Help Wanted

AI Summary: This issue describes an intermittent but reproducible bug where flicking the analog stick upwards in the recompilation UI causes the menu to scroll rapidly. The problem has also been observed on the BK recomp, indicating a potential underlying issue with input handling or UI scrolling logic.

AI Summary: A unit test for the media job queue on Windows CI is intermittently failing due to a race condition. The test attempts to read a JSON file that may not exist yet because its creation is debounced, causing a `ENOENT` error. The proposed fix modifies the `waitFor` helper to gracefully handle predicate errors by retrying until the timeout, thus preventing premature test failure.

AI Summary: The issue describes a bug where the `${TARGET}` variable in a link flag is incorrectly represented as its Python object's repr string in the `build.ninja` file, instead of expanding to the actual target path. This prevents the intended map file generation. The author expects `${TARGET}` to expand correctly in link flags, similar to how it behaves in `env.Command`.

AI Summary: This issue proposes cherry-picking recent fixes and optimizations from the AssemblyScript mainline branch into the Warpo project. The goal is to incorporate these improvements into Warpo's codebase.

AI Summary: This issue is a beginner-friendly task to add a new Japanese example sentence to a JSON file. No coding is required, and the contribution can be made directly through the browser in under a minute. It's an excellent opportunity for new contributors to get involved.

AI Summary: Two functions in the agent's manager.go, `writeFileAsUser` and `healForeignCodexConfig`, have very low or no test coverage. The issue recommends adding hermetic unit tests using a stubbed `su-exec` to cover the uncovered branches and error conditions, which are considered low effort with medium impact.

AI Summary: This bug report identifies two UI strings that incorrectly claim filter counts are repository-wide. In reality, these counts are cross-filtered based on other active filters. The issue also points out that one of these incorrect statements is self-defeating and misleading when a filter combination results in no matching data.

AI Summary: The 'All' context tab badge in the performance view is not correctly cross-filtered, leading to a discrepancy between its displayed count and the actual filtered data. This issue arises because the 'All' badge uses a repository-wide total that isn't affected by other filters, while the individual context badges are correctly filtered. Consequently, the 'All' badge often shows a much larger number than the sum of the filtered contexts, creating confusion for users.

AI Summary: This issue proposes adding bulk delete functionality for questions, answers, and users in the admin interface and API. This is needed to efficiently clean up spam attacks, which currently require manual deletion of each item and user, leading to hundreds of clicks.

AI Summary: The addon fails to apply all settings (subtitles, audio) when navigating to a video from within YouTube's interface, unlike when opening a direct link. This is because internal navigation doesn't trigger a full page reload, preventing the addon from fully initializing. The user suggests a mechanism to detect and force a reload if settings are not applied correctly.

AI Summary: This issue is a "Good First Issue" that requests the addition of a new Japanese cultural etiquette tip to a JSON file. No coding is required, and the contribution can be made directly from the browser in under a minute, making it ideal for beginners.

AI Summary: This issue proposes refactoring a large React component, `ConfigureCardModal.tsx`, into smaller, more manageable modules. The goal is to improve code organization by extracting sub-components, encapsulating complex logic into custom hooks, and separating form state from rendering. Successful completion will result in files under 400 lines, passing tests, and CI checks.

AI Summary: This issue proposes to refactor a large React component, `CustomDashboard.tsx`, into smaller, more manageable modules. The goal is to improve code organization by extracting sub-components, creating custom hooks for complex logic, and separating form state from rendering, with a target of each new file being under 400 lines.

AI Summary: This issue proposes refactoring two large component files, `CardRuntime.tsx` and `BaseModal.tsx`, into smaller, more manageable modules. The goal is to improve code organization and maintainability by extracting specific logic and UI elements into dedicated helper modules and sub-components, adhering to established refactoring guidelines.

AI Summary: This issue proposes to refactor three large TypeScript files related to unified card rendering into smaller, more manageable components. The goal is to improve code organization and maintainability by separating rendering logic, extracting chart-specific components, and moving data transformation hooks to a shared module. This is a continuation of a previous larger refactoring effort.

AI Summary: This issue proposes to refactor a large TypeScript component, `UnifiedDashboard.tsx`, into smaller, more manageable sub-components and custom hooks. The goal is to improve code organization and maintainability by splitting the file into multiple files, each under 400 lines, while ensuring all existing tests and CI checks pass.

