323건 · 관련도순
Process multi-sheet Excel data by finding columns through keywords and counting specified values. Clean text fields to retain Chinese characters, then export the processed data as an Excel file with its size and download link.
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Organize Excel analysis from reading multiple sheets through cleaning, filtering, aggregation, and export. Choose processing methods based on row counts, and use supporting skills to produce tables, charts, and Excel or CSV reports.
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Inspect JSON files or API responses with jq and produce a compact map of keys and value types. Use the result to understand nested data before writing queries or processing the full dataset.
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Investigate XXE, an XML parsing flaw, in APIs and document uploads. The skill guides entry point discovery, external callback checks, and evidence collection to establish whether files or internal services are actually exposed.
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Forecast sales, sensor readings, or other time series without training a custom model. Using Google's TimesFM, this skill produces forecasts and uncertainty ranges from CSV files or arrays, supports batch processing, and checks local computing resources before use.
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Python interface to OpenMS for mass spectrometry data analysis. Use for LC-MS/MS proteomics and metabolomics workflows including file handling (mzML, mzXML, mzTab, FASTA, pepXML, protXML, mzIdentML), signal processing, feature detection, peptide identification, and quantitative analysis. Apply when working with mass spectrometry data, analyzing proteomics experiments, or processing metabolomics datasets.
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Python library for working with DICOM (Digital Imaging and Communications in Medicine) files. Use this skill when reading, writing, or modifying medical imaging data in DICOM format, extracting pixel data from medical images (CT, MRI, X-ray, ultrasound), anonymizing DICOM files, working with DICOM metadata and tags, converting DICOM images to other formats, handling compressed DICOM data, or processing medical imaging datasets. Applies to tasks involving medical image analysis, PACS systems, radiology workflows, and healthcare imaging applications.
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Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or astronomical data processing.
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Amplicon sequence variant (ASV) inference from 16S rRNA or ITS amplicon sequencing using DADA2. Covers quality filtering, error learning, denoising, and chimera removal. Use when processing demultiplexed amplicon FASTQ files to generate an ASV table for downstream analysis.
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Debug and profile Three.js browser games: blank canvases, render and runtime bugs, asset and audio loading, animation, resize, mobile input, plus performance profiling of draw calls, triangles, textures, memory, shader and post-processing cost, and bundle size.
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Insecure file upload playbook. Use when testing upload validation, storage paths, processing pipelines, preview behavior, overwrite risks, and upload-to-RCE chains.
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Process and generate multimedia content using Google Gemini API. Capabilities include analyze audio files (transcription with timestamps, summarization, speech understanding, music/sound analysis up to 9.5 hours), understand images (captioning, object detection, OCR, visual Q&A, segmentation), process videos (scene detection, Q&A, temporal analysis, YouTube URLs, up to 6 hours), extract from documents (PDF tables, forms, charts, diagrams, multi-page), generate images (text-to-image, editing, composition, refinement). Use when working with audio/video files, analyzing images or screenshots, processing PDF documents, extracting structured data from media, creating images from text prompts, or implementing multimodal AI features. Supports multiple models (Gemini 2.5/2.0) with context windows up to 2M tokens.
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Parse Flow Cytometry Standard (FCS) files v2.0–3.1 and extract events/metadata for preprocessing workflows (e.g., when you need NumPy arrays, channel info, or CSV/DataFrame export from cytometry files).
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ALWAYS use this skill instead of the Read tool for PDF files. The Read tool cannot extract PDF tables properly. Use this skill when: (1) Reading ANY PDF file, (2) Extracting tables from PDFs, (3) Converting PDF tables to pandas DataFrames, (4) Processing multi-page PDFs
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An overview of the core data API of ObsPy, a Python framework for processing seismological data. It is useful for parsing common seismological file formats, or manipulating custom data into standard objects for downstream use cases such as ObsPy's signal processing routines or SeisBench's modeling API.
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Use this skill when reading sensor data from CSV files, writing simulation results to CSV, processing time-series data with pandas, or handling missing values in datasets.
