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Found 648 Skills
API gateway patterns and implementations. Kong, AWS API Gateway, NGINX as gateway, rate limiting, request routing, authentication offloading, and request/response transformation. USE WHEN: user mentions "API gateway", "Kong", "AWS API Gateway", "NGINX gateway", "gateway pattern", "request routing", "BFF" DO NOT USE FOR: reverse proxy basics - use infrastructure skills; service mesh - use `service-mesh`; rate limiting in app - use `rate-limiting`
Implement Microsoft's Enhanced Security Admin Environment (ESAE) tiered administration model for Active Directory. Covers Tier 0/1/2 separation, privileged access workstations (PAWs), administrative f
This skill teaches security teams how to deploy and operationalize Amazon GuardDuty for continuous threat detection across AWS accounts and workloads. It covers enabling protection plans for S3, EKS, EC2 runtime monitoring, and Lambda, interpreting finding severity levels, and building automated response workflows using EventBridge and Lambda.
Cloud object storage integration with AWS S3, Azure Blob Storage, and Google Cloud Storage. Covers presigned URLs, multipart uploads, bucket policies, lifecycle rules, and CDN integration. USE WHEN: user mentions "S3", "blob storage", "cloud storage", "object storage", "presigned URL", "file upload to cloud", "GCS", "Azure Blob", "bucket" DO NOT USE FOR: local file uploads - use `file-upload`; database BLOB columns; local filesystem operations
This skill should be used when the user asks to "set up oodle integration", "onboard to oodle", "integrate kubernetes with oodle", "connect AWS to oodle", "install oodle collector", or mentions setting up observability with Oodle. Discovers the environment, recommends matching integrations from available setup specs, and executes step-by-step installation. Not for querying existing metrics, logs, or traces (use /oodle-metrics-query, /oodle-logs, /oodle-traces instead).
Infrastructure-as-Code patterns for data engineering using Terraform to provision AWS resources (S3, EC2, IAM)
Connect to SageMaker Managed MLflow (mlflow-app or mlflow-tracking-server ARN) as an MLflow backend, then hand off to the other MLflow skills. Triggers on a SageMaker MLflow ARN (arn:aws:sagemaker:...:mlflow-app/... or arn:aws:sagemaker:...:mlflow-tracking-server/...) or "SageMaker Managed MLflow".
Executable documentation governance with compound engineering and abductive learning. Enforces the Seven Laws through type compilation, schema validation, and hookify-based enforcement. Implements programmatic compound engineering where K' = K ∪ crystallize(assess(τ)) for monotonic knowledge growth. Integrates abstracted abductive learning (OHPT protocol) for systematic debugging and pattern extraction. Trigger when writing code, debugging, establishing governance, or when mentioned vibecode, compound, abductive, or executable documentation. Self-validating and homoiconic.
Plan and coordinate the deployment of a model to Amazon SageMaker AI. Use this skill whenever the user wants to deploy, host, serve, or expose a model on SageMaker or AWS — including phrases like "deploy a model", "host this LLM on AWS", "serve this embedding model", "deploy a reranker", "deploy a text-to-image / diffusion model", "host this for async inference", "create an endpoint", "serve my fine-tuned model", or any request that involves making a model available for inference on AWS. Use this even when the user is vague (e.g. "I just want to get this running on AWS, you figure it out"). Works for text-generation LLMs, embedding models, rerankers, classifiers, text-to-image / diffusion models — picks the right serving stack and chooses between real-time and async inference. This is the entry-point skill for SageMaker deployment work — it asks clarifying questions, picks a deployment pathway, and coordinates the other deployment skills.
Companion CLIs for Runpod workflows — HuggingFace, GitHub, Docker, and AWS.
Synthesize and generate AWS infrastructure as code using CDK. Creates composable infrastructure components and deployment patterns programmatically.
YAML functions: !terraform.state, !terraform.output, !store, !store.get, !env, !exec, !include, !template, !literal, !random, !aws.*, !cwd, !repo-root