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Found 54 Skills
Scaffolds new Terraform modules with standardized structure including main.tf, variables.tf, outputs.tf, versions.tf, and README.md. This skill should be used when users want to create a new Terraform module, set up module structure, or need templates for common infrastructure patterns like VPC, ECS, S3, or RDS modules.
Comprehensive infrastructure engineering covering DevOps, cloud platforms, FinOps, and DevSecOps. Platforms: AWS (EC2, Lambda, S3, ECS, EKS, RDS, CloudFormation), Azure basics, Cloudflare (Workers, R2, D1, Pages), GCP (GKE, Cloud Run, Cloud Storage), Docker, Kubernetes. Capabilities: CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins), GitOps, infrastructure as code (Terraform, CloudFormation), container orchestration, cost optimization, security scanning, vulnerability management, secrets management, compliance (SOC2, HIPAA). Actions: deploy, configure, manage, scale, monitor, secure, optimize cloud infrastructure. Keywords: AWS, EC2, Lambda, S3, ECS, EKS, RDS, CloudFormation, Azure, Kubernetes, k8s, Docker, Terraform, CI/CD, GitHub Actions, GitLab CI, Jenkins, ArgoCD, Flux, cost optimization, FinOps, reserved instances, spot instances, security scanning, SAST, DAST, vulnerability management, secrets management, Vault, compliance, monitoring, observability. Use when: deploying to AWS/Azure/GCP/Cloudflare, setting up CI/CD pipelines, implementing GitOps workflows, managing Kubernetes clusters, optimizing cloud costs, implementing security best practices, managing infrastructure as code, container orchestration, compliance requirements, cost analysis and optimization.
Use when working on the backend API (packages/api). Covers Elysia routes, Drizzle ORM, TypeBox schemas, JWT authentication, S3 uploads, Google Sheets logging, and the Next.js hybrid setup.
AWS development with CDK best practices, serverless patterns, cost optimization, and event-driven architecture. Use when deploying to AWS, writing Lambda functions, configuring API Gateway, working with DynamoDB, S3, or any AWS service.
Bun JavaScript/TypeScript runtime and all-in-one toolkit. Covers runtime, package manager, bundler, test runner, HTTP server, WebSockets, SQLite, S3, Redis, file I/O, shell scripting, FFI, Markdown parser. Keywords: bun, bunx, bun install, bun run, bun test, bun build, Bun.serve, Bun.file, bun:sqlite, Bun.markdown.
Amazon Bedrock Knowledge Bases for RAG (Retrieval-Augmented Generation). Create knowledge bases with vector stores, ingest data from S3/web/Confluence/SharePoint, configure chunking strategies, query with retrieve and generate APIs, manage sessions. Use when building RAG applications, implementing semantic search, creating document Q&A systems, integrating knowledge bases with agents, optimizing chunking for accuracy, or querying enterprise knowledge.
Amazon Web Services cloud platform with Lambda, EC2, S3, and RDS. Use for AWS infrastructure.
Master Rails Active Storage for file attachments, cloud storage integration, image transformations, and direct uploads. Use when implementing file uploads, managing attachments to records, configuring S3/GCS storage, generating image variants, and handling file analysis. Covers local disk, cloud services, direct uploads, and advanced patterns.
Using DuckDB with remote cloud storage via HTTPFS extension, fsspec, and Delta Lake integration. Covers S3, GCS, Azure, and S3-compatible endpoints.
Native Arrow filesystem integration with PyArrow. Optimized for Parquet workflows, zero-copy data transfer, predicate pushdown, and column pruning. Covers S3, GCS, HDFS with PyArrow datasets.
Creates Robot Framework test cases for SnapLogic account creation. Use when the user wants to create accounts (Oracle, PostgreSQL, Snowflake, Kafka, S3, etc.), needs to know what environment variables to configure, or wants to see account test case examples.
Search data using vector similarity, full-text keywords, or hybrid methods with Reciprocal Rank Fusion (RRF). Use when setting up embeddings for search, configuring full-text indexing, writing vector_search/text_search/rrf SQL queries, using the /v1/search HTTP API, or configuring vector engines like S3 Vectors.