Help Wanted

AI Summary: This bug report describes issues with how array data types, specifically tags, are handled in a mapping function and during dynamic updates. The current implementation fails when PostgreSQL returns array data as raw strings instead of native JavaScript arrays, leading to parsing errors. Additionally, clearing tag lists via an empty array during updates causes data synchronization problems due to improper parameter handling.

AI Summary: This issue is a beginner-friendly task to add a new Japanese grammar point, "〜てもらう" (receive a favor), to a JSON file. It requires no coding and can be completed in under a minute by starring, forking, editing the JSON file, and submitting a pull request.

AI Summary: The `eventsRepository.update` method incorrectly handles clearing optional fields to NULL. It uses a COALESCE clause in SQL that, when combined with a JavaScript nullish coalescing operator, prevents explicit `null` values from updating the database column to NULL. This results in the field retaining its previous value instead of being cleared.

AI Summary: The `eventsRepository.update` method has a bug where passing `null` to clear optional database fields is ignored due to the use of `COALESCE` in the SQL query. The proposed solution is to dynamically build the SQL query based on the provided patch object, ensuring that `null` or empty string values are correctly applied to the database.

AI Summary: The user is experiencing an issue where the generated audio randomly switches to different voices, even when a single reference audio file is provided. This occurs with both zero-shot and finetuned models, and the voice can even change to a different gender than the reference. The user is seeking a way to ensure the generated audio consistently uses only the voice from the reference file.

AI Summary: This issue requests documentation updates to reflect a change in priority behavior. Previously, priority was managed per-queue, but it is now global across all functions and queues. The documentation needs to be updated wherever priority behavior is currently described.

AI Summary: This issue proposes adding a macOS-style animated dock to EaseMotion CSS. The dock would feature icons that enlarge on hover, display labels on hover, and include a bounce animation and glassmorphism background, all implemented using CSS.

AI Summary: This issue proposes to improve error handling in the Python Iggy SDK by introducing a structured `IggyError` class. This new error type will provide more detailed information about Iggy-specific failures, including a code, a stable name, and a human-readable message, replacing generic Python exceptions.

AI Summary: This issue proposes adding built-in support for Angular Karma test runs (`ng test`) to RTK. Currently, RTK does not process the verbose output of `ng test`, leading to wasted CI tokens and a less actionable test summary. The goal is to rewrite `ng test` invocations to be handled by RTK, filtering out noise and preserving only essential information like failures and summaries.

AI Summary: This is a zero-bounty task to fix the frontmatter of a single lesson file (`agent-manual-update-timeout.md`). The goal is to ensure the frontmatter adheres to a standard YAML format, preserving the original lesson content and passing specific validation scripts. This task is intended to improve the search quality for AI agents.

AI Summary: This is a zero-bounty task to fix the frontmatter of a single lesson file, `agent-state-database-lock-cleanup.md`. The goal is to ensure the frontmatter adheres to a standard YAML format with specific keys (title, domain, tags, status, source) without altering the lesson content or other files. The fix is intended to improve search quality and the reliability of an AI agent index.

AI Summary: This issue proposes integrating YouTube's timeline heatmap data into the ImprovedTube extension. This heatmap, which shows viewer engagement across a video's duration, could be used to automatically identify and skip irrelevant sections like intros or filler, thereby enhancing speed-watching capabilities.

AI Summary: This issue proposes adding built-in support for the Bruno CLI (`bru`) within the RTK framework. Currently, RTK does not process Bruno's structured output, leading to verbose and token-inefficient API test runs. The goal is to enable RTK to rewrite `bru` commands, parse Bruno's output, and provide a more compact and faithful summary, improving RTK's completeness for common API testing workflows.

AI Summary: This issue proposes implementing strategic blocking features for channels based on their popularity, category, and the concept of "monoculture." It suggests allowing users to filter out channels using range sliders for subscriber counts and to blacklist or whitelist entire categories, with the option to apply these rules conditionally based on time or user interests.