'postgresql' 검색 결과

Create weekly reports from Postgres metrics, comparing current figures with recent weeks. Add plain-language explanations for notable changes, flag missing data, and post one report to Slack while keeping database access read-only.

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• Preparing a weekly metrics report for Slack
• Reviewing weekly changes and recent trends
• Explaining notable changes and flagging data gaps

Develop and debug LangBot's backend and web frontend. The skill guides environment setup, API additions, authentication, database migrations, and testing, including updates to matching MCP tools so agents can use changed API features.

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• Set up the LangBot backend and frontend for development
• Add an API endpoint and its matching MCP tool
• Update the database schema with Alembic

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

Manage machine learning experiments with MLflow by recording settings, metrics, files, and trained models. Covers experiment comparison, model version management, reproducible project configurations, and deployment workflows across local and cloud environments.

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• Recording experiment settings and evaluation results
• Comparing model performance across experiments
• Managing model versions for production use

Build and run Omnigent’s server and Postgres together with Docker Compose on a laptop or existing Docker host. Use the supplied configuration and troubleshooting guidance to rebuild images, investigate startup problems, or adapt deployment to another platform.

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• Running Omnigent locally with Postgres
• Starting the stack on an existing VPS or EC2 host
• Investigating startup and web interface problems

Choose, create, and review software diagrams that explain structure, interactions, workflows, states, or data relationships. Select suitable notation and rendering tools, then plan static exports or interactive views with readable layouts, accessible controls, and validation.

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• Explain login interactions with a sequence diagram
• Turn a database schema into an entity relationship diagram
• Document application architecture with C4

Write, review, and optimize Postgres queries, database structures, and configuration using guidance maintained by Supabase. Prioritized rules and SQL examples help assess query speed, connections, indexes, and row-level security, which controls access to individual rows.

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• Review slow SQL queries
• Assess table structures and indexes
• Review connection pooling and scaling settings

Create ADRs, short records of architectural decisions, that explain what was chosen, why, and with what trade-offs. Choose among three formats and organize dates, status, numbering, and related links for future team members.

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• Recording why a database was chosen
• Preserving the rationale for a framework choice
• Documenting an authentication approach

Draft structured RFCs, proposals for gathering feedback before a major decision. Organize background, weighted criteria, alternatives, costs, and a recommendation so stakeholders can compare choices and understand the reasons for the proposed direction.

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• Proposing a database migration
• Reviewing changes to team workflows
• Comparing tools or vendors

Build chat bots for multiple platforms using shared TypeScript logic with Chat SDK. The skill guides message handling, interactive cards, webhook connections, streamed AI replies, and adapters that connect platforms or store conversation state.

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• Build a bot for Slack and Teams
• Respond to mentions and direct messages
• Add approval buttons to message cards

Assess web applications for SQL injection, where user input changes database queries. Guides authorized testing through response comparisons, timing checks, impact demonstrations, and evidence collection, leading to vulnerability reports and remediation recommendations.

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• Checking forms and URL parameters for SQL injection
• Investigating flaws through response changes or delays
• Validating authentication bypass risks within an agreed scope

Use SQLMap to test SQL injection, where application inputs can alter database queries. The skill guides automated detection, database and table discovery, selected data extraction, and documentation of the vulnerability type and severity.

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• Testing suspected SQL injection in an authorized web application
• Inspecting database, table, and column structures
• Testing POST requests captured with Burp Suite

Guides authorized security assessments with Metasploit, from scanning and vulnerability testing to payload generation, code used during a test, and post-exploitation investigation. It also covers session management and recording evidence of findings.

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• Checking vulnerabilities in an authorized test environment
• Finding modules for a specific CVE
• Reviewing system information after a test compromise

Build, validate, and release Marina applications and reports, then load or query their Postgres data. Manage application revisions, preview changes locally, roll back to retained packages, or archive applications through the Marina command line.

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• Build and publish a Marina report or application
• Preview application changes with local Postgres
• Load tables and inspect data with SQL

Give new users a practical introduction to what the agent can help with, including coding, memory, research, and planning. Explain natural ways to ask for work, recall earlier lessons, and prepare handoffs for later sessions.

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• Explore what the agent can help with
• Learn how to make a first request
• Learn how to recall lessons from earlier work

Search stored learnings from past sessions by meaning or keywords. Retrieve relevant entries in full, along with their type, confidence, and session context, to revisit earlier findings about development patterns, installation, or errors.

