# Role Assignment

> Give each agent a named role with a role-specific prompt, tool palette, and acceptance criteria — outputs are attributable, specialisation improves quality, and generic drift stops.

- **Category**: Agentic AI
- **Subcategory**: Multi-Agent
- **Canonical URL**: https://designpattern.fyi/patterns/role_assignment/

---

## Description
**Intent**: Assign each agent a named role (researcher, writer, critic, planner) with a role-specific prompt, tool palette, and acceptance criteria.
**Context**: Several agents contribute to a shared workflow — a content pipeline with a researcher, writer, and critic; a coding crew with a planner, coder, and reviewer. The user, the reviewer, and the team need to know who produced what. Each role has its own work to do and its own definition of done.
**Solution**: Define each role with a system prompt naming its responsibility and constraints, a tool palette scoped to its role, and acceptance criteria for outputs it produces. The workflow assigns tasks to roles; outputs are evaluated against the role's acceptance criteria.



## Use Cases
- Multiple agents collaborate and attribution matters — who produced what.
- Different parts of the workflow have distinct responsibilities, tools, and acceptance criteria.
- Generic agents have been observed drifting toward similarity or duplicating effort.






## Trade-offs


### Advantages

- Outputs are attributable and reviewable per role.

- Specialisation improves quality on each role's specific task.




### Considerations & Drawbacks

- Bureaucratic overhead — more prompts, more policies, more things to maintain.

- Role drift over long sessions as agents gradually exceed their defined scope.







---
**Reference**: [Original Source](https://www.agentpatternscatalog.org/patterns/role-assignment/)