Portaljs Add Geo

OrganizationPopular

datopian

portaljs-add-geo

Auto-ingest a geospatial file (GeoJSON, Shapefile, GeoPackage, KML/KMZ, FlatGeobuf, CSV-with-geometry) into a PortalJS portal on the user's own machine, with no server. Normalizes CRS to EPSG:4326, derives a PMTiles render tier and a GeoParquet query tier, pushes all three artifacts to Cloudflare R2 via Git LFS, and appends one dual-tier datasets.json entry the showcase auto-renders. Use when the source is a vector geo format that needs a map or spatial-query view.

Overview

Publisher	datopian
Repository	`portaljs`
Skill name	`portaljs-add-geo`
Stars	2.4K
Forks	332
Bundled files	1
License	MIT
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
1 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by datopian on GitHub. Read the source before you install it.

Installation

Install the Portaljs Add Geo AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/datopian/portaljs.git /tmp/portaljs
mkdir -p .claude/skills
cp -r /tmp/portaljs/skills/portaljs-add-geo .claude/skills/portaljs-add-geo

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Portaljs Add Geo in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Portaljs Add Geo on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Portaljs Add Geo is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

PortalJS — Add Geo

Overview

Turn one geospatial upload into a dual-tier PortalJS dataset entirely on the user's machine — no server-side container compute, keeping the zero-backend bet end-to-end. From a single source the skill derives two serverless tiers plus the preserved original:

PMTiles (render tier) — a vector-tile archive <MapPreview> renders with MapLibre GL over HTTP range requests; any dataset size pans and zooms with no tile server.
GeoParquet (query tier) — a GeoParquet 1.1 file (covering bbox column, Hilbert-sorted) <GeoQuery> runs spatial SQL over in place via DuckDB-Wasm.
Original — the untouched upload in its native CRS, kept downloadable.

All three land on Cloudflare R2 (Git LFS → Giftless), and the skill appends one datasets.json entry whose resources[] match the shape the showcase auto-renders (the @reference/world-boundaries demo, PR #1647): pmtiles → <MapPreview>, geoparquet → <GeoQuery>, original → download. No page edits are needed. It automates the manual tippecanoe/duckdb recipes in the template README.

Prerequisites

A scaffolded portaljs-catalog portal whose template ships components/MapPreview.tsx and components/GeoQuery.tsx (PR #1647 or later).
Native CLIs on the user's machine: GDAL (ogr2ogr, ogrinfo), tippecanoe, and duckdb (with the spatial extension). macOS: brew install gdal tippecanoe duckdb; Debian/Ubuntu: apt-get install gdal-bin duckdb + tippecanoe (apt or build from source); Windows: use WSL. The skill hard-stops with the install hint if any is missing.
Arc credentials for the Git-LFS → R2 push (the same token portaljs-deploy resolves), or an OSS self-hosted Giftless.

Instructions

The canonical, full step-by-step workflow is .claude/commands/portaljs-add-geo.md — the single source of truth. Read and follow it when executing. Summary:

Gather input — source (geo file path or URL), portal directory, namespace. Interview if missing; never dead-end.
Detect the native tools (ogr2ogr, tippecanoe, duckdb + spatial). Any missing → print the per-OS install and stop.
Validate the portal directory and confirm the geo showcase components exist.
Fetch (if URL) and detect the input format; reject raster and bare .shp.
Preserve the original, then normalize to EPSG:4326 GeoJSON with ogr2ogr -t_srs EPSG:4326.
Apply the size escape hatch (measure normalized-GeoJSON bytes): warn ≥ 500 MB; skip PMTiles and emit GeoParquet-only > 2 GB (documented, never silent).
Derive PMTiles with tippecanoe -zg --drop-densest-as-needed.
Derive GeoParquet with duckdb — covering bbox STRUCT + ST_Hilbert order; verify a range read.
Track all three files with Git LFS, mint an Arc JWT, push to R2, prune, and build the absolute data.portaljs.com URLs.
Append one dual-tier datasets.json entry (pmtiles + geoparquet + original resources).
Verify: npx tsc --noEmit and a Range: 206 check on the R2 URL.
Report the tiers, manifest entry, and showcase route.

