20 件 ・ 関連度順
概要と使いどころ
飞书项目（Meego/Meegle）操作工具。支持查询和管理工作项、节点流转、视图查询、个人待办、排期统计等功能。 Use when user needs to work with Feishu/Lark Meego project management — including querying work items, creating/updating work items, completing workflow nodes, checking views, listing todos, analyzing schedules/workloads, or searching with MQL. 关键词：飞书项目、meego、meegle、工作项、需求、任务、缺陷、排期、视图、待办、节点。
日本語の概要は準備中です。原文の説明を表示しています。
Use when the user asks to "generate daily paper", "search arXiv for EEG papers", "find EEG decoding papers", "review brain-computer interface papers", or wants to create paper summaries for EEG/brain decoding/speech decoding research. This skill automates searching arXiv for recent papers on EEG decoding, EEG speech decoding, or brain foundation models, reviewing paper quality, and generating structured Chinese/English summaries.
日本語の概要は準備中です。原文の説明を表示しています。
Organizes, queries, validates, and converts Brain Imaging Data Structure (BIDS) datasets. Supports organizing neuroscience and biomedical data (MRI, EEG, MEG, iEEG, PET, microscopy, NIRS, motion capture, EMG, MR spectroscopy, behavioral), querying BIDS layouts, validating compliance, converting DICOM to BIDS, writing metadata sidecars, or creating BIDS derivatives.
日本語の概要は準備中です。原文の説明を表示しています。
Python toolkit for neurophysiological signal processing: ECG (HR, HRV, R-peaks), EEG (complexity, PSD), EMG (activation onset), EDA/GSR (SCR decomposition), PPG, and RSP. Includes synthetic signal simulation. Alternatives: BioSPPy (less maintained), MNE (EEG/MEG specialist), heartpy (ECG only), scipy.signal (raw DSP).
日本語の概要は準備中です。原文の説明を表示しています。
EEG preprocessing and analysis — filtering, artifact removal, time-frequency decomposition, and ERP workflows.
日本語の概要は準備中です。原文の説明を表示しています。
Use this skill when working with Brain Imaging Data Structure (BIDS) datasets: organizing neuroscience and biomedical data (MRI, EEG, MEG, iEEG, PET, microscopy, NIRS, motion capture, EMG, MR spectroscopy, behavioral), querying BIDS layouts, validating compliance, converting DICOM to BIDS, writing metadata sidecars, or creating BIDS derivatives.
日本語の概要は準備中です。原文の説明を表示しています。
脳波などを測る機器とNeuroSkillをつなぎ、集中・気分・眠気の指標を確認するスキル。過去の記録との比較や睡眠の振り返り、休憩の提案にも使えます。
Use when applies to custom ARIA widgets using composite roles: tablist, list, listbox, menu, menubar, tree, treegrid, grid, rowgroup, row, radiogroup. Use when reviewing components built with div/span elements that replace native HTML list, select, or nav elements.
日本語の概要は準備中です。原文の説明を表示しています。
Comprehensive biosignal processing toolkit for analyzing physiological data including ECG, EEG, EDA, RSP, PPG, EMG, and EOG signals. Use this skill when processing cardiovascular signals, brain activity, electrodermal responses, respiratory patterns, muscle activity, or eye movements. Applicable for heart rate variability analysis, event-related potentials, complexity measures, autonomic nervous system assessment, psychophysiology research, and multi-modal physiological signal integration.
日本語の概要は準備中です。原文の説明を表示しています。
Comprehensive healthcare AI toolkit for developing, testing, and deploying machine learning models with clinical data. This skill should be used when working with electronic health records (EHR), clinical prediction tasks (mortality, readmission, drug recommendation), medical coding systems (ICD, NDC, ATC), physiological signals (EEG, ECG), healthcare datasets (MIMIC-III/IV, eICU, OMOP), or implementing deep learning models for healthcare applications (RETAIN, SafeDrug, Transformer, GNN).
日本語の概要は準備中です。原文の説明を表示しています。
Neurophysiological signal processing for ECG, EEG, EMG, and more
日本語の概要は準備中です。原文の説明を表示しています。
Comprehensive biosignal processing toolkit for analyzing physiological data including ECG, EEG, EDA, RSP, PPG, EMG, and EOG signals. Use this skill when processing cardiovascular signals, brain activity, electrodermal responses, respiratory patterns, muscle activity, or eye movements. Applicable for heart rate variability analysis, event-related potentials, complexity measures, autonomic nervous system assessment, psychophysiology research, and multi-modal physiological signal integration.
日本語の概要は準備中です。原文の説明を表示しています。
Backend-neutral image generation: create new raster images and looping GIF/WebP animations through the local one-file image-use CLI (formerly chatgpt-imagegen), using the user's ChatGPT subscription by default, the Codex backend as fallback, or an optional Gemini subscription — no API key or daemon. Triggers: image generation, generate an image, draw a picture, 画图, 画一张, 生成图片, 生图, 配图. Use for photos, illustrations, icons, hero banners, mockups, sprites, concept art, animation loops, and figures for documents, proposals, blog posts, or READMEs; save outputs in the workspace. Auto mode uses the logged-in ChatGPT browser via chrome-use. Gemini users can pass --backend gemini or agy. Proactively propose useful figures while authoring long-form content. Do not use for editing existing images, SVG/vector work, code-native graphics, established icon systems, explicit high-quality or transparent API output, or end-user image-generation services.
日本語の概要は準備中です。原文の説明を表示しています。
Routes EEG, ECoG, MEG, and related electrophysiology deep-learning workflows through the braindecode Python package, including dataset construction, preprocessing, model training, augmentation, and interpretation.
日本語の概要は準備中です。原文の説明を表示しています。
Think and work like an expert Cognitive Neuroscientist. Use when a task calls for Cognitive Neuroscientist judgment. Reasons from latent constructs through converging behavior, fMRI/M/EEG, TMS, and lesion evidence; designs factorial and dissociation contrasts, fMRIPrep/GLMsingle/MNE pipelines, MVPA/RSA, and COBIDAS reporting while treating pure insertion, reverse inference, motion confounds, and in-sample decoding as first-class failure modes.
日本語の概要は準備中です。原文の説明を表示しています。
Think and work like an expert Brain–Computer Interface Engineer. Use when a task calls for Brain–Computer Interface Engineer judgment. Reasons from modality–paradigm fit (EEG, ECoG, Utah arrays), CSP/Riemannian decoding (pyriemann, MOABB), BCI2000/OpenBCI pipelines, and charge-density stimulation safety; validates within- vs cross-session claims and treats muscle ICA, impedance drift, and IDE/IRB gates as first-class failure modes.
日本語の概要は準備中です。原文の説明を表示しています。
Evaluates neuromarketing studies and neural-data law. Use when judging EEG, fMRI, eye-tracking, or GSR ad study or vendor, or if signals are regulated neural data.
日本語の概要は準備中です。原文の説明を表示しています。
Reverse engineer CGX Cognionics Quick-20 EEG acquisition protocol using MCP RE tooling (Binary Ninja, Ghidra, radare2)
日本語の概要は準備中です。原文の説明を表示しています。
Brain-Computer Interface with colored operad security boundaries. Maximally isolated EEG/neural data processing via VM→Container→Process enclosure with GF(3) conservation for Agent-O-Rama neural pathways.
日本語の概要は準備中です。原文の説明を表示しています。
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日本語の概要は準備中です。原文の説明を表示しています。