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Combine visual features (face detection, lip movement analysis) with audio features to improve speaker diarization accuracy in video files. Use OpenCV for face detection and lip movement tracking, then fuse visual cues with audio-based speaker embeddings. Essential when processing video files with multiple visible speakers or when audio-only diarization needs visual validation.
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Extracts Mermaid diagrams from markdown files and generates high-quality PNG images using bundled scripts. Activates when working with Mermaid diagrams, converting diagrams to PNG, extracting diagrams from markdown, or processing markdown files with embedded Mermaid code.
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Building or editing Simulink (.slx) models that stream signals in frames using DSP System Toolbox — audio, vibration, radar, comms. Use when the prompt names a Simulink block (Discrete FIR Filter, Buffer, Unbuffer, Rate Transition, Downsample, Upsample, Sample-Rate Converter, FIR Decimation, Time Scope, Spectrum Analyzer, From Multimedia File) or an action (frame-based processing, InputProcessing, buffering, overlap, windowing, STFT, short-time Fourier, decimate, downsample, upsample, resample, multirate, anti-aliasing, tunable filter). Prevents silent numerical errors from sample-vs-frame mismatch, wrong block choice, or missing anti-aliasing.
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End-to-end finite element analysis in MATLAB PDE Toolbox — geometry creation, model setup, solve, and post-processing in one skill. Use when building geometry from primitives or file import, setting up femodel with BCs/loads/materials, solving thermal/structural/EM problems, and extracting or visualizing results. Covers fegeometry, multicuboid, multicylinder, multisphere, decsg, boolean ops, mesh generation, femodel, all AnalysisTypes (thermalSteady, thermalTransient, structuralStatic, structuralTransient, structuralModal, structuralFrequency, electrostatic, magnetostatic, dcConduction, harmonic EM), materialProperties, faceBC, faceLoad, cellLoad, vertexLoad, solve, interpolation, von Mises stress, principal stress, reaction forces, heat flux, pdeplot3D visualization. Triggers on: PDE Toolbox, finite element, FEA, thermal analysis, structural analysis, electromagnetic analysis, femodel, mesh, boundary conditions, stress, displacement, heat transfer, post-processing.
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Use when automating ZBrush 2026: batch processing a folder of OBJ or ZTL files, a ZBrush Python script or ZScript, recording a macro to learn a palette path, the ZBrush -script command line, scripting UV Master, Decimation Master or Multi Map Exporter, exporting every SubTool, GoZ or GoB round trips with Maya or Blender, renaming SubTools, or batch reports. Also when a plugin press never returns, a dialog stalls a batch, one file kills the whole run, or GoZ updates the wrong SubTool.
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Toolkit for comprehensive document reading, editing, and creation with visual quality control. Use to work with Word documents (.docx files) for: (1) Reading or extracting content from existing DOCX files, (2) Creating new Word documents with professional formatting, (3) Editing documents requiring precise typography and layout, or any other DOCX reading or generation tasks.
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Guide for diagnosing and improving MSBuild project evaluation performance. USE FOR: builds slow before any compilation starts, high evaluation time in binlog analysis, expensive glob patterns walking large directories (node_modules, .git, bin/obj), deep import chains (>20 levels), preprocessed output >10K lines indicating heavy evaluation, property functions with file I/O ($([System.IO.File]::ReadAllText(...))), multiple evaluations per project. Covers the 5 MSBuild evaluation phases, glob optimization via DefaultItemExcludes, import chain analysis with /pp preprocessing. DO NOT USE FOR: compilation-time slowness (use build-perf-diagnostics), incremental build issues (use incremental-build), non-MSBuild build systems.
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Use ManagedCode.MimeTypes when a .NET application needs consistent MIME type detection, extension mapping, and content-type decisions for uploads, downloads, or HTTP responses. USE FOR: integrating ManagedCode.MimeTypes into upload or download flows; mapping file extensions to content types in APIs or background processing; reviewing content-type. DO NOT USE FOR: unrelated stacks; generic tasks that do not need this specific guidance. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.
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