Use when measuring how well an AI agent handles a recurring kind of task. Builds a small eval set, runs it, and raises the difficulty once the agent passes.
Use when letting AI agents run code, install packages or touch real systems. Covers sandboxing, least privilege and quarantine basics.
Use when structuring a codebase that AI agents will edit heavily. Weighs duplication against abstraction now that repeating code and keeping copies in sync is cheap.
Use when you have several independent jobs for AI agents. Splits work into parallel tasks, hands them off like to coworkers, and reviews results in batches.
Use when reviewing code an AI agent wrote, especially in a language or area you don't know well. Judges the result through tests and behaviour instead of reading every line.
Use when making an app or library usable by a person's own AI agent. Designs a command-line interface so agents can drive the app without a built-in chatbot.
Curated setups
Skills grouped for one workflow and installable with one command.