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• Revisiting hook development patterns
• Finding earlier wizard installation learnings
• Retrieving past findings about TypeScript errors

Comprehensive guide for Go database access — parameterized queries, struct scanning, NULLable columns, transactions, isolation levels, SELECT FOR UPDATE, connection pool, batch processing, context propagation, and migration tooling. Use when writing, reviewing, or debugging Golang code that interacts with PostgreSQL, MariaDB, MySQL, or SQLite; for database testing; or for questions about database/sql, sqlx, or pgx. Does NOT generate database schemas or migration SQL.

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Creates a complete Amazon Aurora database cluster with instances, handling cluster creation, instance provisioning, and Secrets Manager password management in the proper sequence. Use when setting up new Aurora MySQL or PostgreSQL clusters with production-ready configuration.

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Amazon Redshift is NOT PostgreSQL; corrects LLM mistakes; covers SQL, metadata, connectivity/auth, storage, query performance, and operations. Applies ONLY to Redshift (provisioned or Serverless). Pushes back on: CREATE INDEX, string_agg, pg_catalog, text type, SERIAL, stl_query. Triggers on: Redshift SQL, Redshift CREATE TABLE, Redshift COPY/UNLOAD, slow or suddenly slow Redshift query, EXPLAIN plan, queue wait, stale statistics/ANALYZE, result cache, Redshift permission denied, Redshift disk full, storage growth, snapshot/backup cost, ghost rows/bloat, VACUUM, spill to disk, distribution skew, Redshift system views, QUALIFY, PIVOT, MERGE, materialized views, Redshift Data API (Python/boto3), Redshift workload management (WLM), concurrency scaling, Redshift resize, Spectrum, awsdatacatalog, connection failures (SSL/TLS, ODBC/JDBC, connection limit), IAM/SAML federation, IAM Identity Center, datashares. Does NOT apply to: S3 policies, Athena, Glue/Iceberg outside Redshift, Aurora, RDS, DynamoDB.

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Create and troubleshoot AWS Glue connections to JDBC databases (Oracle, SQL Server, PostgreSQL, MySQL, RDS), Redshift, Snowflake, and BigQuery. Gathers connection hints from user, discovers existing connections and RDS/Redshift candidates, registers credentials in Secrets Manager or IAM DB auth, configures VPC, and tests. Triggers on: connect to database, set up Glue connection, register data source, connect to Snowflake/BigQuery/RDS, connection timeout, test connection, troubleshoot connection. Do NOT use for moving data (use ingesting-into-data-lake), creating tables (use creating-data-lake-table), queries (use querying-data-lake), catalog exploration (use exploring-data-catalog), or SaaS (Salesforce, ServiceNow, SAP, MongoDB, Kafka).

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Import data into the AWS data lake from S3 files, local uploads, JDBC databases (Oracle, SQL Server, PostgreSQL, MySQL, RDS, Aurora), Amazon Redshift, Snowflake, BigQuery, DynamoDB, or existing Glue catalog tables (migration). Default target is S3 Tables; standard Iceberg on a general purpose bucket is supported where S3 Tables is not adopted. Handles one-time loads, recurring pipelines, migrations. Triggers on: import data, load data, ingest, sync database, migrate table, move data to AWS, set up pipeline, ETL, pull from Snowflake, query BigQuery into S3, export DynamoDB, CTAS, convert to Iceberg. Do NOT use for setting up or troubleshooting Glue connections (use connecting-to-data-source), creating empty tables (use creating-data-lake-table), running queries (use querying-data-lake), finding tables by fuzzy name (use finding-data-lake-assets), catalog audit (use exploring-data-catalog), or SaaS platforms like Salesforce, ServiceNow, SAP, MongoDB, Kafka.

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PostgreSQL optimization including indexes, query plans, partitioning, JSONB operations, and connection pooling

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Query optimization, indexing strategies, and database performance tuning for PostgreSQL and MySQL

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Build robust backend systems with modern technologies (Node.js, Python, Go, Rust), frameworks (NestJS, FastAPI, Django), databases (PostgreSQL, MongoDB, Redis), APIs (REST, GraphQL, gRPC), authentication (OAuth 2.1, JWT), testing strategies, security best practices (OWASP Top 10), performance optimization, scalability patterns (microservices, caching, sharding), DevOps practices (Docker, Kubernetes, CI/CD), and monitoring. Use when designing APIs, implementing authentication, optimizing database queries, setting up CI/CD pipelines, handling security vulnerabilities, building microservices, or developing production-ready backend systems.

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