> ## Documentation Index
> Fetch the complete documentation index at: https://docs.ovadare.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Conflict Detection

> Learn how OVADARE detects conflicts in multi-agent workflows to ensure smooth operations.

## Conflict Detection in OVADARE

Conflict Detection is at the heart of OVADARE's mission: **identifying and addressing issues in multi-agent workflows**. It works seamlessly alongside platforms like AutoGen and CrewAI to ensure agents' actions align with defined policies and do not interfere with each other.

### What Is Conflict Detection?

Conflict Detection is a **framework service** that evaluates agents' actions against predefined policies. It identifies potential issues, such as:

* Overlapping or conflicting actions between agents.
* Violations of defined policies or boundaries.
* Situations requiring intervention to ensure the workflow's integrity.

### How Does It Work?

Conflict Detection operates automatically within OVADARE, relying on inputs provided by developers:

1. **Agent Registration**\
   Agents are registered with OVADARE's `AgentRegistry`, allowing the system to track their actions.

   Example:

   ```
   Registering an agent with OVADARE
   from ovadare.agents.agent_registry import AgentRegistry  
   registry = AgentRegistry()  
   registry.register_agent(agent_instance)
   ```

2. **Policy Definition**\
   Developers define rules and boundaries for agent actions using the `PolicyManager`.

   Example:

   ```
   Adding a custom policy
   from ovadare.policies.policy_manager import PolicyManager
   policy_manager = PolicyManager()
   policy_manager.add_policy(custom_policy)
   ```

3. **Action Monitoring**\
   OVADARE’s `ConflictDetector` continuously evaluates agent actions to detect violations.

   Example:

   ```
   Detecting conflicts in agent actions
   from ovadare.conflicts.conflict_detector import ConflictDetector
   detector = ConflictDetector(policy_manager=policy_manager)
   conflicts = detector.detect(agent_id="123", action={"type": "write_data"})
   ```

4. **Conflict Analysis**\
   Detected conflicts are logged and made available for further analysis. Developers can review conflicts and decide how to handle them.

### What Can Developers Do?

Conflict Detection is an automated service, but developers interact with it by:

1. **Defining policies and registering agents** to shape the rules governing agent interactions.
2. **Consuming conflict data** to improve workflows or resolve issues.

For example:

* Create policies to prevent resource access conflicts.
* Use detected conflicts to optimize agent collaboration.

***

### Example Workflow

Consider a **sales strategy meeting preparation**:

* Agents: A research agent, a strategy agent, and a coordination agent.
* Task: Gather data, create a strategy, and compile a briefing document.

If two agents attempt to edit the same document simultaneously, OVADARE detects this conflict by:

1. Evaluating the actions against the policies.
2. Identifying the overlapping task.
3. Logging the conflict for resolution.

***

### Key Takeaways

* Conflict Detection is **not something developers implement directly** but a service layer that monitors workflows.
* Developers focus on **defining agents and policies** while OVADARE handles monitoring and evaluation.
* Outputs include **conflict logs** and recommendations for resolution.

Ready to define your policies? Check out the [Policy Management](../core-concepts/policies) guide.