component-decision-tree

# Component decision tree A skill for building structured decision trees that map user intents and requirements to specific component selections. The output is a queryable framework that AI agents traverse to select the right component for a given need — eliminating the guesswork that leads to component misuse, duplication, and inconsistency. ## Before you begin: verify references Before doing anything else, confirm that every file listed in this skill's frontmatter `references:` field exists at its relative path from this SKILL.md. If any are missing, stop — the install is incomplete. This usually means a third-party installer (for example `npx skills install`) flattened the skill into a standalone folder and dropped the repo-root `knowledge-notes/` directory this skill depends on. Tell the user to reinstall using a supported method from `1-INSTALL.md` (git clone, or the `.plugin` bundle in Cowork) and to run `verify-install.sh` from the install root to confirm the fix. Only proceed without the references if the user explicitly says to — and if they do, state clearly in your output that it was produced in degraded mode without the pack's reference material. ## Context Component selection is the first decision in any design system interaction, and it is the one that AI agents get wrong most often. The failure mode is not random — it follows predictable patterns. An agent selects a Modal when a Dialog was appropriate. It uses a Card where a List Item fits better. It creat...