Here's what we generate from a job description.

Candidate answer

A) The component will not re-render because it only reads `selectedRowIds`, which has not changed.

Grader feedback

The correct answer is B. When useDashboardStore is called with no selector argument, the component subscribes to the entire store state object. Any state change, including a change to filters, will cause a re-render because the reference to the returned state object changes on every update. The candidate selected A, which describes what would happen if a selector like (s) => s.selectedRowIds were used. This is a foundational Zustand behavior that is worth reviewing.

Candidate answer

import { useQuery, useQueryClient } from '@tanstack/react-query';
import { useState, useEffect } from 'react';

export interface Report {
  id: string;
  name: string;
  createdAt: string;
  value: number;
}

export interface PaginatedResponse<T> {
  data: T[];
  totalPages: number;
  currentPage: number;
}

async function fetchReports(page: number): Promise<PaginatedResponse<Report>> {
  const response = await fetch(`/api/reports?page=${page}&pageSize=50`);
  if (!response.ok) throw new Error('Failed to fetch reports');
  return response.json();
}

export interface UsePaginatedReportsResult {
  data: PaginatedResponse<Report> | undefined;
  isLoading: boolean;
  isError: boolean;
  currentPage: number;
  goToNextPage: () => void;
  goToPreviousPage: () => void;
}

export function usePaginatedReports(): UsePaginatedReportsResult {
  const [currentPage, setCurrentPage] = useState(1);

  const { data, isLoading, isError } = useQuery({
    queryKey: ['reports', currentPage],
    queryFn: () => fetchReports(currentPage),
  });

  const goToNextPage = () => {
    setCurrentPage(currentPage + 1);
  };

  const goToPreviousPage = () => {
    setCurrentPage(currentPage - 1);
  };

  return {
    data,
    isLoading,
    isError,
    currentPage,
    goToNextPage,
    goToPreviousPage,
  };
}

Grader feedback

The hook is structurally correct: useState initialised to 1, useQuery with a key that includes currentPage, and goToPreviousPage and goToNextPage functions. The return type annotation is present and accurate. However, two requirements from the spec are missing. First, there is no prefetch of the next page: the description explicitly asks for a useEffect that calls queryClient.prefetchQuery for currentPage + 1, which is what makes navigation feel instant. Second, goToPreviousPage does not clamp at 1, meaning a user on page 1 could set currentPage to 0 and fire a request for page 0. The goToNextPage and goToPreviousPage functions would also benefit from using the functional updater form, setCurrentPage((prev) => prev + 1), to avoid acting on a stale closure. Overall, the core pattern is solid and the TypeScript is clean, but the two missing requirements are meaningful gaps.

Candidate answer

## Summary

This pull request refactors the `ReportTable` component to leverage
TanStack Query for data fetching, replacing the previous manual
implementation based on `useEffect` and local component state.

## Motivation

The existing implementation manages three separate pieces of state
(`data`, `loading`, and `error`) within the component itself. This
approach, while functional, introduces several challenges:

- **Lack of caching**: Every mount triggers a fresh network request.
- **Race conditions**: Rapid changes to `orgId` may result in stale
  responses being applied out of order.
- **Boilerplate**: The imperative pattern requires substantial repetition
  across components.

## Changes

- Introduced a dedicated `fetchReports` function for improved separation
  of concerns.
- Replaced the `useEffect` and `useState` logic with a single `useQuery`
  invocation.
- Adopted a structured query key (`['reports', orgId]`) to enable granular
  cache invalidation.
- Enhanced error handling by leveraging the built-in `isError` state.

## Reviewer Considerations

Reviewers should pay particular attention to the query key structure, as
this determines caching granularity. It is also worth noting that error
messaging is now handled generically.

## Follow-up Work

Future iterations could explore prefetching, optimistic updates, and a
shared query client configuration to further enhance the developer
experience.

Grader feedback

The PR description covers all three required areas: what changed, why, and follow-up work. The motivation section correctly identifies caching, race conditions, and boilerplate as the problems being solved. The changes list accurately describes the structural difference. The follow-up mentions prefetching and a shared query client configuration, which aligns with the model answer's suggestion about a QueryClient provider and moving fetchReports to a shared module. The main gap is that the staleTime and retry configuration considerations are not mentioned, and the description does not call out that the queryKey ties cache entries to orgId specifically. The formatting is very polished with markdown headers and bold bullets, which may be appropriate for some teams but is heavier than a typical PR body in many organisations. The substance is good, but some of the phrasing is generic.

Candidate answer

Write me a React component for a paginated report table.

It should use TanStack Query to fetch the data and Zustand for the state. It
needs to be in TypeScript. Make sure it handles pagination and sorting, and
add loading and error states. Use best practices and make it production
ready.

Grader feedback

The prompt is too generic to be useful. It names TanStack Query and Zustand but omits versions, which matters because the keepPreviousData API changed between TanStack Query v4 and v5. It does not specify the query parameter contract (sort_field, sort_direction), the Zustand store shape, or any TypeScript interface expectations. The requirement to keep the previous page visible while loading is stated in the problem but absent from the prompt, so the AI would have no reason to use placeholderData or keepPreviousData. There is no mention of strict mode, no success criteria, and no edge cases called out. A prompt this sparse would produce generic boilerplate that the candidate would then need to heavily revise, which defeats the purpose of the collaboration.