KDE Plasma AI Quota HUD: My Arch Linux Setup

A developer built a KDE Plasma panel HUD for Arch Linux that tracks AI quota usage across Claude, Codex, Gemini, and DeepSeek using four circular indicators, after fixing a bug caused by relying on positional data in API responses. The system now uses duration-based identification and state validation to handle schema changes from providers like Codex.

KDE Plasma AI Quota HUD: My Arch Linux Setup Claude /en/tags/claude/ Code, Codex, Gemini, and DeepSeek on Arch Linux is a logistical nightmare. When you're deep into a complex task with massive context and an hour of iteration, the last thing you want is to hit a rate limit mid- git rebase . To solve this, I built a HUD for the KDE panel that tracks remaining room and reset times for each agent via four circular indicators. The "Token-Week" Problem The industry has created a bizarre new unit of measurement: the token-hour or token-week. Every provider does it differently: Claude: Uses rolling hour/day windows. Codex: Reports specific plan windows.Requires local request estimation. Gemini /en/tags/gemini/ :Operates on a monetary balance. DeepSeek /en/tags/deepseek/ : I've essentially turned my panel into a dashboard of "donuts." A full ring means the agent is ready; an empty one means it's time to switch models. Hovering provides the exact reset time, so I don't have to leave my terminal to check if I've exhausted my limits. Technical Pivot: Data over Position My initial deployment failed because I relied on the position of data in the API response. For Codex, I assumed the first window returned was the 5-hour limit and the second was the weekly limit. When Codex changed their schema and stopped reporting the short window, my logic broke. The widget started labeling a 7-day window as "5h" because it was the first item in the list. To fix this for a more robust AI workflow, I implemented two changes: 1. Duration-based Identification: The system now identifies windows by their actual length. Short durations are flagged as sessions; long durations are flagged as weekly limits. 2. State Validation: I decoupled "failed queries" from "missing data." If a query fails, the HUD preserves the last cached value. If a query succeeds but a window is missing, the HUD removes that window from the state entirely. This prevents the "ghost value" bug where a depleted quota appears active just because the API call timed out. For anyone building a custom LLM agent monitor, avoid positional indexing at all costs—API schemas shift too often. Next SEO Automation vs. Domain Authority: A Reality Check → /en/threads/3771/