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Found 87 Skills
Complete E2E (end-to-end) and integration testing skill for TypeScript/NestJS projects using Jest, real infrastructure via Docker, and GWT pattern. ALWAYS use this skill when user needs to: **SETUP** - Initialize or configure E2E testing infrastructure: - Set up E2E testing for a new project - Configure docker-compose for testing (Kafka, PostgreSQL, MongoDB, Redis) - Create jest-e2e.config.ts or E2E Jest configuration - Set up test helpers for database, Kafka, or Redis - Configure .env.e2e environment variables - Create test/e2e directory structure **WRITE** - Create or add E2E/integration tests: - Write, create, add, or generate e2e tests or integration tests - Test API endpoints, workflows, or complete features end-to-end - Test with real databases, message brokers, or external services - Test Kafka consumers/producers, event-driven workflows - Working on any file ending in .e2e-spec.ts or in test/e2e/ directory - Use GWT (Given-When-Then) pattern for tests **REVIEW** - Audit or evaluate E2E tests: - Review existing E2E tests for quality - Check test isolation and cleanup patterns - Audit GWT pattern compliance - Evaluate assertion quality and specificity - Check for anti-patterns (multiple WHEN actions, conditional assertions) **RUN** - Execute or analyze E2E test results: - Run E2E tests - Start/stop Docker infrastructure for testing - Analyze E2E test results - Verify Docker services are healthy - Interpret test output and failures **DEBUG** - Fix failing or flaky E2E tests: - Fix failing E2E tests - Debug flaky tests or test isolation issues - Troubleshoot connection errors (database, Kafka, Redis) - Fix timeout issues or async operation failures - Diagnose race conditions or state leakage - Debug Kafka message consumption issues **OPTIMIZE** - Improve E2E test performance: - Speed up slow E2E tests - Optimize Docker infrastructure startup - Replace fixed waits with smart polling - Reduce beforeEach cleanup time - Improve test parallelization where safe Keywords: e2e, end-to-end, integration test, e2e-spec.ts, test/e2e, Jest, supertest, NestJS, Kafka, Redpanda, PostgreSQL, MongoDB, Redis, docker-compose, GWT pattern, Given-When-Then, real infrastructure, test isolation, flaky test, MSW, nock, waitForMessages, fix e2e, debug e2e, run e2e, review e2e, optimize e2e, setup e2e
Production backend systems development. Stack: Node.js/TypeScript, Python, Go, Rust | NestJS, FastAPI, Django, Express | PostgreSQL, MongoDB, Redis. Capabilities: REST/GraphQL/gRPC APIs, OAuth 2.1/JWT auth, OWASP security, microservices, caching, load balancing, Docker/K8s deployment. Actions: design, build, implement, secure, optimize, deploy, test APIs and services. Keywords: API design, REST, GraphQL, gRPC, authentication, OAuth, JWT, RBAC, database, PostgreSQL, MongoDB, Redis, caching, microservices, Docker, Kubernetes, CI/CD, OWASP, security, performance, scalability, NestJS, FastAPI, Express, middleware, rate limiting. Use when: designing APIs, implementing auth/authz, optimizing queries, building microservices, securing endpoints, deploying containers, setting up CI/CD.
Fetches official documentation for external libraries and frameworks (React, Next.js, Prisma, FastAPI, Express, Tailwind, MongoDB, etc.) with 60-90% token savings via content-type filtering. Use this skill when implementing features using library APIs, debugging library-specific errors, troubleshooting configuration issues, installing or setting up frameworks, integrating third-party packages, upgrading between library versions, or looking up correct API patterns and best practices. Triggers automatically during coding work - fetch docs before writing library code to get correct patterns, not after guessing wrong.
Quick access to up-to-date library documentation using MCP. Use this skill when you need to reference official documentation for libraries, frameworks, or APIs. Leverages the context7 MCP server to fetch current docs for React, Next.js, Vue, MongoDB, Supabase, and hundreds of other libraries. Complements the documentation-maintainer agent.
Diagnose and manage Alibaba Cloud databases through natural language. Use when users need to troubleshoot database performance issues (high CPU, slow queries, abnormal connections, lock waits), check instance status, analyze disk space, optimize SQL, run health inspections, or detect security baseline violations. Supports RDS (MySQL/PostgreSQL/SQL Server), PolarDB, MongoDB, Redis (Tair), and Lindorm. Trigger this skill even for casual descriptions like "my database is slow", "can't connect to the database", "help me check this SQL", or "database disk is almost full". Also suitable for consulting Alibaba Cloud-specific database features (e.g., PolarDB Serverless, DAS autonomy capabilities) and comparing product differences (RDS vs PolarDB). Do NOT use this skill for general SQL tutorials, non-Alibaba Cloud databases, or local database administration.
World-class backend engineering - distributed systems, database architecture, API design, and the battle scars from scaling systems that handle millions of requestsUse when "backend, api, database, postgres, mysql, mongodb, redis, graphql, rest, authentication, authorization, caching, queue, background job, webhook, migration, transaction, n+1, rate limit, server, node.js, python, go, backend, api, database, architecture, performance, reliability, security" mentioned.
Use when deploying a database to Zeabur. Use when user needs MySQL, PostgreSQL, MongoDB, or Redis. Use when user says "I need a database", "add database", "deploy postgres", "set up MySQL", "add Redis", "add MongoDB", or "connect to database". Also use when user mentions data persistence issues like "data lost after restart", "data not saved", "data disappears", "need persistent storage for data", or "how to persist data". Also use when integrating a database with an existing service.
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.
Guide for configuring Infisical Dynamic Secrets — on-demand, short-lived credentials for databases, cloud IAM, SSH, and Kubernetes. Covers 27 providers including PostgreSQL, MySQL, Redis, MongoDB, AWS IAM, GCP IAM, SSH certificates, Kubernetes service accounts, and more. Use this skill when someone asks about: dynamic secrets, ephemeral database credentials, short-lived tokens, rotating database users, dynamic PostgreSQL/MySQL/Redis credentials, SSH certificates, temporary AWS IAM users, or 'how do I generate temporary credentials with Infisical'.
Senior Database Administrator with expertise in PostgreSQL, MySQL, MongoDB, and enterprise database systems. Specializes in high availability architectures, performance tuning, backup strategies, and database security for production environments.
Automatically discover database skills when working with SQL, PostgreSQL, MongoDB, Redis, database schema design, query optimization, migrations, connection pooling, ORMs, or database selection. Activates for database design, optimization, and implementation tasks.
Database design specialist for schema modeling, query optimization, indexing strategies, and data integrityUse when "database design, schema, indexes, query optimization, migrations, normalization, database scaling, foreign keys, data modeling, database, sql, postgres, mysql, mongodb, schema, indexes, migrations, normalization, optimization" mentioned.