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/with-tanstack-querynpx skills add TanStack/table --skill with-tanstack-querygit 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 | $0.00042 | $0.00887 |
| Opus 5 | $0.00021 | $0.00443 |
| Sonnet 5 | $0.00008 | $0.00177 |
| Haiku 4.5 | $0.00004 | $0.00089 |
Grade A, and why
with-tanstack-query scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.
This skill builds on @tanstack/table-core#client-vs-server, getting-started, and table-state. Decide the server-owned stages and dataset before wiring Query.
Setup
import {
injectQuery,
keepPreviousData,
} from '@tanstack/angular-query-experimental'
import { signal } from '@angular/core'
import {
injectTable,
rowPaginationFeature,
tableFeatures,
} from '@tanstack/angular-table'
const features = tableFeatures({ rowPaginationFeature })
const EMPTY_ROWS: never[] = []
export class PeopleTable {
readonly pagination = signal({ pageIndex: 0, pageSize: 20 })
readonly query = injectQuery(() => ({
queryKey: [
'people',
this.pagination().pageIndex,
this.pagination().pageSize,
],
queryFn: () =>
fetch(
`/api/people?page=${this.pagination().pageIndex}&size=${this.pagination().pageSize}`,
).then((r) => r.json()),
placeholderData: keepPreviousData,
}))
readonly table = injectTable(() => ({
features,
columns,
data: this.query.data()?.rows ?? EMPTY_ROWS,
rowCount: this.query.data()?.rowCount ?? 0,
manualPagination: true,
state: { pagination: this.pagination() },
onPaginationChange: (next) =>
typeof next === 'function'
? this.pagination.update(next)
: this.pagination.set(next),
}))
}
Core Patterns
Track every server-owned input
Read pagination, sorting, and filtering signals inside injectQuery(() => ...) and include them in the query key. Return data already processed for each manual stage.
Keep Query data authoritative
Read the Query signal directly in injectTable. Create another signal only for a deliberate editable draft with an explicit cache synchronization policy.
Common Mistakes
HIGH Capturing query inputs outside tracking
Wrong:
const page = this.pagination().pageIndex
readonly query = injectQuery(() => ({ queryKey: ['people', page], queryFn }))
Correct:
readonly query = injectQuery(() => ({ queryKey: ['people', this.pagination().pageIndex], queryFn }))
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.
- yesterday First seen · 143 lines · 42 tokens per session scan A 8f726846c423
with-tanstack-query is a skill published in the GitHub repository TanStack/table (28,393 stars, last pushed 2d ago), licensed MIT. It adds 42 tokens to every session and 887 once invoked, about $0.0002 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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