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Data Tables

Community
param087
data-tables

Use when building data tables — sorting, filtering, pagination, row selection and bulk actions with TanStack Table + shadcn/ui, plus the loading, empty, and error states tables almost always forget.

Overview

Publisherparam087
Repositorysaas-ui-skills
Skill namedata-tables
Stars
3
Forks
0
Bundled files
Instructions only
LicenseMIT
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 param087 on GitHub. Read the source before you install it.

Installation

Install the Data Tables 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.
    https://github.com/param087/saas-ui-skills/tree/main/skills/data-tables
  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/param087/saas-ui-skills.git /tmp/saas-ui-skills
mkdir -p .claude/skills
cp -r /tmp/saas-ui-skills/skills/data-tables .claude/skills/data-tables
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Data Tables 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 Tables 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 Tables 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.

Data Tables

Overview

Tables are where SaaS apps live (users, invoices, logs). Build them with TanStack Table (headless logic: sorting, filtering, pagination, selection) rendered through shadcn/ui Table primitives. Separate column definitions from the table shell so every table in the app behaves consistently.

When to use

  • Displaying lists of records with sort/filter/paginate.
  • Bulk actions on selected rows.
  • A <table> is being hand-built with manual sort state.

Column definitions

tsx
import { ColumnDef } from "@tanstack/react-table";
import { Checkbox } from "@/components/ui/checkbox";
import { Badge } from "@/components/ui/badge";

export type Invoice = { id: string; customer: string; status: "paid" | "open" | "void"; amount: number };

export const columns: ColumnDef<Invoice>[] = [
  {
    id: "select",
    header: ({ table }) => (
      <Checkbox
        checked={table.getIsAllPageRowsSelected()}
        onCheckedChange={(v) => table.toggleAllPageRowsSelected(!!v)}
        aria-label="Select all"
      />
    ),
    cell: ({ row }) => (
      <Checkbox
        checked={row.getIsSelected()}
        onCheckedChange={(v) => row.toggleSelected(!!v)}
        aria-label="Select row"
      />
    ),
    enableSorting: false,
  },
  { accessorKey: "customer", header: "Customer" },
  {
    accessorKey: "status",
    header: "Status",
    cell: ({ row }) => <Badge variant={row.original.status === "paid" ? "success" : "secondary"}>{row.original.status}</Badge>,
  },
  {
    accessorKey: "amount",
    header: () => <div className="text-right">Amount</div>,
    cell: ({ row }) => <div className="text-right tabular-nums">${(row.original.amount / 100).toFixed(2)}</div>,
  },
];

The reusable shell

tsx
const table = useReactTable({
  data, columns,
  getCoreRowModel: getCoreRowModel(),
  getSortedRowModel: getSortedRowModel(),
  getPaginationRowModel: getPaginationRowModel(),
  getFilteredRowModel: getFilteredRowModel(),
  state: { sorting, rowSelection, globalFilter },
  onSortingChange: setSorting,
  onRowSelectionChange: setRowSelection,
});

Render header/body from table.getHeaderGroups() / table.getRowModel().rows. Always handle the three non-happy states:

tsx
{isLoading ? (
  <TableRow><TableCell colSpan={columns.length}><Skeleton className="h-8 w-full" /></TableCell></TableRow>
) : rows.length === 0 ? (
  <TableRow><TableCell colSpan={columns.length} className="h-24 text-center text-muted-foreground">No results.</TableCell></TableRow>
) : (
  rows.map((row) => <TableRow key={row.id} data-state={row.getIsSelected() && "selected"}>…</TableRow>
)}

Bulk actions

When table.getSelectedRowModel().rows.length > 0, show an action bar:

tsx
{selectedCount > 0 && (
  <div className="flex items-center gap-2 rounded-md border bg-muted/50 px-3 py-2 text-sm">
    <span>{selectedCount} selected</span>
    <Button size="sm" variant="destructive" onClick={deleteSelected}>Delete</Button>
  </div>
)}

Server-side at scale

For large datasets, set manualPagination/manualSorting/manualFiltering: true and pass state to your API. Keep filter/sort/page in the URL (searchParams) so views are shareable and survive refresh.

Pitfalls

  • No loading/empty/error states — the #1 omission; a blank table looks broken.
  • Right-align numbers + tabular-nums — left-aligned currency is hard to scan.
  • Client-paginating 50k rows — move to server-side; don't ship it all.
  • Selection lost on page change unless you key it by row id.
  • Non-accessible sort headers — make them <button>s with aria-sort.
  • Filter/sort only in component state — put it in the URL for shareable views.

Hand-off

A consistent table that pairs with empty-and-loading-states (skeletons), modals-and-dialogs (row edit/confirm), and notifications-and-toasts (bulk-action feedback).

Frequently asked questions

What does the Data Tables AI skill do?

Use when building data tables — sorting, filtering, pagination, row selection and bulk actions with TanStack Table + shadcn/ui, plus the loading, empty, and error states tables almost always forget.

Why use Data Tables on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/param087/saas-ui-skills/tree/main/skills/data-tables. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Data Tables?

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 Tables?

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

Is the Data Tables AI skill free?

Yes. It is published on GitHub by param087 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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