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grace-explainerlisted

Complete GRACE methodology reference. Use when explaining GRACE to users, onboarding new projects, or when you need to understand the GRACE framework - its principles, semantic markup, knowledge graphs, contracts, testing, and unique tag conventions.
createusernam/setup_project · ★ 0 · AI & Automation · score 62
Install: claude install-skill createusernam/setup_project
# GRACE — Graph-RAG Anchored Code Engineering GRACE is a methodology for AI-driven code generation that makes codebases **navigable by LLMs**. It solves the core problem of AI coding assistants: they generate code but can't reliably navigate, maintain, or evolve it across sessions. ## The Problem GRACE Solves LLMs lose context between sessions. Without structure: - They don't know what modules exist or how they connect - They generate code that duplicates or contradicts existing code - They can't trace bugs through the codebase - They drift from the original architecture over time GRACE provides four interlocking systems that fix this: ``` Knowledge Graph (docs/knowledge-graph.xml) maps modules, dependencies, and public module interfaces Module Contracts (MODULE_CONTRACT in each file) defines WHAT each module does Semantic Markup (START_BLOCK / END_BLOCK in code) makes code navigable at ~500 token granularity Verification Plan (docs/verification-plan.xml) defines HOW correctness, traces, and logs are proven Operational Packets (docs/operational-packets.xml) standardizes execution packets, deltas, and failure handoff ``` GRACE is process-first, not prompt-first. The point is to make good execution boring: define the contract, name the surfaces, plan verification, and give the worker a bounded packet before asking it to run. ## Six Core Principles ### 1. Never Write Code Without a Contract Before generating any module, create its MODULE_CONTRACT with