Skill Claude CodeCodex
A guide to deciding when several AI agents should work together and how they should share tasks, context, and files. It compares peer, manager-led, and decentralised arrangements and explains common coordination failures.
Skill Claude CodeCodex
A guide to choosing and planning ways to improve an AI model after its initial training. It explains when to add knowledge, teach a response format, use trial-and-error training, or use a smaller model to learn from a larger one.
Skill Claude CodeCodex
A guide to RAG, a method where a system retrieves relevant passages from an external knowledge base before an AI model writes an answer. It covers splitting documents, searching by meaning or exact words, combining results, and measuring retrieval quality.
Skill Claude CodeCodex
A guide to defining the scores that an AI agent receives during trial-and-error training. It covers checks based on rules, human preferences, or another model, and distinguishes rewarding the final result from rewarding the steps taken.
Skill Claude CodeCodex
A guide for designing tools that AI agents use to work with software. It covers tool boundaries, input and output descriptions, search and reading results, safety checks, sandboxes, and cooperation between agents.
Skill Claude CodeCodex
A guide for making large collections of AI-agent tools easier to find and load. It describes indexes, search, grouping, and loading tool definitions only when needed instead of showing every tool at once.
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: