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datopiandatopian/portaljs/skills/portaljs-architect/SKILL.md

portaljs-architect

Skill2.4k starsChanged 12 days agoMITView on GitHub

Recommend a data-portal architecture (storage, compute, catalog, access, hosting, metadata) from stated needs, then hand off to the build skills. The advisory entry point. Use when starting a new data-portal project and the underlying architecture has not yet been decided.

We split this skill into the rules it gives an agent

1 rule. About 0 are common, 0 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈0

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    No PortalJS project needs to exist yet.

    line 33

≈ “Common” is an estimate: at least 1 in 5 of the 308,232 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

PortalJS — Architect

Overview

The advisory entry point for a PortalJS project. Before anything gets scaffolded, this skill works out what to build: given the kind of portal, the shape of the data, and its purpose, it fills six architecture slots (storage, catalog, compute, access, hosting, metadata), resolves two build-time knobs (per-dataset data tier and the portal-wide DATA_QUERY mode), and hands off to the concrete build skills. It decides; it does not build. When the brief is thin it interviews in short rounds and never dead-ends — every question has a sensible default, reachable by replying "use defaults."

Prerequisites

  • A rough idea of the portal's purpose and data (exact numbers are not required — the interview supplies defaults for anything missing).
  • Optional: local files or a directory of sample data to inspect for size and shape.
  • No PortalJS project needs to exist yet; this skill runs before scaffolding.

Instructions

The canonical, full step-by-step workflow lives in .claude/commands/portaljs-architect.md — that file is the single source of truth. Follow it when executing this skill:

  1. Parse $ARGUMENTS for anything already specified, then interview for what's missing, one round at a time: (1) what's being built, (2) what the data is, (3) what it's for, (4) constraints. Accept "use defaults" at any point. Inspect named files/directories with du -sh and line counts to ground size guesses.
  2. Derive the recommendation by matching the answers against the decision tables — Storage/Catalog/Compute by data volume and query needs, Access/Hosting by public vs. private, Metadata by standards-compliance needs — then resolve the two build-time knobs: per-dataset data tier (inline | LFS | external) and the portal-wide DATA_QUERY mode (flat | duckdb).
  3. Echo the architecture brief (stack, reasoning per slot, deviations from default, deferred items) and wait for confirmation ("go") or corrections.
  4. On confirmation, persist the brief to ./ARCHITECTURE.md in the working directory.
  5. Hand off to the build skills — /portaljs-new-portal, /portaljs-add-dataset, /portaljs-connect-ckan, /portaljs-define-schema, /portaljs-deploy — mapped from the brief, and offer to run the first one.

Output

  • Created: ./ARCHITECTURE.md documenting the six slots, the two build-time knobs, the reasoning, and anything deferred to a later build step.
  • Modified: nothing else — this skill is advisory only.
  • Verified: the brief was echoed back and confirmed before being persisted.
  • Result: a concrete, named sequence of follow-up skill invocations (e.g. /portaljs-new-portal → /portaljs-add-dataset → /portaljs-deploy).

Error Handling

SymptomCauseFix
Skill keeps asking rounds of questionsBrief was thin or $ARGUMENTS omittedAnswer inline, or reply "use defaults" to accept the opinionated default stack
Recommendation looks genericRounds were skipped without real data detailsGive actual size/shape/cadence, or point at files for du -sh inspection
ARCHITECTURE.md never appearsConfirmation step was skippedReply "go" once the echoed brief looks right
Scaffolded portal has the wrong DATA_QUERYFlat downgrade wasn't appliedRun the perl -pi -e one-liner from the command file against lib/datasets.ts
Hand-off names a skill that doesn't existDecision maps to a (planned) skill (e.g. /connect-openmetadata)Treat it as designed-in/built-later; proceed with the closest available skill

Examples

Example 1 — National statistics office, DCAT-AP harvesting

/portaljs-architect We're a national statistics office. ~200 datasets, mostly large
CSVs (some GBs), updated quarterly, all public, and we must publish DCAT-AP for the
EU data portal.

Infers a multi-publisher, analytics-grade portal. Recommends Parquet on R2 + DuckLake + DuckDB, static Cloudflare Pages, Frictionless + DCAT-AP metadata, owner namespace, data tier external for the Parquet, DATA_QUERY=duckdb. Writes ARCHITECTURE.md and hands off to /portaljs-new-portal then /portaljs-add-dataset.

Example 2 — Small nonprofit, no arguments given

/portaljs-architect

Runs the full four-round interview since nothing was pre-filled. Accepting defaults at each round lands on the opinionated default stack: repo files or Git-LFS + R2 storage, datasets.json catalog, DuckDB compute, static access on Cloudflare Pages, Frictionless metadata, theme namespace, data tier LFS, DATA_QUERY=duckdb.

Example 3 — Internal catalog with restricted datasets

/portaljs-architect Internal engineering data catalog, single team, dozens of CSVs,
some of it access-controlled to specific roles.

The private-data answer in Round 2 flips Access/Hosting to runtime + backend RBAC on Cloudflare Workers — flagged as the larger, opt-in build — while Storage/Catalog/Compute still follow the volume-based defaults.

Resources

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Trending

Steady: 0 new projects took it in the last 4 weeks, none the 4 weeks before.thin data

Week of Aug 30: 0 new projectsWeek of Sep 6: 0 new projectsWeek of Sep 13: 0 new projectsWeek of Sep 20: 0 new projectsWeek of Sep 27: 0 new projectsWeek of Oct 4: 0 new projectsWeek of Oct 11: 0 new projectsWeek of Oct 18: 0 new projects
Aug 2026Sep 2026Oct 2026
New projects taking a version of this file each week, over the 8 weeks our latest run read: only 0 in all, so this is a hint, not a trend.

Who's talking about datopian/portaljs

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Talked about on GitHub and Hacker News (38 times).

On GitHub · 37

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