'toolkit' 검색 결과

Test local web applications with Playwright, a browser automation tool. Write Python scripts to check interface behavior, inspect rendered pages, capture screenshots, and collect browser logs, with a helper that manages one or more application servers.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Checking buttons, links, and form behavior
• Investigating interface issues with screenshots and logs
• Automating checks for local static HTML

Connect .NET MAUI screens to application data using XAML or C#. Covers compile-time binding checks, change notifications, value conversion, and fallback displays to help implement bindings and investigate screens that fail to update.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Fix screens that do not reflect data changes
• Add compile-time checks to XAML bindings
• Convert and format values for display

Give slides, documents, reports, and HTML landing pages consistent colors and fonts. Choose from ten preset themes using a visual showcase, or create a custom theme from a description and review it before application.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Making colors and fonts consistent across slides
• Choosing a theme for documents or reports
• Styling an HTML landing page

Test local web applications with Python scripts using Playwright, a browser automation tool. Verify interface behavior, investigate problems, capture screenshots, and inspect browser logs, with a helper that manages one or more application servers.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Verify buttons, links, and form behavior
• Investigate problems in dynamic web interfaces
• Capture screenshots of local applications

Work with crystal structures in Python: convert files, analyze symmetry, assess material stability, and examine electronic properties. Retrieve Materials Project data and prepare input files for materials calculations, with scripts for common analysis tasks.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Convert crystal structure files between CIF and POSCAR
• Analyze crystal symmetry and neighboring atoms
• Build phase diagrams and assess material stability

Analyze relationships between people, objects, or papers as networks in Python. Use NetworkX to find shortest paths, identify important nodes and communities, visualize connections, exchange graph data, and generate sample networks for testing.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Visualizing social relationships or paper citation networks
• Finding shortest paths through a network
• Identifying important nodes and closely connected groups

Save decisions, research findings, and work updates to Obsidian, then update related notes, daily entries, and task boards. Maintain existing pages, preserve changing facts with their history, and check for duplicates and broken links.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Save decisions and tasks from a conversation
• Connect development logs to project notes
• Check a vault for duplicates and broken links

Test local web applications with Playwright, a browser automation tool. Write Python scripts to check interface behavior, inspect rendered pages, capture screenshots, and collect browser logs, with a helper that manages one or more application servers.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Checking buttons, links, and form behavior
• Investigating interface issues with screenshots and logs
• Automating checks for local static HTML

Evaluate scientific manuscripts and grant proposals for sound methods, statistics, reproducibility, ethics, and clear reporting. Produce a structured review that separates major concerns from minor issues and gives authors specific, constructive suggestions for revision.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Preparing a structured review of a scientific manuscript
• Evaluating methods and statistics in a grant proposal
• Checking reproducibility and reporting guidelines

Set up and audit multilingual application interfaces. Replace hard-coded text with translation keys, localize error messages, and check for missing translations, matching keys across languages, plural forms, and date or number formatting.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Adding multilingual support to an application
• Finding missing translations across languages
• Localizing error messages and accessibility labels

Breaks a long-running goal into small, tracked actions and records observable evidence for each success criterion. Checkpoints preserve progress so the agent can resume after interruptions and verify completion against the current work.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Resuming long-running work after an interruption
• Tracking evidence for each success criterion
• Breaking a large goal into small actions

Handle encoded strings and cryptographic data with tool-based conversions. Decode layered formats, calculate hashes, encrypt or decrypt with AES and RSA, and inspect JWT tokens, which carry encoded headers and data used in authentication.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Decoding strings with multiple layers of encoding
• Calculating hashes and checking likely hash formats
• Encrypting or decrypting data with a known key

Create, edit, and inspect Word documents, including text extraction, formatting, comments, and tracked changes. Its review workflow marks only the text that changes, helping reviewers identify revisions while preserving unchanged content and formatting.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Creating a new Word document
• Reviewing documents with tracked changes
• Extracting text and revisions for inspection

Process PDF documents with Python libraries and command-line tools to extract text and tables, merge or split files, fill forms, and create documents. Examples also cover scanned text recognition and exporting tables to Excel.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Extracting PDF tables into Excel
• Merging documents or splitting selected pages
• Recognizing text in scanned PDFs

Create and edit Excel workbooks, analyze spreadsheet data, and visualize results. Preserve existing formatting, use formulas that update when inputs change, and recalculate workbooks to identify formula errors before delivering the finished files.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Creating sales summaries with formulas
• Updating existing Excel templates
• Analyzing and visualizing Excel or CSV data

Create, edit, and inspect PowerPoint presentations, including slide content, layouts, speaker notes, and comments. Reuse existing templates, rearrange slides, and review thumbnail previews to check text placement, overlap, and readability.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Creating a new PowerPoint presentation
• Building slides from an existing template
• Replacing text and rearranging slides

Build PyTorch machine learning workflows for molecules, proteins, and biomedical relationships. Get guidance on datasets, model selection, training, and evaluation for property prediction, protein modeling, molecule generation, and planning synthesis routes from target molecules.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Predicting molecular solubility and toxicity
• Predicting protein function from sequences or structures
• Exploring new drug uses through biomedical relationships

Guides statistical analysis in Python, including regression, time series forecasting, and hypothesis tests. Helps interpret estimates and uncertainty, check model assumptions, investigate influential observations, compare models, and produce statistical tables for reporting.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Interpreting regression coefficients and confidence intervals
• Forecasting time series with prediction intervals
• Checking model assumptions and influential observations

Use TensorBoard to visualize training loss and accuracy, compare experiments, and inspect model structure. Guides logging for PyTorch and TensorFlow, including weight distributions and performance profiling to investigate training problems and processing bottlenecks.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Monitoring training loss and accuracy
• Comparing experiments with different training settings
• Inspecting weight and gradient distributions

Analyze research data with suitable statistical tests, regression, correlation, or Bayesian methods. Check assumptions, estimate effect sizes and uncertainty, plan sample sizes, and prepare figures, tables, and reports following APA academic reporting conventions.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Choosing statistical tests for research data
• Checking analysis assumptions and alternative methods
• Estimating sample sizes before collecting data

Give slides, documents, reports, and HTML landing pages consistent colors and fonts. Choose from ten preset themes using a visual showcase, or create a custom theme from a description and review it before application.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Making colors and fonts consistent across slides
• Choosing a theme for documents or reports
• Styling an HTML landing page

Analyze biological data in Python, from DNA, RNA, and protein sequences to evolutionary trees and microbial communities. Read and convert files, compare diversity within and between samples, and test differences between groups.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Processing DNA, RNA, and protein sequences
• Building and comparing evolutionary trees
• Comparing microbial community diversity

Use RDKit in Python to read molecular structures, calculate properties such as molecular weight, find similar compounds or specific structural features, and generate molecular drawings and 3D coordinates for chemistry research.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Calculating properties for a list of molecules
• Finding compounds similar to a reference molecule
• Filtering molecules by a specific structural feature

Analyze how long events take to occur, including records where observation ends before the event. Use Python to prepare data, fit and compare survival models, and evaluate predictions with measures suited to incomplete observations.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Analyze time to events with incomplete observations
• Compare Cox models and Random Survival Forests
• Select features in datasets with many variables