'data write' 검색 결과

Build Next.js 14+ applications with App Router, server-rendered components, and form actions. Produces routes, page layouts, data fetching, loading and error states, and SEO metadata, while supporting performance optimization and deployment preparation.

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• Building pages and layouts with App Router
• Implementing form submissions with Server Actions
• Adding loading states, error handling, and SEO metadata

Investigate slow PostgreSQL and MySQL queries using execution plans, which show how the database runs a query. Develop index, SQL, and configuration changes, then compare measurements before and after each change to validate the results.

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• Investigating slow SQL queries
• Reviewing database index design
• Tuning memory and database configuration

Audit and fix four access-control problems in Convex apps: impersonation, missing ownership checks, sensitive data exposure, and writes into another user's container. Check the authentication foundation first, then verify changes with TypeScript.

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• Check whether callers can impersonate another user
• Restrict document access to its owner
• Review queries that expose sensitive data

Work with Apache Beam I/O connectors, components that read and write external data. Get guidance on connector usage, unit and integration tests, troubleshooting data connections, and the basic structure of new connectors.

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• Add BigQuery or Kafka reads and writes to a pipeline
• Run unit and integration tests for connectors
• Investigate data source or destination issues

Implement and review browser API requests in OpenBot using shared patterns for reading and changing data. Covers cache keys, refreshing stored results after changes, error handling, and how components display request states.

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• Adding a screen that displays server data
• Implementing create, update, and delete actions
• Investigating stale lists after an update

Write and troubleshoot n8n expressions, the formulas that pass and transform data between workflow steps. Correct field references, read webhook inputs, format dates and text, and query nested JSON while checking for silently missing results.

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• Include webhook form data in Slack messages
• Fix expressions that return null or literal text
• Extract and total values from nested JSON

Execute read-only SQL queries against multiple Microsoft SQL Server databases. Use when: (1) querying MSSQL/SQL Server databases, (2) exploring database schemas/tables, (3) running SELECT queries for data analysis, (4) checking database contents. Supports multiple database connections with descriptions for intelligent auto-selection. Blocks all write operations (INSERT, UPDATE, DELETE, DROP, etc.) for safety.

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Execute read-only SQL queries against multiple MySQL databases. Use when: (1) querying MySQL databases, (2) exploring database schemas/tables, (3) running SELECT queries for data analysis, (4) checking database contents. Supports multiple database connections with descriptions for intelligent auto-selection. Blocks all write operations (INSERT, UPDATE, DELETE, DROP, etc.) for safety.

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Execute read-only SQL queries against multiple PostgreSQL databases. Use when: (1) querying PostgreSQL databases, (2) exploring database schemas/tables, (3) running SELECT queries for data analysis, (4) checking database contents. Supports multiple database connections with descriptions for intelligent auto-selection. Blocks all write operations (INSERT, UPDATE, DELETE, DROP, etc.) for safety.

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Designs relational and document database schemas from requirements or an existing app - tables and collections, keys, relationships, constraints, indexes driven by real query patterns, ERDs, and reversible migration scripts - with PostgreSQL (including Supabase) as the default and MySQL, SQLite, and MongoDB supported. Use when the user wants to model data for a new app or feature, review or fix an existing schema, choose keys or indexes, plan multi-tenancy, normalize or denormalize, or write CREATE TABLE statements or migrations, even if they just describe their app and ask "how should I store this". For moving data between database providers, use database-migrator.

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Execute read-only SQL queries against multiple PostgreSQL databases. Use when: (1) querying PostgreSQL databases, (2) exploring database schemas/tables, (3) running SELECT queries for data analysis, (4) checking database contents. Supports multiple database connections with descriptions for intelligent auto-selection. Blocks all write operations (INSERT, UPDATE, DELETE, DROP, etc.) for safety.

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Use when reading from or writing to Neo4j with Apache Spark or Databricks using the Neo4j Connector for Apache Spark 6.0 (org.neo4j.connectors:spark) or 5.x (org.neo4j:neo4j-connector-apache-spark). Covers SparkSession setup, DataFrame reads via labels/Cypher/relationship scan, DataFrame writes with SaveMode, node.keys for MERGE, relationship write mapping, partition and batch tuning, PySpark and Scala examples, Databricks cluster config, Databricks secrets for credentials, Delta Lake to Neo4j pipelines. Does NOT handle Cypher authoring — use neo4j-cypher-skill. Does NOT handle the Python bolt driver — use neo4j-driver-python-skill. Does NOT handle GDS algorithms — use neo4j-gds-skill.

