prime-radiant-inc/greenfield

Description and use

**Project Summary:**
Greenfield is an open-source Claude Code plugin that uses AI to reverse-engineer clean behavioral specs, test vectors, and acceptance criteria from any codebase. This allows a fresh team to reimplement a project without inheriting the original's internal structure, making it easier to adopt AI capabilities without starting from scratch. By providing a provenance trail, Greenfield enables teams to evaluate model tooling and build RAG or agent workflows.

**Value:**
The value proposition of Greenfield lies in its ability to add AI capability without requiring a team to start from a blank model stack. This is particularly useful for prototyping AI features, building RAG or agent workflows, and evaluating model tooling.

**Practical Adoption Path:**
To adopt Greenfield, a team should start with a small proof of concept and thoroughly review the README documentation. This will help them understand the plugin's integration process and potential limitations. Once they have a solid grasp of the plugin's functionality, they can begin to integrate it into their existing codebase.

**Production Readiness:**
Greenfield has a medium production readiness score, indicating that it is useful for prototypes or internal workflows but requires further evaluation and dependency checks before being deployed in a production environment. The project has a moderate level of GitHub activity

Use in a workflow

prime-radiant-inc/greenfield helps add AI capability without starting from a blank model stack.

• prototype AI features
• build RAG or agent workflows
• evaluate model tooling

Limitations and review notes

Medium: useful for prototypes or internal workflows, with dependency and maintenance checks before production.