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/create-table-hooknpx skills add TanStack/table --skill create-table-hookgit 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 | $0.00050 | $0.00749 |
| Opus 5 | $0.00025 | $0.00375 |
| Sonnet 5 | $0.00010 | $0.00150 |
| Haiku 4.5 | $0.00005 | $0.00075 |
Grade A, and why
create-table-hook 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 — 99 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 plus this package's getting-started and table-state skills.
Setup
import Alpine from 'alpinejs'
import { createTableHook, tableFeatures } from '@tanstack/alpine-table'
type Person = { id: string; name: string }
const { createAppTable, createAppColumnHelper } = createTableHook({
features: tableFeatures({}),
getRowId: (row: Person) => row.id,
})
const helper = createAppColumnHelper<Person>()
const columns = helper.columns([helper.accessor('name', { header: 'Name' })])
Alpine.data('peopleTable', () => {
const local = Alpine.reactive({
data: [{ id: '1', name: 'Ada' }] as Array<Person>,
})
const table = createAppTable({
columns,
get data() {
return local.data
},
})
return { table }
})
Core Patterns
Share infrastructure, keep data local
Bind features, row models, row IDs, and defaults in the factory. Each Alpine component passes its own columns, reactive data getter, and controlled state.
Reuse markup with Alpine primitives
Use real templates and Alpine.bind bundles for interactive reuse. createTableHook intentionally returns no component registry or context hooks.
Use the helper to retain feature inference
Columns from createAppColumnHelper<TData>() know the factory's registered features without userland feature generics.
Common Mistakes
HIGH Assuming a JSX component registry
Wrong: pass cellComponents or tableComponents to Alpine createTableHook.
Correct: share features/defaults with the hook and build reusable interactive markup with Alpine templates or bind bundles.
The Alpine hook returns only app features, a column helper, and createAppTable.
Source: TanStack/table:packages/alpine-table/src/createTableHook.ts
MEDIUM Abstracting a one-off table
Wrong: introduce an app factory for one table with no shared conventions.
Correct: use standalone createTable until infrastructure repeats.
The hook is an application reuse boundary, not required setup.
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 · 99 lines · 50 tokens per session scan A 80ef98f07268
create-table-hook is a skill published in the GitHub repository TanStack/table (28,393 stars, last pushed 2d ago), licensed MIT. It adds 50 tokens to every session and 749 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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