Plugins

Infrastructure and tools for decentralized messaging protocol integration and messaging agent development.

XP marketplace MCP (open-world tools) + ticket skills, commands, and a ticket-purchase agent

Deep research + planning + execution framework. Spawns parallel research/review agents, creates comprehensive plans, and executes via parallel agent waves.

A minimal, evidence-driven development flow.

TPU/XLA profiling analysis: MCP tools for XProf HTTP API (operator breakdowns, memory profiles, A/B comparisons) + methodology skills for trace parsing, MFU calculation, bottleneck identification

Launch a Docker container with Intel GPU access on Linux. Encodes the correct combination of `--device /dev/dri`, render-group access, `--ipc=host`, `ZE_AFFINITY_MASK` pinning, Hugging Face cache mount, and `--entrypoint /bin/bash` for interactive use. Use when running any Intel-XPU container (vLLM-XPU, sglang-xpu, torch-XPU, llama.cpp SYCL, etc.) and the device must be visible inside. The CUDA analogue is `docker run --gpus all` — Intel has no `--gpus` flag, you pass the Direct Rendering Manager (DRM) nodes directly.

Plan an end-to-end Intel XPU model deployment by chaining existing skills. Calls xpu-runtime-preflight (readiness), model-can-it-fit (sizing), model-config-recommend (flags), and the selected runtime skill (vllm-xpu-run / sglang-xpu-run / torch-xpu-run), then writes a single PLAN.md with one exact launch command, smoke test, and rollback to .out/skills/xpu-deploy-plan/. Use when the user asks to deploy a model on an Intel GPU end-to-end, wants a single coordinated plan, or asks which skills to run and in what order.

Inventory Intel GPUs (Arc, Arc Pro, Data Center GPU Max) on a Linux host. Detect devices, check driver health, list processes using each XPU, run a quick diagnostic, and read live utilisation.

Detect whether a Hugging Face model is text generation, text encoder, seq2seq, masked LM, vision classification, vision-language (CLIP), audio encoder, audio seq2seq, multimodal VL, diffusion, time-series, or a reward model before loading it on Intel XPU. Pairs with torch-xpu-run and vllm-xpu-run so the agent picks the right AutoModel class and input kwargs and avoids wrong-input failures after a 20-second load.

Execute a single-target CUDA-to-XPU port of a PyTorch repo with libcst-based scan, mechanical rewrite, and CPU FP64 vs target-dtype correctness verify on one forward pass. Use when the request says "port" — "port my repo to XPU", "port my repo at <path> to XPU", "rewrite the CUDA calls to XPU", "apply the mechanical transforms", "run the scan and rewrite", "make the port changes now". Not for the "migrate" verb ("migrate my repo", "migrate this repo to XPU") or a bare whole-repo workflow request where scope is not yet set — those start with cuda-to-xpu-migration, whose plan routes here. Not for assessment-only, throughput (torch-xpu-bench), op-level slowness (torch-xpu-profile), custom CUDA C++ extensions, or dual-target CUDA+XPU codebases.

Profile Intel-XPU workloads at the SYCL / Level Zero kernel level via Intel pti-gpu's unitrace. Captures per-API-call and per-kernel timing, memory transfers, oneCCL / MPI events, and hardware counters PyTorch-level profilers cannot see. Use when a hot op is already known at the torch.profiler layer and the user needs the SYCL kernel beneath, or when profiling oneCCL collectives in multi-GPU runs. Not for PyTorch-level signal (use torch-xpu-profile / vllm-xpu-profile). Requires building unitrace from source.

Run a read-only go/no-go preflight before any Intel GPU/XPU skillpack work. Checks driver health, /dev/dri permissions, render/video groups, Docker, /dev/shm, disk, proxy, and optional container-level XPU visibility. Use when the user asks whether a machine is ready for XPU model work or needs a reusable lab readiness report. Not for launching workloads, pulling images, editing system config, or verifying model output.

First-time setup for Intel XPU/GPU hosts. Detects what's missing and installs xpu-smi, configures user groups (render), sets up Intel GPU PPA repository, installs Level Zero runtime, installs Docker, and runs a post-setup verification gate. Prompts before each installation by default (use --auto for unattended). Also handles Battlemage (Arc Pro B60/B70) prerequisites on Ubuntu 24.04: nomodeset removal, OEM kernel upgrade, and compute runtime 26.18+ — use check_battlemage_prerequisites.sh when xpu-smi shows No device discovered or clinfo shows 0 platforms. Use when a bare-metal or minimally-configured machine needs to be prepared for XPU model work.

XQuery language intelligence for Claude Code (diagnostics, go-to-definition, hover, find-references) powered by xq-lsp.

Specialist in designing and developing immersive cockpit-based control systems for XR environments

座舱控制系统与沉浸式控制界面专家

Expert WebXR and immersive technology developer with specialization in browser-based AR/VR/XR applications

WebXR、浏览器端 AR/VR 沉浸式体验开发专家

Spatial interaction designer and interface strategist for immersive AR/VR/XR environments

空间交互设计与沉浸式 UX 专家（AR/VR/XR）

Xray import, spec-implementer, regression-preventer & change-evaluator skills + read-only subagent.

xterm.js terminal emulator development - building, configuring, and integrating xterm.js in web and Electron apps with addon support and PTY wiring

Author and maintain X-Ways Forensics X-Tensions — scaffold from templates, wrap CLI tools, port conventions, and audit for API correctness, backed by a distilled X-Tension API knowledge base.

from yaccp/claude-plugin-aws-docusaurus

Hebrew landing-page workflow + copy/design/SEO/CRO skills and slash commands

Validate, add, or update YAML frontmatter on documentation files

YANG's personal toolkit: daily-ops skills + 4-tier observability layer + nested CLAUDE.md gap detection. Bring your own agents.

Session checkpoint (/save) and resume (/resume) skills, plus brainstorm-to-execution pipeline

吆喝 — 让 Agent 自动全网宣传你的开源项目。Rule-abiding, per-channel tailored promotion across 20 CN & EN channels

AskUserQuestion 運用 hook 群（セッション単位無効化 #aq-off/#aq-on と発火時のデスクトップ通知）。