Janitorr automates scheduled cleanup for Jellyfin stacks

// 2h agoVIDEO

Janitorr automates scheduled cleanup for Jellyfin stacks

Janitorr is an open-source cleanup tool for self-hosted media stacks that connects Radarr, Sonarr, Jellyseerr, and Jellyfin to track watched or aged content and delete it on a schedule. It also creates a “leaving soon” collection in Jellyfin so users can see what is about to be removed before the cleanup runs.

// ANALYSIS

Useful if you already run a *arr + Jellyfin setup and want retention to be automated instead of managed by hand.

–Ties deletion decisions to the wider media stack, not just Jellyfin alone.
–Adds a visible warning window via the “leaving soon” collection, which reduces surprise deletions.
–Best fit for users comfortable with scheduled automation and careful config.
–The main tradeoff is trust: this is powerful cleanup automation, so dry-run and exclusion tags matter.

// TAGS

self-hostedjellyfinsonarrradarrjellyseerrmedia-managementautomation

DISCOVERED

2h ago

2026-05-11

PUBLISHED

2h ago

2026-05-11

RELEVANCE

6/ 10

AUTHOR

Github Awesome

// KEEP READING

More AI developer news from the feed

EXPLORE FULL FEED

NEWS40m ago

Grok Skills preview hints at task automation

xAI appears to be building a custom Skills system for Grok that lets users save reusable instruction sets and import them as `.zip`, `.skill`, or `.md` packages. The feature is still behind a flag, so this is a preview rather than a public rollout.

UPDATE1h ago

OpenClaw adds Code Mode for tools

This post is a product update about OpenClaw, highlighting a new Code Mode that expands the agent beyond plain shell execution. The core idea is that shell can compose shell commands, but Code Mode can also orchestrate MCP tools, app tools, dynamic tools, structured JSON outputs, loops, filters, maps, and conditionals inside a single runtime cell. The author frames it as an additional composition path rather than a replacement, with an opt-out via `code_mode_only` so the model can still use normal tools directly.

BENCHMARK1h ago

llama.cpp Vulkan stumbles on Arrow Lake

A Reddit user says llama.cpp’s Vulkan backend performs terribly on an Arrow Lake Arc 130T iGPU, with decent prompt processing but sub-4 tok/s generation on Gemma 4 E4B. The thread frames SYCL and other Intel-native backends as the real alternative, not Vulkan.