1,120 件 ・ 関連度順
概要と使いどころ
Creates and audits truthful, accessible, publication-ready scientific figures with Matplotlib, Seaborn, or Plotly. Use it for figure design, multi-panel layouts, uncertainty and missing-data displays, color/contrast review, image metadata validation, and journal export planning.
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。
Reads, inspects, writes, transforms, and preflights local DICOM datasets and pixel data. Applies to DICOM metadata, transfer syntaxes, compression plugins, frames, private elements, JSON, and bounded de-identification review.
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。
Searches and reads biomedical papers, FDA/PMDA/EMA documents, clinical trials, and protein records with the GXL Paperclip CLI and Python SDK. Supports source-scoped search, full-text grep, metadata SQL, map/reduce extraction, figure analysis, optional repositories and claim verification, and line-pinned citations. Use when a task names GXL paperclip, asks to install or authenticate it, or requests literature retrieval and evidence extraction through Paperclip.
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。
Processes, cleans, compares, and searches tandem mass spectra with matchms. Use for MS/MS file I/O, metadata harmonization, peak filtering, spectral similarity, library matching, score matrices, and molecular-similarity networks. Use pyopenms instead for LC-MS feature detection or proteomics pipelines.
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。
Inspects and automates microscopy data workflows against OMERO.server with omero-py, BlitzGateway, OMERO CLI, tables, annotations, ROIs, rendering, and documented OMERO.web APIs. Use this skill for scoped OMERO inventory, metadata export, import/export planning, or reviewed write 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。
Converts neuroscience acquisition data to Neurodata Without Borders files with NeuroConv and PyNWB, preserves metadata and timebases, checks evidence-based clock alignment, and produces schema validation, NWB Inspector findings and round-trip checks. Use for NWB conversion and synchronization of planar single-channel two-photon TIFF imaging plus timestamped behavioral position CSV; this skill does not perform spike sorting or claim tested support for arbitrary acquisition formats.
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。
Performs bounded, local exploratory analysis of explicitly supported scientific files. Supports redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain formats are reference-only and unknown formats fail closed.
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。
Analyzes flow cytometry data with FlowKit, including spillover compensation, logicle and biexponential transforms, hierarchical gating, GatingML strategies, and supported FlowJo 10 workspaces. Use for reproducible gate counts, population percentages, gated fluorescence summaries, or reproducing a FlowJo analysis in Python. For FCS metadata inspection or file-format repair alone, use FlowIO.
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。
Reads, inspects, and writes Flow Cytometry Standard (FCS) 2.0, 3.0, and 3.1 files with FlowIO. Use for low-level FCS metadata and channel inspection, NumPy event extraction, multi-dataset files, table export, and FCS 3.1 creation; use FlowKit for compensation, cytometry transforms, gating, or FlowJo workspaces.
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 citation management for academic research. Search OpenAlex, PubMed, and Google Scholar for papers, extract accurate metadata, validate citations, and generate properly formatted BibTeX entries. This skill should be used when you need to find papers, verify citation information, convert DOIs to BibTeX, or ensure reference accuracy in scientific writing.
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。
Queries the CZ CELLxGENE Census programmatically for versioned public single-cell and spatial transcriptomics data. Use when you need population-scale cell metadata, gene expression slices, Census summary counts, source H5AD URIs/downloads, embeddings, spatial Census data, or reference atlas comparisons across organisms, tissues, diseases, assays, and cell types. For analyzing your own local single-cell data use scanpy, anndata, or scvi-tools.
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。
Draft or audit manuscript Data/Code Availability statements, dataset access routes, repository plans, and FAIR metadata. Use for 数据可用性声明、数据共享、数据仓库选择 and dataset citations; not general data cleaning or statistical analysis.
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。
Provide comprehensive techniques for penetration testing AWS cloud environments. Covers IAM enumeration, privilege escalation, SSRF to metadata endpoint, S3 bucket exploitation, Lambda code extraction, and persistence techniques for red team operations.
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。
Query Ondo tokenized US stock data on Binance Web3. Covers: supported stock token list, RWA metadata (company info, attestation reports), market and per-asset trading status (with corporate action codes for earnings, dividends, splits), real-time on-chain data (token price, holders, circulating supply, market cap), US stock fundamentals (P/E, dividend yield, 52-week range), and token K-Line/candlestick charts. Use this skill when users ask about: - Tokenized stock price, holders, or on-chain data for specific tickers - Whether a stock token is tradable, paused, or halted - Ondo RWA token list or which US stocks are available on-chain - Corporate actions affecting a token (dividends, stock splits, earnings halt) - Stock token K-Line or candlestick chart data - Comparing on-chain token price vs US stock price NOT for general crypto tokens (BTC, ETH, SOL, etc.) — use query-token-info for those.
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。
Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for ZIP and PKZIP archive challenges, legacy ZipCrypto identification, known-plaintext recovery with bkcrack, key-based decryption, and reproducible extraction. Use when the user asks to solve an encrypted ZIP challenge, inspect ZipCrypto metadata, recover keys from a known file prefix, or unlock an archive without starting with password brute force. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
日本語の概要は準備中です。原文の説明を表示しています。
Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for image, audio, video, document, and container steganography. Use when the user asks to inspect metadata, alpha or palette channels, LSBs, thumbnails, appended trailers, QR fragments, transcoding artifacts, or recover a hidden payload from media without blind brute force. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
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 for authorized cloud, container, and Kubernetes security assessment including metadata SSRF, IAM misconfig, container escape paths, and cluster RBAC review.
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。
Implement NFT standards (ERC-721, ERC-1155) with proper metadata handling, minting strategies, and marketplace integration. Use when creating NFT contracts, building NFT marketplaces, or implementing digital asset systems.
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。
Skill for using the command-line tool pdftk (PDFtk Server) for working with PDF files. Use when asked to merge PDFs, split PDFs, rotate pages, encrypt or decrypt PDFs, fill PDF forms, apply watermarks, stamp overlays, extract metadata, burst documents into pages, repair corrupted PDFs, attach or extract files, or perform any PDF manipulation from the command line.
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。
Process and manipulate images using ImageMagick. Supports resizing, format conversion, batch processing, and retrieving image metadata. Use when working with images, creating thumbnails, resizing wallpapers, or performing batch image operations.
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。
Generate concise, actionable meeting minutes for internal meetings. Includes metadata, attendees, agenda, decisions, action items (owner + due date), and follow-up steps.
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Govern Power Automate flows and Power Apps at scale using the FlowStudio MCP cached store. Classify flows by business impact, detect orphaned resources, audit connector usage, enforce compliance standards, manage notification rules, and compute governance scores — all without Dataverse or the CoE Starter Kit. Load this skill when asked to: tag or classify flows, set business impact, assign ownership, detect orphans, audit connectors, check compliance, compute archive scores, manage notification rules, run a governance review, generate a compliance report, offboard a maker, or any task that involves writing governance metadata to flows. Requires a FlowStudio for Teams or MCP Pro+ subscription — see https://mcp.flowstudio.app
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。
Apply the SGLang kernels RFC when adding, moving, splitting, or reviewing kernel APIs, registry metadata, kernel tests, benchmarks, and model-specific implementations. Use with add-jit-kernel, add-sgl-kernel, and write-sglang-test for placement and migration checks.
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。