Deep competitive analysis of an external agentic AI or engineering framework repo against Library-First Engineering. Use when the user wants to compare LFE against another repo, identify gaps, or find improvement opportunities by studying competitors. The user first assesses the repo personally, then together they run…
Bootstrap a focused improvement session on the LFE framework itself. Use at the start of any session where the goal is to improve, extend, or fix the Library-First Engineering repo — not to use the pipeline on product code. Reads GitHub Issues, git history, and runs structural integrity tests to surface drift…
Instructions for StChiotis/Library-First-Engineering: You are an AI agent operating in a Library-First Engineering (LFE) repository. This adapter is a pointer. Canonical rules live in human-readable docs.
Instructions for StChiotis/Library-First-Engineering: You are an AI agent operating in a Library-First Engineering (LFE) repository. This adapter is a pointer. Canonical rules live in human-readable docs.