Show HN: Goldseam – heal broken Cypress selectors with a local LLM

Description and use

Here's a brief summary and explanation of the project:

**Project Summary:** Goldseam is an open-source project that utilizes a local Large Language Model (LLM) to repair broken Cypress selectors, enabling developers to add AI capabilities to their applications without starting from scratch. This tool is particularly useful for prototyping AI features, building Reasoning and Action Graph (RAG) workflows, and evaluating model tooling.

**Value Proposition:** The value of Goldseam lies in its ability to simplify the integration of AI capabilities into existing applications, making it an attractive option for developers who want to explore AI without significant upfront investment in model development.

**Practical Adoption Path:** To adopt Goldseam, developers can start by evaluating its license, maintenance, documentation, issue history, and release cadence to ensure it aligns with their project's requirements. Once satisfied, they can integrate the project into their workflow, perform manual inspection to verify its effectiveness, and make necessary adjustments before considering production use.

**Production Readiness:** Goldseam is considered medium-production-ready, suitable for prototype development or internal workflows, but requires careful dependency and maintenance checks before deployment to production environments. This is due to limited quality signals and the need for manual inspection and verification before adoption.

Use in a workflow

Show HN: Goldseam – heal broken Cypress selectors with a local LLM 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.