Knowledge Priming Refiner

Purpose

This refiner facilitates a structured conversation to create a project-specific knowledge base document. The document captures the project's identity -- its tech stack, architecture, directory layout, and the trusted sources that shaped how the team works. Think of it as answering one question: "What does AI need to know about this project to avoid defaulting to generic internet patterns?"

This is not about how to write good code -- that is handled by the clean-code atom (coding principles), architecture atom (structural rules), and domain-driven-design atom (domain modeling). Knowledge priming covers what those skills cannot know: which framework, which version, which docs to trust, and how the repo is organized.

What This Produces

• Output: .lattice/standards/knowledge-base.md (or custom path from .lattice/config.yaml -> paths.knowledge_base)
• Mode: Override is the standard approach -- every project's knowledge base is unique, so there are no generic defaults to overlay on. Overlay mode is available for selective revisions of an existing document.
• Config key: paths.knowledge_base in .lattice/config.yaml
• Template: Read ./assets/template.md for the full document structure and interview guidance comments
• Consumed by: The knowledge-priming atom loads this document via config resolution and provides it as ambient project context to all skills and molecules

Scope Boundary

Knowledge priming captures project identity and technical context. It deliberately excludes concerns covered by other skills: