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/2428424081cn/skill-mcp/tanstack-query-patternsnpx skills add 2428424081cn/Skill-mcp --skill tanstack-query-patternsgit clone --depth 1 https://github.com/2428424081cn/Skill-mcpWrote 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.
[](https://agentmods.dev/skills/2428424081cn/skill-mcp/tanstack-query-patterns)<a href="https://agentmods.dev/skills/2428424081cn/skill-mcp/tanstack-query-patterns"><img src="https://agentmods.dev/badge/skills/2428424081cn/skill-mcp/tanstack-query-patterns.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00036 | $0.00511 |
| Opus 5 | $0.00018 | $0.00255 |
| Sonnet 5 | $0.00007 | $0.00102 |
| Haiku 4.5 | $0.00004 | $0.00051 |
Grade A, and why
tanstack-query-patterns 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 4d 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.
What it actually says
TanStack Query v5 (React Query) 最佳实践
1. 统一 Query Key Factory 模式
绝不在组件内随意手写散装数组作为 Query Key，必须通过统一工厂对象维护，确保类型安全与精准缓存失效：
export const userKeys = {
all: ['users'] as const,
lists: () => [...userKeys.all, 'list'] as const,
list: (filters: UserFilters) => [...userKeys.lists(), { filters }] as const,
details: () => [...userKeys.all, 'detail'] as const,
detail: (id: string) => [...userKeys.details(), id] as const,
};
2. 乐观更新 (Optimistic Updates) 标准模式
在执行点赞、修改、删除等操作时，先立即更新本地 UI，若网络失败则自动回滚：
export function useUpdateTodo() {
const queryClient = useQueryClient();
return useMutation({
mutationFn: updateTodoApi,
onMutate: async (newTodo) => {
// 1. 取消正在发起的并发请求，防止覆盖乐观状态
await queryClient.cancelQueries({ queryKey: todoKeys.detail(newTodo.id) });
// 2. 备份快照
const previousTodo = queryClient.getQueryData<Todo>(todoKeys.detail(newTodo.id));
// 3. 乐观写入新数据
queryClient.setQueryData<Todo>(todoKeys.detail(newTodo.id), (old) => ({ ...old, ...newTodo }));
return { previousTodo };
},
onError: (err, newTodo, context) => {
// 4. 发生错误时回滚到快照
if (context?.previousTodo) {
queryClient.setQueryData(todoKeys.detail(newTodo.id), context.previousTodo);
}
},
onSettled: (data, err, newTodo) => {
// 5. 最终刷新服务端最新数据
queryClient.invalidateQueries({ queryKey: todoKeys.detail(newTodo.id) });
},
});
}
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 4d ago First seen · 52 lines · 36 tokens per session scan A 78975aee8b15
tanstack-query-patterns is a skill published in the GitHub repository 2428424081cn/Skill-mcp (1 stars, last pushed 11d ago), licensed MIT. It adds 36 tokens to every session and 511 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 2026-08-31.
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