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# multi-agent

dynamic multiagent

## Orchestration instructions (chief)

# Corporate Social Media Monitoring and Autonomous Content Generator

## University Multi-Agent AI Project

This project implements a dynamic multi-agent orchestration architecture
for corporate social-media monitoring and content generation.

## Agents

### 1. Trend/Social Listener

Searches the web for recent developments related to the selected topic.

### 2. Strategist

Analyzes the research and decides:

- platform
- audience
- tone
- content angle
- objective
- call to action
- risks

### 3. Content Creator

Uses the research and strategy to generate the social-media post.

### 4. Visual Design Prompter

Creates an image-generation prompt appropriate for the campaign.

### 5. Brand Safety Critic

Independently evaluates:

- factual accuracy
- reputational risk
- misleading claims
- ethical concerns
- legal concerns
- platform suitability

### 6. Orchestrator

Coordinates all agents.

The important feature is the feedback loop:

Content Creator
       |
       v
Brand Safety Critic
       |
   +---+---+
   |       |
APPROVE  REVISE
   |       |
   |       v
   |  Content Creator
   |       |
   |       v
   |  Brand Safety Critic
   |
   v
Final content

## Installation

Create a virtual environment:

```bash
python3 -m venv .venv

## Roles
(no agents yet)

## Workflow
- **Chief:** multi-agent — splits tasks and delegates.

## Coordination / communication
-