A comprehensive library of over 1,273 agentic skills for various AI coding assistants, featuring clear documentation and installation instructions.

非线智能 NoneLinear - ReLE评测：中文AI大模型能力评测（持续更新）：目前已囊括374个大模型，覆盖chatgpt、gpt-5.4、谷歌gemini-3.1-pro、Claude-4.6、文心ERNIE-X1.1、ERNIE-5.0、qwen3.6-max、qwen3.6-plus、百川、讯飞星火、商汤senseChat等商用模型， 以及step3.5-flash、kimi-k2.6、ernie4.5、MiniMax-M2.7、deepseek-v4、Qwen3.6、llama4、智谱GLM-5.1、MiMo-V2、LongCat、gemma4、mistral等开源大模型。不仅提供排行榜，也提供规模超200万的大模型缺陷库！方便广大社区研究分析、改进大模型。

Guide on how to set-up Linux and Docker for real-time applications using the Ubuntu realtime-kernel/PREEMPT_RT patch with a focus on robotics with ROS and ROS 2

Collection of best practices for working with Docker/Docker-Compose and the Robot Operating System (ROS/ROS 2) in simulation as well as with hardware and real-time requirements

Use when the user wants to run multiple marketing skills together (brief, blog post, social copy, changelog, newsletter, video script) from a single input, or when they mention "marketing pipeline", "full marketing", or "launch content"

Rewrite existing text under the EW anti-AI rules and the writer's voice profile, then show a structured before/after with specific failure analysis. Use when the user pastes a draft and asks to fix, tighten, de-slop, humanize, critique, or improve it.

Investigate and reduce SigNoz telemetry ingestion cost and metric cardinality across metrics, logs, and traces. Find what drives SigNoz spend (via the Cost Meter), which metrics have runaway or unbounded label cardinality, and safe, dashboard-, alert-, and Infra-page-aware ways to cut volume. Make sure to use this skill whenever the user asks "why is my SigNoz bill so high", "what's driving my ingestion cost", "reduce telemetry volume", "which metrics cost the most", "cardinality health check", or "what can I safely drop" — or otherwise asks about telemetry spend, ingestion volume, or metric cardinality, even if they don't say "cost" or "optimize" explicitly.