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Lightweight, script-driven variant of data2motion for turning data into a smooth, on-brand animated chart (one self-contained HTML) — built for a TEXT-ONLY model that cannot see its own output. You never write HTML/CSS/SVG/animation; you extract the data, pick a chart, fill a small JSON spec, and run one build script that owns 100% of the look and the motion, so the result cannot drift from the house template style or lose its smoothness. Use to turn a number/stat/table/CSV/paragraph into a quick animated chart, data reveal, or KPI when you want guaranteed template fidelity with minimal reasoning and no image feedback.

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Large-scale data migrations with validation, rollback, and zero-downtime strategies. Activate on: data migration, database migration, zero-downtime migration, dual-write, backfill, cutover, data validation, schema migration. NOT for: schema evolution in streams (use schema-evolution-manager), API versioning (use api-versioning-backward-compatibility).

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Write, validate, and (optionally) execute an NQL query against a Narrative dataset. Drafts the query from the user's question, runs `narrative_nql_validate` until it compiles, explains the query in plain English, and only runs it on explicit approval (or when invoked with `--run`). Use when: "write an NQL query for X", "query this dataset", "validate this NQL", "run NQL against dataset <id>", "how many rows match Y", "show me the top N records from <dataset>". (narrative-common)

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Large-scale data migrations with validation, rollback, and zero-downtime strategies. Activate on: data migration, database migration, zero-downtime migration, dual-write, backfill, cutover, data validation, schema migration. NOT for: schema evolution in streams (use schema-evolution-manager), API versioning (use api-versioning-backward-compatibility).

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Helps design ClickHouse tables, write analytical queries, and improve slow queries. Covers loading data in batches, preparing reusable summaries, and monitoring performance for large datasets, real-time dashboards, and time-series analysis.

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• Designing tables for large-scale analytics
• Improving slow aggregation queries
• Loading large datasets in batches

Plan market, competitor, consumer, or financial research with chapter outlines, data requirements, and chart plans. Then turn collected evidence into a structured Markdown report with comparisons, citations, and strategic implications, while clearly identifying missing data.

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• Planning research chapters and data collection requirements
• Turning market and competitor findings into a report
• Organizing consumer insights and brand strategy analysis

Work with genomic regions in Polars tables to find overlaps, nearby regions, covered bases, and gaps. Read and write bioinformatics files, query data with SQL, and check coordinate conventions when joining datasets or migrating from bioframe.

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• Finding variants that overlap genomic regions
• Merging regions and measuring covered bases
• Summarizing sequencing read depth

Connect a company SQL database, support ticket exports, and documents in cognee, linking shared people, teams, and projects so questions about ownership, decisions, and ongoing work can draw on several sources together.

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• Finding owners across company databases, tickets, and documents
• Tracing decisions across multiple company sources
• Checking who is handling a support issue

Connect business software to Claude by checking existing connectors first, then Zapier or scheduled exports. The skill narrows the task, configures access, tests real data, and explains limits, with approval required for write actions.

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• Connect business software that has no native Claude connector
• Retrieve open work orders for a daily briefing
• Use scheduled exports when direct connections are unavailable

Write and improve SQL for major data warehouses, accounting for differences in their syntax. Use it to build analytical queries, translate existing SQL, investigate errors, and review slow queries for performance improvements.

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• Translate SQL from PostgreSQL to BigQuery
• Review slow queries for performance improvements
• Calculate retention rates and funnel conversion

Write SQL that uses BigQuery’s built-in machine learning and generative AI for forecasting, anomaly detection, identifying drivers of change, searching by meaning, and classifying or summarizing text stored in your data.

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• Forecasting future values from time-series data
• Detecting anomalies and investigating drivers of change
• Searching documents by meaning

Guide SQLite database design and performance tuning for applications. Covers concurrent reads and writes, indexes that speed up queries, full-text search, JSON processing, analytical queries, and versioned changes to database structure.

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• Investigating slow SQLite queries
• Reducing contention between database reads and writes
• Designing full-text search and JSON queries