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/sortingnpx skills add TanStack/table --skill sortinggit 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 | $0.00043 | $0.00719 |
| Opus 5 | $0.00022 | $0.00360 |
| Sonnet 5 | $0.00009 | $0.00144 |
| Haiku 4.5 | $0.00004 | $0.00072 |
Grade A, and why
sorting 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 — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
This skill builds on core, table-features, and client-vs-server. Sorting state describes order; client processing requires a sorted model and server processing requires sorted input.
Setup
import {
createSortedRowModel,
rowSortingFeature,
sortFn_alphanumeric,
sortFn_text,
tableFeatures,
} from '@tanstack/table-core'
export const features = tableFeatures({
rowSortingFeature,
sortedRowModel: createSortedRowModel(),
sortFns: { alphanumeric: sortFn_alphanumeric, text: sortFn_text },
})
Import individual sortFn_* built-ins and register only those your columns
reference by string name or that sortFn: 'auto' should resolve for your data
types. The full sortFns registry object still works but bundles every
built-in; numeric columns fall back to a basic comparator without registration.
Core Patterns
const options = { enableSortingRemoval: false, enableMultiSort: true }
const numericColumn = { sortUndefined: 'last' as const }
Configure sort cycles and undefined placement to match the product rather than relying on implicit defaults.
Common Mistakes
[CRITICAL] Expecting manual mode to reorder
Wrong: const options = { data: unsortedRows, manualSorting: true }
Correct: const options = { data: serverSortedRows, manualSorting: true }
Manual sorting bypasses sortedRowModel and trusts incoming order.
Source: packages/table-core/src/features/row-sorting/rowSortingFeature.types.ts
[HIGH] Reversing inside the comparator
Wrong: const newest: SortFn<any, any> = (a, b, id) => b.getValue<number>(id) - a.getValue<number>(id)
Correct: const numeric: SortFn<any, any> = (a, b, id) => a.getValue<number>(id) - b.getValue<number>(id)
Return ascending comparison only; Table reverses it when sorting is descending.
Source: docs/framework/react/guide/sorting.md#custom-sorting-functions
[MEDIUM] Leaving ambiguous sort policy
Wrong: const options = { enableSortingRemoval: true }
Correct: const options = { enableSortingRemoval: false }; const rankColumn = { sortUndefined: 'last' as const }
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 · 83 lines · 43 tokens per session scan A 9d49320e546a
sorting is a skill published in the GitHub repository TanStack/table (28,393 stars, last pushed 2d ago), licensed MIT. It adds 43 tokens to every session and 719 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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