AI Summary: This issue proposes refactoring two large TypeScript files, `DashboardPage.tsx` and `DashboardRuntime.tsx`, into smaller, more manageable components and custom hooks. The goal is to improve code organization and maintainability by splitting out sections like headers, layout grids, and data-fetching logic, adhering to specific refactoring guidelines.

AI Summary: This issue proposes to refactor a large React component, `StatBlockFactoryModal.tsx`, by splitting it into smaller, more manageable modules. The goal is to improve code organization and maintainability by extracting sub-components, creating custom hooks for complex logic, and separating form state from rendering. The refactoring should result in files under 400 lines while ensuring all existing tests and CI checks pass.

AI Summary: This issue proposes to refactor a large `auth.tsx` file into smaller, more manageable modules: an AuthContext, authentication hooks, and utility functions. The goal is to improve code organization and adhere to repository guidelines for file splitting, ensuring all tests and CI checks pass after the changes.

AI Summary: This issue proposes refactoring a large React component, `AddCardModal.tsx`, into smaller, more manageable modules. The goal is to improve code organization by extracting sub-components, encapsulating complex logic into custom hooks, and separating form state from the rendering logic. The refactoring should result in files under 400 lines while maintaining all existing tests and passing CI checks.

AI Summary: This issue proposes refactoring a large `WorkloadImportDialog.tsx` component into smaller, more manageable files. The goal is to improve code organization by extracting logic into a custom hook, separating UI steps into sub-components, and moving constants to a dedicated file, while maintaining existing functionality and test coverage.

AI Summary: This issue proposes refactoring a large `SudokuGame.tsx` component into smaller, more manageable files. The goal is to improve code organization by extracting logic into a custom hook, rendering into a sub-component, and moving constants to a dedicated file, while ensuring existing functionality and tests remain intact.

AI Summary: This issue proposes refactoring the `GPUInventoryHistory.tsx` component into smaller, more manageable container and presentational components. The goal is to improve code organization and maintainability by separating data fetching and logic from UI rendering, adhering to established project guidelines.

AI Summary: This issue proposes refactoring the `Missions.tsx` component into smaller, more manageable container and presentational components. The goal is to improve code organization and maintainability by extracting sub-components and data-fetching logic into separate files, adhering to established project guidelines. The refactoring should not introduce any functional changes and must pass existing tests and CI checks.

AI Summary: This issue proposes refactoring a large React component, `LaunchSequence.tsx`, into smaller, more manageable modules. The goal is to improve code organization by extracting sub-components, encapsulating complex logic into custom hooks, and separating form state from rendering. The refactoring should result in files under 400 lines while ensuring all existing tests and CI checks pass.

AI Summary: This issue proposes refactoring a large `Solitaire.tsx` component into smaller, more manageable files. The goal is to improve code organization by extracting game logic into a custom hook and rendering logic into sub-components, while moving constants to a separate file. The original component will remain as a container.

AI Summary: This issue proposes refactoring a large `KubeDoom.tsx` component into smaller, more manageable parts. The goal is to improve code organization and maintainability by extracting rendering logic, game state management, and constants into separate hooks and files, while keeping the main component as an orchestrator.

AI Summary: This issue proposes refactoring a large React component, `KubeBert.tsx`, into smaller, more manageable parts. The goal is to improve code organization by extracting canvas rendering logic into a hook or sub-component, game state management into another hook, and constants into a separate file, while keeping the main component as a composer.

AI Summary: This issue proposes to refactor the `CardWrapper.tsx` component, which is a large and frequently used core component, into smaller container and presentational sub-components. The goal is to improve maintainability by extracting state and effect logic into dedicated hooks and ensuring all new files are under 400 lines, without altering existing functionality. This is a significant undertaking due to the component's size and the risk of breaking existing tests, as indicated by previous failed attempts.

AI Summary: This issue proposes to refactor a large `Weather.tsx` component (758 lines) into smaller, more manageable files. The plan involves extracting data-fetching logic into a custom hook, and splitting the UI for search, forecast, and hourly weather into separate sub-components, with the original `Weather.tsx` serving as a container. The goal is to improve code organization and maintainability, ensuring all split files are under 400 lines and existing tests remain valid.