'relationships' 검색 결과

Choose statistical tests for research data, check their assumptions, and interpret effect sizes, which describe the magnitude of differences or relationships. This skill also supports sample size planning and produces results in APA reporting style, with figures and tables.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Choosing a test for group comparisons or relationships
• Checking normality, variance, and outliers before analysis
• Estimating the sample size needed for a study

Create Excalidraw diagram files that explain workflows, architectures, and concepts through visual relationships. Technical diagrams include concrete code or data examples, while a rendering and review process checks readability, connections, spacing, and overall composition.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Visualizing workflow steps and decision points
• Explaining system architecture with code and data examples
• Illustrating abstract concepts and relationships

Turn concepts and relationships into a softly animated radial diagram, with points arranged around a central idea. A frosted card, curved connections, and gentle floating motion suit system explanations and warm product storytelling.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Introducing a system or architecture concept
• Telling a product story with soft visual styling
• Illustrating networks or memory relationships

Helps build a research framework by comparing theories, mapping relationships between variables, and deriving testable hypotheses. Explores less conventional options, examines weaknesses and competing explanations, and produces diagrams with anticipated reviewer objections.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Comparing theories for a research question
• Deriving hypotheses from relationships between variables
• Examining weaknesses and anticipated reviewer objections

Guide economic time series analysis from initial plots to forecasting. Use Python, R, and Stata examples to check whether statistical properties remain stable over time, choose models, diagnose errors, and examine relationships between multiple series.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Checking trends and stationarity in economic data
• Building ARIMA forecasts and evaluating accuracy
• Examining relationships between multiple time series

Run linear or logistic regression on CSV or Excel tables to examine relationships between variables. Get coefficients, measures of model fit, significance tests, and checks for overlapping predictors, with explanations in plain language.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Examining relationships between sales and numeric factors
• Analyzing factors associated with customer churn
• Checking coefficient significance and model fit

Comprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks, or visualizing network topologies. Applicable to social networks, biological networks, transportation systems, citation networks, and any domain involving pairwise relationships.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Analyze Azure resource groups and generate detailed Mermaid architecture diagrams showing the relationships between individual resources. WHEN: create architecture diagram, visualize Azure resources, show resource relationships, generate Mermaid diagram, analyze resource group, diagram my resources, architecture visualization, resource topology, map Azure infrastructure.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Analyze Azure resource groups and generate detailed Mermaid architecture diagrams showing the relationships between individual resources. WHEN: create architecture diagram, visualize Azure resources, show resource relationships, generate Mermaid diagram, analyze resource group, diagram my resources, architecture visualization, resource topology, map Azure infrastructure.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Create and enrich durable data catalogs using the native DS_CATALOG_V1 Markdown contract, declared entity relationships, privacy citation fields, and stable relationship IDs. Use when inventorying engagement data, recording semantic relationships, or preparing a catalog for ERD rendering.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Plan the merging of two families thoughtfully — roles, rules, routines, and relationships — so a blended household starts on the right foot instead of a collision. Use when asked to help blend our families, moving in with my partner and their kids, step-parenting help, or how to merge two households. Produces a read on the situation and its sensitivities, an approach to step-parent roles and discipline, a plan to align house rules and routines across homes, ways to build relationships at each child's pace, and how to handle exes and loyalty binds — realistic, not idealized. Not therapy.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Design a restorative practice protocol for addressing harm, rebuilding trust, and restoring relationships. Use when managing conflict, behavioural incidents, or relationship breakdown between students.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Comprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks, or visualizing network topologies. Applicable to social networks, biological networks, transportation systems, citation networks, and any domain involving pairwise relationships.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Designs convex/schema.ts tables, validators, indexes, and relationships, and keeps the schema honest as data evolves. Use when creating tables, adding fields, choosing index fields, modeling relationships, or when a validator error appears at deploy time.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Provides Spring Data Neo4j integration patterns for Spring Boot applications. Use when you need to work with a graph database, Neo4j nodes and relationships, Cypher queries, or Spring Data Neo4j. Creates node entities with @Node annotation, defines relationships with @Relationship, writes Cypher queries using @Query, configures imperative and reactive Neo4j repositories, implements graph traversal patterns, and sets up testing with embedded databases.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Reconstruct and report long-running or multi-turn research, architecture questions, reviews, decisions, completion results, and status as a clear, self-contained brief. Use when a reader must re-enter earlier context, understand the real question and its relationships, distinguish verified facts from judgment and open evidence, or make a decision without reconstructing the work log. Quote the relevant original user wording before substantive analysis, keep one coherent main line, use spatial diagrams when relationships matter, and finish with an explicit decision boundary and practical next step.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Applies abstract interpretation using different abstract domains (intervals, octagons, polyhedra, sign, congruence) to statically analyze program variables and infer invariants, value ranges, and relationships. Use when analyzing program properties, inferring loop invariants, detecting potential errors, or understanding variable relationships through static analysis.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Lists tables, describes columns and data types, identifies foreign key relationships, and maps entity relationships in a database. Use when the user asks about database schema, table structure, column types, what tables exist, ERD, foreign keys, or how entities relate.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Design a restorative practice protocol for addressing harm, rebuilding trust, and restoring relationships. Use when managing conflict, behavioural incidents, or relationship breakdown between students.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Interpersonal communication theory and practice for one-on-one and small group interaction. Covers communication models (linear, transactional, constructivist), self-disclosure and Johari Window, relational dialectics, communication climate, supportive versus defensive communication, feedback models, and adapting style across relationships and contexts. Use when analyzing communication dynamics, improving relationships, giving feedback, or understanding communication breakdowns between individuals.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Framework-agnostic SQLAlchemy 2.0 core shared by fastapi-plugin and flask-plugin: declarative mapped classes with Mapped/mapped_column, column type selection, relationships with explicit lazy loading and cascades, 2.0-style select() querying, transaction/flush discipline, and Alembic-agnostic migration metadata rules. Framework plugins layer their delta skills (async sessions for FastAPI, Flask-SQLAlchemy integration for Flask) on top of this skill. Use this skill to: - Write SQLAlchemy 2.0 declarative models with Mapped[T] annotations and mapped_column(). - Pick correct column types (String(N), Numeric, DateTime(timezone=True), Uuid, Enum). - Define relationships with explicit lazy loading strategy and cascade settings. - Query with 2.0-style select() statements and manage flush vs commit boundaries. - Keep model metadata visible to Alembic autogenerate. Do NOT use this skill for: - FastAPI async engine/session lifecycle — see fastapi-plugin:sqlalchemy-patterns. - Flask-SQLAlchemy extension setup and Flask-Migrate — see flask-plugin:sqlalchemy-patterns. - Python idioms — see python-foundation:python-conventions.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Designing Lookup vs Master-Detail vs Hierarchical vs External relationships: cascade delete, roll-up summaries, ownership, sharing implications, polymorphic lookups, junction objects, relationship depth limits. NOT for restricting which records a lookup can pick — use admin/lookup-filter-cross-object-patterns. NOT for a roll-up across a plain lookup — use data/roll-up-summary-alternatives.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use this skill when creating, configuring, or troubleshooting FSC Relationship Groups — including Household, Professional Group, and Trust group types; member role assignment via AccountContactRelation FSC fields; Primary Group designation; and group-level wealth aggregation rollups. NOT for standard account relationships, Contact-Account relationships outside FSC, NPSP household configuration, or Financial Account role setup (use admin/financial-account-setup).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use the Malpedia platform and API to research malware family relationships, track variant evolution, link families to threat actors, and integrate YARA rules for detection across malware lineages.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.