gds-generate-project-context

To generate project context for AI agents, you use a collaborative discovery workflow to produce a polished project-context.md capturing project-wide rules and patterns. This documents engine choices and guardrails for consistent code generation.

Project-context.md is a structured document containing project-wide rules and patterns optimized for LLM consumption. It provides lean, LLM-friendly content that allows AI agents to quickly scan and understand engine choices, patterns, and guardrails during development.

You document project-wide rules by applying a stepwise generation workflow including discovery, rule generation, and completion. This process uses a frontmatter-driven structure to track progress and supports A/P/C collaborative decisions to codify project-specific rules.

Yes, you can use a frontmatter-driven structure to manage AI agent context generation. The workflow enforces this structure to track progress during the stepwise generation phases, yielding lean, LLM-optimized content for agent consumption.

You need to create a project context file with guardrails when engaging in AI-assisted game development. It ensures AI agents follow consistent code generation patterns by documenting engine choices and project-specific rules.

The best way to structure documentation for LLM-friendly content scanning is to create a lean project-context.md using a frontmatter-driven structure. This enforces collaborative discovery and yields optimized content for quick agent consumption.