Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/tanstack/table/getting-startednpx skills add TanStack/table --skill getting-startedgit clone --depth 1 https://github.com/TanStack/tableWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00060 | $0.00829 |
| Opus 5 | $0.00030 | $0.00415 |
| Sonnet 5 | $0.00012 | $0.00166 |
| Haiku 4.5 | $0.00006 | $0.00083 |
Grade A, and why
getting-started scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
This skill builds on @tanstack/table-core#core and @tanstack/table-core#table-features.
Setup
import Alpine from 'alpinejs'
import {
FlexRender,
createTable,
tableFeatures,
type ColumnDef,
} from '@tanstack/alpine-table'
type Person = { id: string; name: string }
const features = tableFeatures({})
const columns: Array<ColumnDef<typeof features, Person>> = [
{ accessorKey: 'name', header: 'Name' },
]
Alpine.data('peopleTable', () => {
const local = Alpine.reactive({
data: [{ id: '1', name: 'Ada' }] as Array<Person>,
})
const table = createTable({
features,
columns,
get data() {
return local.data
},
getRowId: (row) => row.id,
})
return { table, FlexRender }
})
window.Alpine = Alpine
Alpine.start()
Render real table structure with x-for; use x-html="FlexRender({ header })" or x-html="FlexRender({ cell })" only for renderer output.
Core Patterns
Pass live options through getters
Wrap changing data in an Alpine.reactive({ data }) object and read local.data through get data(). The property read gives the adapter's effect a dependency to track before it calls table.setOptions.
Read table APIs directly in bindings
The adapter returns a reactive proxy. Expressions such as x-text="table.getRowModel().rows.length" update without a Subscribe component.
Render interaction controls as real markup
Buttons, inputs, and directives belong in the template. Renderer strings are useful for cell content, but x-html does not initialize Alpine directives inside the injected HTML.
Common Mistakes
HIGH Passing a data snapshot
Wrong: createTable({ features, columns, data: local.data }) when local.data will be replaced.
Correct: expose get data() { return local.data }.
The adapter tracks option getters; a captured array does not follow later replacements.
Source: TanStack/table:packages/alpine-table/src/createTable.ts
HIGH Interactive directives hidden in x-html
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 109 lines · 60 tokens per session scan A 9f28ce916992
getting-started is a skill published in the GitHub repository TanStack/table (28,393 stars, last pushed 2d ago), licensed MIT. It adds 60 tokens to every session and 829 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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