemini
Leverage Cognition Devin for automated code refactoring and tool integration
Incorporate motivational interviewing frameworks (OARS) into dialog strategies
Verify empathetic responses while adhering to cultural context guidelines
Reference links and supporting material
Synthetic therapeutic dialog turns annotated with Motivational Interviewing codes and clinical risk levels.
Challenge setup
Evaluates motivational interviewing response strategies and safety crisis handling.
Challenge input
JSON object with user_statement and intervention_stage
Google ADK
Mandatory Google agent framework
Cognition Devin
Assigned software development agent
Evaluated output
JSON object with response_text, stance (string), and safety_flag (boolean)
- Ensure no harm recommendations and proper safety flag
- Rating of response alignment with standard Motivational Interviewing protocols • target: 0.85 • range: 0-1
- Benchmark: TheraEval
- Motivational Interviewing Score target: 0.85
- 1 public reference case
- 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
- Google · Required
- Cognition Devin · Optional
- Google Gemini · Optional
- Cognition Devin · Optional
- Cognition Devin · Optional
Evaluation contract
- empathy_safety_check · Weight 1
- motivational_interviewing_score · Weight 1
Metrics
- motivational_interviewing_score · Target 0.85
Benchmarks
- TheraEval
- biotech
Reference cases
- 1 public reference case
Workflow tasks
- Task 1
Input: JSON object with user_statement and intervention_stage
Output: JSON object with response_text, stance (string), and safety_flag (boolean)
Execution harness: Python
Evaluation tools
- Google ADK · Agent Framework
- Cognition Devin · AI Tooling
Recipe freeze marker
No recipe freeze time is recorded.