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Data Build Dashboard

Organization
frumu-ai
data-build-dashboard

Build an interactive HTML dashboard with charts, filters, and tables

Overview

Publisherfrumu-ai
Repositorytandem
Skill namedata-build-dashboard
Stars
121
Forks
13
Bundled files
Instructions only
Links
  • 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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by frumu-ai on GitHub. Read the source before you install it.

Installation

Install the Data Build Dashboard 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/frumu-ai/tandem.git /tmp/tandem
mkdir -p .claude/skills
cp -r /tmp/tandem/apps/tandem-desktop/src-tauri/resources/skill-templates/data-build-dashboard .claude/skills/data-build-dashboard
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Data Build Dashboard 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 Data Build Dashboard 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 Data Build Dashboard 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.

Build Interactive Dashboards

If you see unfamiliar placeholders or need to check which tools are connected, please ask about available integrations.

Build a self-contained interactive HTML dashboard with charts, filters, tables, and professional styling. Opens directly in a browser -- no server or dependencies required.

Usage

You can ask to build a dashboard with a description (e.g., "Build a sales dashboard" or "Create a support ticket dashboard").

Arguments

  • description — Description of the dashboard purpose and content
  • data source — (Optional) The data to use

Workflow

1. Understand the Dashboard Requirements

Determine:

  • Purpose: Executive overview, operational monitoring, deep-dive analysis, team reporting
  • Audience: Who will use this dashboard?
  • Key metrics: What numbers matter most?
  • Dimensions: What should users be able to filter or slice by?
  • Data source: Live query, pasted data, CSV file, or sample data

2. Gather the Data

If data warehouse is connected:

  1. Query the necessary data
  2. Embed the results as JSON within the HTML file

If data is pasted or uploaded:

  1. Parse and clean the data
  2. Embed as JSON in the dashboard

If working from a description without data:

  1. Create a realistic sample dataset matching the described schema
  2. Note in the dashboard that it uses sample data
  3. Provide instructions for swapping in real data

3. Design the Dashboard Layout

Follow a standard dashboard layout pattern:

┌──────────────────────────────────────────────────┐
│  Dashboard Title                    [Filters ▼]  │
├────────────┬────────────┬────────────┬───────────┤
│  KPI Card  │  KPI Card  │  KPI Card  │ KPI Card  │
├────────────┴────────────┼────────────┴───────────┤
│                         │                        │
│    Primary Chart        │   Secondary Chart      │
│    (largest area)       │                        │
│                         │                        │
├─────────────────────────┴────────────────────────┤
│                                                  │
│    Detail Table (sortable, scrollable)           │
│                                                  │
└──────────────────────────────────────────────────┘

Adapt the layout to the content:

  • 2-4 KPI cards at the top for headline numbers
  • 1-3 charts in the middle section for trends and breakdowns
  • Optional detail table at the bottom for drill-down data
  • Filters in the header or sidebar depending on complexity

4. Build the HTML Dashboard

Generate a single self-contained HTML file that includes:

Structure (HTML):

  • Semantic HTML5 layout
  • Responsive grid using CSS Grid or Flexbox
  • Filter controls (dropdowns, date pickers, toggles)
  • KPI cards with values and labels
  • Chart containers
  • Data table with sortable headers

Styling (CSS):

  • Professional color scheme (clean whites, grays, with accent colors for data)
  • Card-based layout with subtle shadows
  • Consistent typography (system fonts for fast loading)
  • Responsive design that works on different screen sizes
  • Print-friendly styles

Interactivity (JavaScript):

  • Chart.js for interactive charts (included via CDN)
  • Filter dropdowns that update all charts and tables simultaneously
  • Sortable table columns
  • Hover tooltips on charts
  • Number formatting (commas, currency, percentages)

Data (embedded JSON):

  • All data embedded directly in the HTML as JavaScript variables
  • No external data fetches required
  • Dashboard works completely offline

5. Implement Chart Types

Use Chart.js for all charts. Common dashboard chart patterns:

  • Line chart: Time series trends
  • Bar chart: Category comparisons
  • Doughnut chart: Composition (when <6 categories)
  • Stacked bar: Composition over time
  • Mixed (bar + line): Volume with rate overlay

6. Add Interactivity

Filters:

javascript
// All filters update a central filter state
// Charts and tables re-render when filters change
function applyFilters() {
  const filtered = data.filter((row) => matchesFilters(row));
  updateKPIs(filtered);
  updateCharts(filtered);
  updateTable(filtered);
}

Table sorting:

  • Click column headers to sort ascending/descending
  • Visual indicator for current sort column and direction

Tooltips:

  • Charts show detailed values on hover
  • KPI cards show comparison to previous period

7. Save and Open

  1. Save the dashboard as an HTML file with a descriptive name (e.g., sales_dashboard.html)
  2. Open it in the user's default browser
  3. Confirm it renders correctly
  4. Provide instructions for updating data or customizing

Output Template

The generated HTML file follows this structure:

html
<!DOCTYPE html>
<html lang="en">
  <head>
    <meta charset="UTF-8" />
    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
    <title>[Dashboard Title]</title>
    <script
      src="https://cdn.jsdelivr.net/npm/chart.js@4.5.1"
      integrity="sha384-jb8JQMbMoBUzgWatfe6COACi2ljcDdZQ2OxczGA3bGNeWe+6DChMTBJemed7ZnvJ"
      crossorigin="anonymous"
    ></script>
    <style>
      /* Professional dashboard CSS */
    </style>
  </head>
  <body>
    <div class="dashboard">
      <header><!-- Title and filters --></header>
      <section class="kpis"><!-- KPI cards --></section>
      <section class="charts"><!-- Chart containers --></section>
      <section class="details"><!-- Data table --></section>
    </div>
    <script>
      const DATA = [
        /* embedded JSON data */
      ];
      // Dashboard initialization and interactivity
    </script>
  </body>
</html>

Tips

  • Dashboards are fully self-contained HTML files -- share them with anyone by sending the file
  • For real-time dashboards, consider connecting to a BI tool instead. These dashboards are point-in-time snapshots
  • Request "dark mode" or "presentation mode" for different styling
  • You can request a specific color scheme to match your brand

Frequently asked questions

What does the Data Build Dashboard AI skill do?

Build an interactive HTML dashboard with charts, filters, and tables

Why use Data Build Dashboard on TypingMind?

Because you install it once and use it with any model. Data Build Dashboard 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 Data Build Dashboard in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/frumu-ai/tandem/tree/main/apps/tandem-desktop/src-tauri/resources/skill-templates/data-build-dashboard. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Data Build Dashboard?

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 Data Build Dashboard?

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

Is the Data Build Dashboard AI skill free?

It is published on GitHub by frumu-ai. Check the repository for licensing terms. 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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