# MAGI: Multi-Agent Guided Interview for Psychiatric Assessment

arXiv: https://arxiv.org/abs/2504.18260 · HTML: https://mlsanity.com/paper/2504.18260/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- Placed in Medical and scientific domain agents, one of 16 directions in LLM agents and tool use.
- Builds on 7 of its 31 references that are in the map.
- First posted on arXiv 25 Apr 2025.

## Placed in

- LLM agents and tool use / [Medical and scientific domain agents](https://mlsanity.com/agents/medical-and-scientific-domain-agents/)

## Builds on (most cited first, 7 of 7)

- [LLaMA: Open and Efficient Foundation Language Models](https://mlsanity.com/paper/2302.13971/) (2023)
- [Generative Agents: Interactive Simulacra of Human Behavior](https://mlsanity.com/paper/2304.03442/) (2023)
- [A Computational Approach to Understanding Empathy Expressed in Text-Based Mental Health Support](https://mlsanity.com/paper/2009.08441/) (2020)
- [Cognitive Reframing of Negative Thoughts through Human-Language Model Interaction](https://mlsanity.com/paper/2305.02466/) (2023)
- [Empowering Psychotherapy with Large Language Models: Cognitive Distortion Detection through Diagnosis of Thought Prompting](https://mlsanity.com/paper/2310.07146/) (2023)
- [The Capability of Large Language Models to Measure Psychiatric Functioning](https://mlsanity.com/paper/2308.01834/) (2023)
- [Node-weighted Graph Convolutional Network for Depression Detection in Transcribed Clinical Interviews](https://mlsanity.com/paper/2307.00920/) (2023)

## Built on by (most cited first, 14 of 14)

- [Beyond Static Responses: Multi-Agent LLM Systems as a New Paradigm for Social Science Research](https://mlsanity.com/paper/2506.01839/) (2025)
- [TheraMind: A Strategic and Adaptive Agent for Longitudinal Psychological Counseling](https://mlsanity.com/paper/2510.25758/) (2025)
- [PatientHub: A Unified Framework for Patient Simulation](https://mlsanity.com/paper/2602.11684/) (2026)
- [Interaction Protocol Shapes Moral Judgment in Multi-Agent Debate](https://mlsanity.com/paper/2510.10002/) (2025)
- [Unveiling the Landscape of Clinical Depression Assessment: From Behavioral Signatures to Psychiatric Reasoning](https://mlsanity.com/paper/2508.04531/) (2025)
- [Responsible Evaluation of AI for Mental Health](https://mlsanity.com/paper/2602.00065/) (2026)
- [Dep-LLM: Training-Free Depression Diagnosis via Evidence-Guided Structured Multi-factor with Reliable LLM Reasoning](https://mlsanity.com/paper/2606.10796/) (2026)
- [Tell Me: An LLM-powered Mental Well-being Assistant with RAG, Synthetic Dialogue Generation, and Agentic Planning](https://mlsanity.com/paper/2511.14445/) (2025)
- [DELTA: Deliberative Multi-Agent Reasoning with Reinforcement Learning for Multimodal Psychological Counseling](https://mlsanity.com/paper/2602.04112/) (2026)
- [Initial Risk Probing and Feasibility Testing of Glow: a Generative AI-Powered Dialectical Behavior Therapy Skills Coach for Substance Use Recovery and HIV Prevention](https://mlsanity.com/paper/2602.08121/) (2026)
- [Trust Stack for Mental Health AI: A Survey of Calibration across Human, Interaction, and AI Layers](https://mlsanity.com/paper/2604.20166/) (2026)
- [HiMA-MDD: A Hierarchical Multi-Agent Harness for Interpretable Multimodal Depression Detection in Clinical Interviews](https://mlsanity.com/paper/2608.21868/) (2026)
- [From Pattern Recognizers to Personalized Companions: A Survey of Large Language Models in Mental Health](https://mlsanity.com/paper/2609.25186/) (2026)
- [MACBT: A Multi-Agent Cognitive Behavioral Therapy Decision Support System with Longitudinal Memory](https://mlsanity.com/paper/2609.30939/) (2026)

## Abstract (arXiv)

Automating structured clinical interviews could revolutionize mental healthcare accessibility, yet existing large language models (LLMs) approaches fail to align with psychiatric diagnostic protocols. We present MAGI, the first framework that transforms the gold-standard Mini International Neuropsychiatric Interview (MINI) into automatic computational workflows through coordinated multi-agent collaboration. MAGI dynamically navigates clinical logic via four specialized agents: 1) an interview tree guided navigation agent adhering to the MINI's branching structure, 2) an adaptive question agent blending diagnostic probing, explaining, and empathy, 3) a judgment agent validating whether the response from participants meet the node, and 4) a diagnosis Agent generating Psychometric Chain-of- Thought (PsyCoT) traces that explicitly map symptoms to clinical criteria. Experimental results on 1,002 real-world participants covering depression, generalized anxiety, social anxiety and suicide shows that MAGI advances LLM- assisted mental health assessment by combining clinical rigor, conversational adaptability, and explainable reasoning.