data-fetching

data-fetching is a skill for Claude Code, Codex from mercuryPark/oc-setup. It costs 22 tokens per session (307 once invoked), scanned A, original, MIT.

A collection of patterns for loading and changing data in React applications, using tools such as React Query and SWR. It includes pagination, loading states, and optimistic updates, where the interface changes before the server confirms the change.

In plain words
What is it for?
Use it to fetch lists, load more results, update data with rollback on failure, and choose cursor-based or offset-based pagination.
Why use it?
It provides established ways to manage server data instead of handling requests, errors, caching, and rollback logic from scratch.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/mercurypark/oc-setup/data-fetching
Any agent
npx skills add mercuryPark/oc-setup --skill data-fetching
Clone the repo
git clone --depth 1 https://github.com/mercuryPark/oc-setup

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for data-fetching

README.md
[![agentmods](https://agentmods.dev/badge/skills/mercurypark/oc-setup/data-fetching.svg)](https://agentmods.dev/skills/mercurypark/oc-setup/data-fetching)
Your own site
<a href="https://agentmods.dev/skills/mercurypark/oc-setup/data-fetching"><img src="https://agentmods.dev/badge/skills/mercurypark/oc-setup/data-fetching.svg" alt="Measured on agentmods" height="20"></a>
Per session 22 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 307 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What 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.

ModelPer sessionOnce invoked
Fable 5 $0.00022 $0.00307
Opus 5 $0.00011 $0.00153
Sonnet 5 $0.00004 $0.00061
Haiku 4.5 $0.00002 $0.00031

Measured 5d ago against content hash 252fa6f894c2, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

data-fetching 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 5d 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.

templates/skills/data-fetching/SKILL.md · 53 lines

What it actually says

Data Fetching Patterns

Basic Setup

import { useQuery, useMutation, QueryClient } from '@tanstack/react-query'

const queryClient = new QueryClient()

function UserList() {
  const { data, isLoading } = useQuery({
    queryKey: ['users'],
    queryFn: fetchUsers
  })
}

Mutations with Optimistic Updates

const mutation = useMutation({
  mutationFn: updateUser,
  onMutate: async (newUser) => {
    await queryClient.cancelQueries({ queryKey: ['users'] })
    const previousUsers = queryClient.getQueryData(['users'])
    queryClient.setQueryData(['users'], (old) => [...old, newUser])
    return { previousUsers }
  },
  onError: (err, newUser, context) => {
    queryClient.setQueryData(['users'], context.previousUsers)
  }
})

Pagination

Cursor-based

const { data, fetchNextPage } = useInfiniteQuery({
  queryKey: ['users'],
  queryFn: ({ pageParam }) => fetchUsers(pageParam),
  getNextPageParam: (lastPage) => lastPage.nextCursor
})

Offset-based

Use for predictable page sizes and SEO-friendly URLs.

Changes

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.

  1. 5d ago First seen · 53 lines · 22 tokens per session scan A 252fa6f894c2

Subscribe to this mod's changes

data-fetching is a skill published in the GitHub repository mercuryPark/oc-setup (2 stars, last pushed 4mo ago), licensed MIT. It adds 22 tokens to every session and 307 once invoked, about $0.0001 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 2026-08-31.

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