'collections' 검색 결과

Process 3D scan data with CloudCompare through text commands. Clean point clouds, collections of measured 3D points, extract ground surfaces, align scans, calculate distances, and convert or export point clouds and surface meshes in supported formats.

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• Remove noise and reduce point counts in LiDAR scans
• Extract ground points from buildings and vegetation
• Align two scans and calculate distances between them

Design how an AI agent finds and loads tools as needed. Compare discovery approaches, organize large tool collections, and assess tool selection accuracy, token costs, and cache reuse without placing every tool definition in the initial context.

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• Designing on-demand loading for many MCP tools
• Comparing tool discovery approaches
• Investigating cache misses after loading tools

Helps organize biological datasets and models in LaminDB. Covers data registration, table validation, annotation with standardized biological terms, metadata searches, and tracking analysis inputs and outputs so researchers can preserve the context needed to repeat their work.

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• Register and organize biological datasets
• Validate DataFrame or AnnData metadata
• Standardize annotations with biological vocabularies

Use Dask to process tables, numerical arrays, and file collections in pieces across CPU cores or machines. Helps choose data structures, size memory-friendly chunks, coordinate dependent tasks, and diagnose slow or memory-heavy workflows.

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• Aggregate CSV or Parquet files that exceed available memory
• Process large scientific arrays in chunks
• Clean JSON records and logs before analysis

Query public single-cell and spatial gene expression data by tissue, disease, or cell type. Retrieve selected expression values, cell metadata, and summary counts for analysis and comparisons across datasets without first downloading entire collections.

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• Explore cell types within a tissue
• Retrieve expression values for selected marker genes
• Compare cells across tissues and datasets

Create output schemas, definitions of result fields and display settings, for an Apify Actor by inspecting its source code. Generate dataset and output files, add key-value storage definitions when needed, and update actor.json to reference them.

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• Creating output schemas for a new Actor
• Updating schemas after output fields change
• Configuring result table columns in Apify Console

Turn API code into documentation covering available operations, inputs, outputs, authentication, and errors. Add practical request examples and usage guides, with OpenAPI specifications or Postman collections where possible to help developers explore and use the API.

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• Document a new API from its code
• Update documentation after API changes
• Prepare API guides for new developers or external users

Set up and manage DeepTutor from the command line, a text interface for running commands. Run learning tasks, build searchable document collections, manage sessions and notebooks, diagnose installation issues, and launch the server or Web app.

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• Set up DeepTutor and diagnose installation issues
• Build and search a knowledge base from PDFs
• Generate practice questions from learning materials

Design and improve Unity games that process large numbers of entities. Learn ECS, an approach that separates data from behavior, and apply Jobs and Burst patterns to organize parallel processing and address CPU performance bottlenecks.

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• Designing Unity games with thousands of entities
• Converting object-oriented game logic to ECS
• Addressing CPU performance bottlenecks

Manage resources in OpenViking through its command-line tool. The skill guides adding and searching materials, editing and organizing files, scheduling refreshes, and transferring or backing up resource collections with the appropriate commands and options.

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• Adding local files or URLs to OpenViking
• Searching and organizing stored resources
• Setting up scheduled resource refreshes

Update Pester test assertions, checks of expected results, from classic v5 syntax to v6 Should-* commands. Identify behavior changes involving booleans, empty values, and collections, then verify the suite and report conversions needing human judgment.

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• Convert assertions in PowerShell test files
• Adopt Should-* syntax one file at a time
• Review boolean, empty-value, and collection checks

Find and load Copilot Spaces, shared collections of project documents, code, and instructions, to answer team-specific questions or follow reporting workflows. Also create and update spaces, attached resources, and collaborator settings through the GitHub CLI.

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• Find spaces available to a team
• Answer questions using project documentation
• Draft weekly updates from a space's workflow

Build Splunk pipelines that import threat intelligence and match security events against indicators such as malicious IP addresses, domains, and file hashes. Add source, confidence, and severity details so analysts have context when investigating matches.

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• Importing external threat feeds into Splunk
• Matching network and endpoint logs against threat indicators
• Adding threat and asset context to alerts

Assess REST, GraphQL, and gRPC APIs for authentication, access control, input validation, and business logic weaknesses. Use OWASP API Security Top 10, a framework of common API risks, to organize testing and document findings with reproduction steps and remediation.

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• Comparing API access across user roles
• Checking token handling and request rate limits
• Assessing GraphQL access control and data exposure

Turn API code into documentation covering endpoints, inputs, authentication, responses, and errors. Add request examples in multiple languages and usage guides to help developers understand and start using the API.

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• Writing documentation for a new API
• Updating API documentation after code changes
• Preparing API guides for new developers or external users

Prepare text for language models using HuggingFace Tokenizers, which splits text into model-readable units. Train custom vocabularies, process batches, track original text positions, and configure input lengths for use with transformers.

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• Preparing large text collections for language models
• Training a tokenizer on domain-specific text
• Mapping model outputs back to original text

Build similarity search with FAISS to find nearby matches in large collections of numeric vectors. The skill guides index selection, memory reduction, GPU use, and saving indexes while balancing search speed and accuracy.

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• Find similar items in large vector datasets
• Choose an index for search speed and accuracy
• Reduce memory use for vector search

Run Gemini CLI to review code, assess technical plans, and analyze large collections of files. Choose a model and execution settings for the task, then capture findings about security, maintainability, architecture, or technical debt.

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• Reviewing security and quality across multiple files
• Checking architecture plans for missing components
• Analyzing the structure of a large codebase

Build image classification and search workflows by comparing images with text descriptions. Covers classification without additional training, similarity scoring, batch processing, and storing image representations in a vector database for retrieval.

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• Classifying images without additional training
• Searching image collections with text descriptions
• Comparing images with candidate descriptions

Prepare training datasets for large language models with GPU-assisted cleaning. Covers duplicate removal, quality filtering, and personal information redaction, with workflows for text, images, video, and audio using NeMo Curator.

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• Clean web data for model training
• Remove exact and near duplicates from large text collections
• Redact personal information from training text

Retrieve locally stored Chinese A-share prices, financial statements, and valuation context through the project's shared interfaces. Look up technical indicators, inspect available data fields, and check data dates when results disagree.

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• Checking a stock's prices and valuation context
• Retrieving financial data across reporting periods
• Looking up technical indicators and their data dates

Develop varied ideas for names, writing angles, and problem solving by exploring five candidates internally and presenting the strongest. It also expands small example collections into diverse datasets for evaluation, training, or testing.

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• Finding a distinctive product name
• Developing a fresh angle for a blog post
• Exploring solutions to a technical problem

Find related papers across local PDFs, research notes, and web sources, then summarize their key contributions and relevance. Use existing collections as a starting point, remove duplicates, and search for literature that fills gaps.

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• Find related work for a research topic
• Summarize relevant papers already stored locally
• Combine Zotero highlights with Obsidian research notes

Write and review animation code using gsap.utils helpers. Convert scroll positions into animation values, constrain ranges, generate random values, snap positions to a grid, and handle element collections with reusable functions.

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• Mapping scroll position to movement or rotation
• Snapping animated positions to a grid
• Randomizing element positions and colors