OpenBMB

Use PilotDeck's browser-use plugin for browser automation, screenshots, form filling, and web UI checks.

Run safe PowerShell commands on Windows, translate Bash snippets, and troubleshoot native Windows setup.

Intelligent meeting recording and transcription assistant with automated minutes generation, action item extraction, and sentiment analysis. Supports audio transcription, speaker diarization, meeting summarization, and task extraction. Use when users need to record meetings, transcribe audio, generate meeting minutes, extract action items, or analyze meeting content.

Set up and use 1Password CLI for sign-in, desktop integration, and reading or injecting secrets.

Create, view, edit, delete, search, move, or export Apple Notes via the memo CLI on macOS.

List, add, edit, complete, or delete Apple Reminders and reminder lists via remindctl.

Create, search, and manage Bear notes via grizzly CLI.

Monitor blogs and RSS/Atom feeds for updates using the blogwatcher CLI.

Run MiniCPM5-1B with llama.cpp using the released GGUF artifacts (F16 / Q8_0 / Q4_K_M). Use when the user wants CPU-only / consumer-GPU / cross-platform native deployment, asks for "llama.cpp", "llama-cli", "llama-server", "GGUF", or has no Python available.

Fine-tune MiniCPM5-1B into a LoRA adapter and convert it to a GGUF adapter that loads directly into llama.cpp / llama-server and the MiniCPM Desk Pet app's custom-LoRA upload. Use when the user wants "GGUF LoRA", "convert LoRA to GGUF", "convert_lora_to_gguf", a custom persona/skin for the desktop pet, "桌宠自定义 LoRA", "上传 LoRA 到桌宠", or asks how to take a trained adapter and run it on a GGUF base.

Pick the right fine-tuning framework for a MiniCPM5-1B base checkpoint and route to a framework-specific cookbook skill. Use when the user wants to SFT / LoRA / DPO / continue-pretrain MiniCPM5 and has not yet committed to a specific framework, or when they say "fine-tune MiniCPM5", "train MiniCPM5", "MiniCPM5 微调", "LoRA MiniCPM5", "继续训练 MiniCPM5".

Run MiniCPM5-1B in LM Studio (desktop GUI) using either the GGUF runtime (cross-platform) or the MLX runtime (Apple Silicon, faster). Includes OpenAI-compatible local server. Use when the user mentions "LM Studio", desktop GUI inference, "lms" CLI, or wants a no-code chat UI for MiniCPM5.

Run MiniCPM5-1B natively on Apple Silicon with Apple's MLX framework. Use when the user has an Apple Silicon Mac and asks for "MLX", "mlx_lm", "mlx_lm.convert", "mlx_lm.generate", or wants the fastest path on Apple Silicon.

Serve MiniCPM5-1B via SGLang as an OpenAI-compatible HTTP server with RadixAttention prefix cache and built-in MiniCPM5 tool-call parsing. Use when the user asks for "SGLang", "RadixAttention", "prefix cache", batch evaluation, tool calling, or wants a high-concurrency NVIDIA-GPU server alternative to vLLM.

Serve MiniCPM5-1B via vLLM as an OpenAI-compatible HTTP server. Use when the user wants high-throughput production serving on NVIDIA GPU, asks for "vLLM", "OpenAI server", "REST API for MiniCPM5", or "production deployment".

Run MiniCPM5-1B via Ollama on macOS / Linux laptop using the released GGUF. Use when the user wants "ollama run", "ollama pull", a Modelfile-driven setup, or one-line laptop deployment.

Orchestrate ClawXMemory retrieval using memory_search first and memory_get for exact file reads. Use when the user asks for historical context, project progress, project collaboration rules, or user profile facts.

Audit ClawXMemory memory quality with a read-only Dream pass over current file memories and the global profile.

Browse ClawXMemory status and recent indexes using memory_overview first, then memory_list, and memory_get only for exact detail reads.

Diagnose and maintain ClawXMemory index health using scripts and tools. Use when installation, indexing, or data quality looks wrong.

Greet the user in a distinctive, easy-to-verify format for skill activation demos.

Use the existing Python execution tools as a scratchpad for calculations, data transformation, and quick script-based validation.

Call REST APIs from Python, parse JSON responses, and report the useful fields back to the user.

帮用户给 MiniCPM-Desk-Pet 桌宠做一个自定义人格 / 皮肤：微调一个 LoRA、转成 GGUF、 在 App 里上传并切换。覆盖"训练 → 转 GGUF → 上传 → 启用"的完整链路。 Use when the user wants a custom desktop-pet persona, asks "做一个自己的桌宠人格 / 角色", "训练 / 上传自定义 LoRA", "把我的 LoRA 用到桌宠上", "convert LoRA to GGUF for the pet", or hits errors uploading a .gguf adapter in Settings.

一键部署 MiniCPM 桌宠体验环境，后端采用 OpenVINO 推理引擎（Deploy MiniCPM Desk Pet with OpenVINO backend）. 使用本 Skill 可部署一个完整的桌宠体验环境，在 Intel AIPC 上本地运行，无需云端服务。 部署完成后，用户直接通过桌宠 UI 界面进行对话交互。 Use this skill when the user wants to deploy/set up/run the MiniCPM desk pet with OpenVINO backend, or build a local AI pet experience environment on Intel hardware. Trigger on: 部署桌宠/体验环境/搭建环境/本地推理/OpenVINO后端/桌宠环境/deploy pet/setup environment/run desk pet/ 英特尔/intel/AIPC/本地/离线/offline/MiniCPM/OpenVINO/桌宠. This is a DEPLOYMENT skill — it sets up the environment and launches the pet. After deployment, the user interacts with the pet directly through its UI (not via this script).

[开发者向] 帮 contributor / 开发者从源码 dev 模式跑通 MiniCPM-Desk-Pet。 普通用户应直接下载 dmg 安装包，跟着 Onboarding 引导走，不应触发本 skill。 Use when a developer clones the repo and wants to run it from source, or asks to "部署桌宠 (从源码)", "跑起来 MiniCPM dev 模式", or hits errors during go.sh / npm start / uv sync.