Output

Created: data/<slug>.pmtiles, data/<slug>.parquet, data/<slug>.<origext> (all LFS-tracked → R2); data/<slug>.4326.geojson (intermediate; can be pruned).
Modified: datasets.json (one dual-tier entry appended); .gitattributes (LFS tracking).
Verified: npx tsc --noEmit passes; the R2 URLs answer HTTP 206 range reads.
Result: /@<namespace>/<slug> renders the PMTiles map and the GeoParquet spatial-query panel together, with no page edits.

Error Handling

Symptom	Cause	Fix
`MISSING_TOOLS`	`ogr2ogr`/`tippecanoe`/`duckdb` (or duckdb `spatial`) absent	Print the per-OS install line and stop; re-run after installing.
`UNSUPPORTED_FORMAT`	Raster `.tif`/`.tiff` (COG tier, later phase)	Use `portaljs-add-dataset` for tabular; await the COG phase.
`SHAPEFILE_NOT_ZIPPED`	Bare `.shp` with no siblings	Zip the whole `.shp/.dbf/.shx/.prj` set and pass the `.zip`.
`MULTI_LAYER`	GPKG/KML with more than one layer	List layers and ask which to ingest; pass the layer name.
`REPROJECTION_FAILED`	`ogr2ogr` error, often a missing `.prj`	Show stderr; re-run with `-s_srs EPSG:<code>`.
`EMPTY_OUTPUT`	Normalized GeoJSON has 0 features	Check the geometry column / CRS of the source.
`TILING_FAILED` / `GEOPARQUET_FAILED`	tippecanoe or duckdb non-zero	Show stderr; for very large inputs see the size escape hatch.
`LFS_PUSH_FAILED`	Missing/expired Arc token or unset `lfs.url`	Re-mint the JWT (see `portaljs-deploy`); confirm `git config lfs.url`.

Examples

Example 1 — Ingest a GeoJSON into both tiers


/portaljs-add-geo source=./data/rivers.geojson name="World Rivers" namespace=reference

Example 2 — Zipped Shapefile from a URL


/portaljs-add-geo source=https://example.com/admin-boundaries.zip slug=admin-boundaries

Example 3 — GeoPackage with an explicit layer and namespace


/portaljs-add-geo source=./data/census.gpkg slug=census-tracts namespace=statistics

Resources

Full workflow: .claude/commands/portaljs-add-geo.md
Flags, thresholds, and the dual-tier manifest shape: references/reference.md
Related skills: portaljs-add-dataset, portaljs-add-map, portaljs-add-resource, portaljs-deploy
tippecanoe: https://github.com/felt/tippecanoe · DuckDB spatial: https://duckdb.org/docs/extensions/spatial

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

references/reference.md5 KB

Frequently asked questions

What does the Portaljs Add Geo AI skill do?

Why use Portaljs Add Geo on TypingMind?

Because you install it once and use it with any model. Portaljs Add Geo is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Portaljs Add Geo in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/datopian/portaljs/tree/main/skills/portaljs-add-geo. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Portaljs Add Geo?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Portaljs Add Geo?

As many as you like. As long as a model supports skills, you can use Portaljs Add Geo with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Portaljs Add Geo AI skill free?

Yes. It is published on GitHub by datopian under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

PortalJS — Add Geo

Overview

Prerequisites

Instructions

Output

Error Handling

Examples

Example 1 — Ingest a GeoJSON into both tiers

Example 2 — Zipped Shapefile from a URL

Example 3 — GeoPackage with an explicit layer and namespace

Resources

Bundled files

Frequently asked questions

Related AI Skills

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