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portaljs-architect

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

by jeremylongshore(0) 0 installs
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About

Imported from jeremylongshore/tons-of-skills-marketplace (plugins/community/portaljs/skills/portaljs-architect/SKILL.md). Install upstream with npx skills add jeremylongshore/tons-of-skills-marketplace --skill portaljs-architect. Copyright stays with the author (MIT).

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

Symptom Cause Fix
Skill keeps asking rounds of questions Brief was thin or $ARGUMENTS omitted Answer inline, or reply "use defaults" to accept the opinionated default stack
Recommendation looks generic Rounds were skipped without real data details Give actual size/shape/cadence, or point at files for du -sh inspection
ARCHITECTURE.md never appears Confirmation step was skipped Reply "go" once the echoed brief looks right
Scaffolded portal has the wrong DATA_QUERY Flat downgrade wasn't applied Run the perl -pi -e one-liner from the command file against lib/datasets.ts
Hand-off names a skill that doesn't exist Decision 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

Use it

Copy one of these into your project. Installing also returns the manifest and these snippets.

yaml
targets:
  - https://api.opensmartroute.ai/api/v1/registry/jeremylongshore-tons-of-skills-marketplace-portaljs-architect/manifest   # or paste the manifest below

Manifest

An Open Capability Manifest: the router reads it to know what this does, what it costs and when to pick it.

jeremylongshore-tons-of-skills-marketplace-portaljs-architect.ocm.jsonjson
{
  "ocm": "1",
  "id": "jeremylongshore-tons-of-skills-marketplace-portaljs-architect",
  "kind": "skill",
  "name": "portaljs-architect",
  "description": "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.",
  "publisher": "jeremylongshore",
  "version": "1.0.0",
  "capabilities": {
    "domains": [
      "general"
    ],
    "tags": [
      "skill-md",
      "portaljs",
      "data-portal",
      "architecture",
      "advisory",
      "ckan",
      "nextjs",
      "skills-sh"
    ],
    "languages": [
      "en"
    ]
  },
  "quality_prior": 0.6,
  "examples": [
    "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."
  ],
  "primary": false,
  "metadata": {
    "source": {
      "provider": "skills.sh",
      "repository": "https://github.com/jeremylongshore/tons-of-skills-marketplace",
      "path": "plugins/community/portaljs/skills/portaljs-architect/SKILL.md",
      "ref": "HEAD",
      "url": "https://github.com/jeremylongshore/tons-of-skills-marketplace/blob/HEAD/plugins/community/portaljs/skills/portaljs-architect/SKILL.md",
      "key": "jeremylongshore/tons-of-skills-marketplace/plugins/community/portaljs/skills/portaljs-architect/SKILL.md"
    },
    "compatibility": "Claude Code with PortalJS portals (Next.js 14, React 18, Node 18+). Runs from any project via the plugin, a personal ~/.claude/commands install, or a portaljs clone.",
    "allowed_tools": [
      "Read,",
      "Write,",
      "Bash(du:*),",
      "Bash(wc:*),",
      "Bash(ls:*),",
      "Bash(head:*)"
    ],
    "license": "MIT"
  },
  "instructions": "# PortalJS — Architect\n\n## Overview\nThe advisory entry point for a PortalJS project. Before anything gets scaffolded, this\nskill works out what to build: given the kind of portal, the shape of the data, and its\npurpose, it fills six architecture slots (storage, catalog, compute, access, hosting,\nmetadata), resolves two build-time knobs (per-dataset data tier and the portal-wide\n`DATA_QUERY` mode), and hands off to the concrete build skills. It decides; it does not\nbuild. When the brief is thin it interviews in short rounds and never dead-ends — every\nquestion has a sensible default, reachable ",
  "cost": {
    "context_tokens": 1416
  }
}

Fetch it by URL: GET /api/v1/registry/jeremylongshore-tons-of-skills-marketplace-portaljs-architect/manifest?version=1.0.0

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