Portaljs Add Chart logo

Portaljs Add Chart

OrganizationPopular
datopian
portaljs-add-chart

Add a chart (line, bar, area, pie, or scatter) to a dataset's showcase in a PortalJS portal. Installs recharts, writes a reusable Chart component, and renders it in the showcase Views section. Use when visualizing a dataset already registered in datasets.json.

Overview

Publisherdatopian
Repositoryportaljs
Skill nameportaljs-add-chart
Stars
2.4K
Forks
332
Bundled files
1
LicenseMIT
Links
Skill sourceRepositoryHomepage
  • 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 Chart AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. 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.
2

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-chart .claude/skills/portaljs-add-chart
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Portaljs Add Chart 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 Chart 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 Chart 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 Chart

Overview

Add a visualization to a dataset's showcase in a PortalJS portal. The skill installs recharts (added directly — never @portaljs/components), writes a reusable client-side Chart component into components/, and renders a <Chart /> into the Views section of the showcase route pages/[owner]/[slug].tsx for one chosen dataset. The chart reads the same /public/data/<file> the showcase <Table /> already uses, so no data is duplicated. Five chart types are supported: line, bar, area, pie, and scatter.

Prerequisites

  • A scaffolded PortalJS portal (see portaljs-new-portal).
  • The target dataset already registered in datasets.json (see portaljs-add-dataset).
  • components/ui/parseCsv.ts present (ships with the template).
  • Node 18+ and npm available in the portal directory.

Instructions

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

  1. Gather input — dataset slug, X column, Y column(s), chart type (default line), portal directory. If any is missing, interview the user; never dead-end on a missing value.
  2. Resolve the dataset from datasets.json (namespace, file, format).
  3. Validate that the X and every Y column exist in the data file's header; warn on non-numeric Y columns (values are coerced with Number()).
  4. Install the chart library: npm install recharts@^2.15.0.
  5. Write components/Chart.tsx (idempotent — do not overwrite a customized component).
  6. Render <Chart /> into the Views section, gated on the dataset's (namespace, slug) so other showcases are unaffected. Extend an existing view-dispatch block, do not overwrite.
  7. Verify with npx tsc --noEmit.
  8. Report the component, route, and dependency added.

Output

  • Created: components/Chart.tsx (recharts wrapper, if absent).
  • Modified: pages/[owner]/[slug].tsx (import + gated <Chart /> in Views); package.json (recharts@^2.15.0).
  • Verified: npx tsc --noEmit passes.
  • Result: the chart renders at /@<namespace>/<slug> under a "Views" heading.

Error Handling

SymptomCauseFix
Missing dataset/columnsSlug or column not in manifest/headerList available slugs/headers and re-prompt; do not error out.
Gaps in the chartNon-numeric cells coerced to NaNClean the source data or pick a numeric Y column.
tsc failureBad column prop or import pathFix the first reported error before reporting success.
Sluggish renderOver ~2,000 SVG pointsPre-aggregate the series (e.g. yearly buckets).

Examples

Example 1 — Single line series

/portaljs-add-chart co2-emissions x=year y=emissions type=line

Example 2 — Multi-series bar chart

/portaljs-add-chart trade x=year y=imports,exports type=bar

Example 3 — Pie chart of a categorical breakdown

/portaljs-add-chart budget x=department y=amount type=pie

Resources

Bundled files

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

Frequently asked questions

What does the Portaljs Add Chart AI skill do?

Add a chart (line, bar, area, pie, or scatter) to a dataset's showcase in a PortalJS portal. Installs recharts, writes a reusable Chart component, and renders it in the showcase Views section. Use when visualizing a dataset already registered in datasets.json.

Why use Portaljs Add Chart on TypingMind?

Because you install it once and use it with any model. Portaljs Add Chart 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 Chart in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/datopian/portaljs/tree/main/skills/portaljs-add-chart. 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 Chart?

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 Chart?

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

Is the Portaljs Add Chart 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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