PortalJS, Define Schema

Overview

Define a dataset's metadata profile, the authoring skill for the metadata-profile contract (lib/metadata). Where portaljs-add-dataset registers that a dataset exists, this skill describes what its data means: infer a Frictionless Table Schema (fields, types, constraints) from sampled data, add the Data Package fields a catalog surfaces (title, licenses, sources, keywords), and write them onto the dataset's entry in datasets.json. The showcase at /@<namespace>/<slug> then renders a typed field table instead of a bare preview. The model is Frictionless-native; DCAT is a serialization layer built on top later, not authored here.

The skill runs on a profile ladder, reach for higher levels only when needed:

Level	What it is	When
L0	Default frictionless-tabular profile; declare schema + metadata.	Default. Standard tabular CSV/TSV.
L1	L0 plus extra descriptive package fields.	Extra metadata, standard validation is fine.
L2	Fully custom profile (own schema template + validate()).	A dataset type needing custom validation rules.
L3	Multiple registered profiles, resolved per dataset.	A portal mixing dataset types.

The skill is interactive and never dead-ends: if input is thin it interviews in short rounds, infers defaults from the data, echoes the schema for confirmation, and accepts "use defaults" to proceed with the inferred schema as-is.

Prerequisites

• A scaffolded PortalJS portal with the metadata contract (lib/metadata/types.ts, pages/[owner]/[slug].tsx); see portaljs-new-portal.
• The target dataset already registered in datasets.json (see portaljs-add-dataset).
• For tabular schema inference, the dataset's CSV/TSV file present under PORTAL_DIR/public/data/. JSON/GeoJSON datasets get package metadata only, no fields.
• Node 18+; tsx optional, used for the schema-validation check.

Instructions