Generate an optimized AGENTS.md file after analyzing the directory/codebase for context.
Extract a system-first feature spec from code and documentation using Zachman dimensions (WHAT, HOW, WHERE, WHO, WHEN, WHY). Use when users request structured, implementation-grounded specs, architecture extraction, or system design context from an existing codebase and linked sources.
Transform a user's 'basic prompt' into an 'optimized prompt' by applying context engineering -> the right context beats the right prompt.
Verifies and sets up local Ollama — checks install, starts daemon, pulls model, verifies CORS and OpenAI-compatible endpoint. Client-agnostic; use before any skill that needs a working Ollama (e.g. enable-ollama-in-cursor). Use when the user wants Ollama running locally, needs to troubleshoot Ollama, or before configuring any client to use Ollama.
Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria.
Behavioral guidelines to reduce common LLM investigation mistakes. Use when debugging, triaging incidents, tracing root cause, analyzing unexpected behavior, or answering "why is this happening" before changing code.
Refactoring with KISS principles. Rethinks implementations to reach the same outcome with less complexity—prefers straightforward, readable code over clever abstractions. Use when refactoring, reviewing code, the user asks for a simpler approach, or when a solution feels over-engineered relative to the problem.