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Found 276 Skills
Deploy to Cloudflare (Workers, R2, D1), Docker, GCP (Cloud Run, GKE), Kubernetes (kubectl, Helm). Use for serverless, containers, CI/CD, GitOps, security audit.
Amazon OpenSearch Service and Serverless across five capabilities — migration (Solr/ES/self-managed OpenSearch into AOS/AOSS, schema/query translation, sizing, cutover); provisioning (domain + AOSS lifecycle, upgrades, storage tiers, FGAC, monitoring); search (vector / semantic / hybrid / RAG with Bedrock connectors); log-analytics (PPL, OSI ingestion, anomaly detection, OpenSearch Dashboards, Splunk/Datadog alternatives); trace-analytics (OTel spans, service maps, Data Prepper). Triggers on OpenSearch, AOS, AOSS, Elasticsearch, ELK, Solr, Lucene, vector / k-NN / semantic / hybrid / neural search, RAG, ELSER, log analytics, observability, Kibana, OSI, OCU, PPL, trace analytics, BM25, eDisMax, schema.xml, ILM, ISM, FAISS, HNSW, Migration Assistant for Amazon OpenSearch Service, Historical Data Migration, Live Traffic Migration, UltraWarm, OR1, Splunk/Datadog alternative, moving off Solr. Picks ONE capability per ask, names instance class + count + shard math, ships query DSL examples.
Run headless Chrome in Next.js serverless functions using @sparticuz/chromium + puppeteer-core. Use when the user needs browser automation from a Next.js app, wants to take screenshots or snapshots from server actions or API routes, or is building a Next.js app that needs headless Chrome. Triggers include "screenshot from Next.js", "headless Chrome in serverless", "browser automation in Next.js", "puppeteer on Vercel", or any task requiring Chrome in a Next.js server context.
Build Python APIs on Cloudflare Workers using pywrangler CLI and WorkerEntrypoint class pattern. Includes Python Workflows for multi-step DAG automation. Prevents 11 documented errors. Use when: building Python serverless APIs, migrating Python to edge, or troubleshooting async errors, package compatibility, handler pattern mistakes, RPC communication issues.
AWS cloud resources including EC2, RDS, Lambda, ECS/EKS, VPC networking, load balancers, databases, serverless, messaging, and cost optimization. Monitor AWS infrastructure, analyze resource usage, optimize costs, and ensure security compliance.
Novita AI: LLM, Image Generation & Editing, Video Generation, Audio (TTS/ASR), and GPU Cloud. Use this skill whenever the user wants to call Novita AI APIs — chat with LLMs (DeepSeek, Llama, Qwen), generate images (FLUX, Stable Diffusion, Seedream, Hunyuan Image), edit images (remove background, upscale, inpainting, img2img, outpainting, reimagine, merge face, replace background, remove text), generate videos (Kling, Wan, Hunyuan, Minimax Hailuo, Vidu, PixVerse, Seedance), do text-to-speech or speech-to-text (MiniMax TTS, GLM TTS, Fish Audio, ASR, voice cloning), run OpenAI-compatible batch jobs, manage GPU cloud instances and serverless endpoints, or check account balance and billing. Also trigger when the user mentions novita.ai, Novita AI, Novita API key, or wants to use any Novita platform service — even if they just say "generate an image" or "run an LLM" and Novita is available as a provider.
Guidelines for building production-grade microservices with FastAPI/Python and Go, covering serverless patterns, clean architecture, observability, and resilience.
Expert cloud architect specializing in AWS/Azure/GCP multi-cloud infrastructure design, advanced IaC (Terraform/OpenTofu/CDK), FinOps cost optimization, and modern architectural patterns. Masters serverless, microservices, security, compliance, and disaster recovery. Use PROACTIVELY for cloud architecture, cost optimization, migration planning, or multi-cloud strategies.
Serverless and microservices development guidelines covering FastAPI, cloud-native patterns, API gateways, and best practices for scalable serverless architectures.
TensorLake SDK for building agentic workflows, sandboxed code execution, and document parsing/extraction. Use when the user mentions tensorlake, or asks about TensorLake APIs/docs/capabilities. Also use when the user is building AI agents or agentic applications that need serverless workflow orchestration (parallel map/reduce DAGs), sandboxed execution of LLM-generated code, or document parsing, structured extraction, and OCR from PDFs/images. Works with any LLM provider (OpenAI, Anthropic), agent framework (LangChain, CrewAI, LlamaIndex), database, or API as the infrastructure layer.
Amazon Redshift is NOT PostgreSQL — corrects PostgreSQL-derived LLM mistakes; covers Redshift-specific SQL, DDL, COPY/UNLOAD, system views, metadata discovery, and operational patterns. Applies ONLY when the task is about Redshift itself (cluster, Serverless workgroup, or Redshift SQL). Pushes back on: CREATE INDEX, string_agg, pg_catalog, text type, SERIAL, stl_query, LATERAL, RETURNING. Triggers on: Redshift SQL, Redshift CREATE TABLE, Redshift COPY/UNLOAD, slow Redshift query, Redshift permission denied, Redshift disk full, Redshift system views, QUALIFY, PIVOT, MERGE, Redshift Data API, Redshift WLM, concurrency scaling, Redshift resize, Redshift Spectrum external tables. Does NOT apply to (defer to that service's own skill): Amazon S3 storage/bucket policies, Athena or Glue queries/catalogs, data-lake or Iceberg work outside Redshift, Aurora, RDS, or DynamoDB — but S3/Glue ARE in scope for Redshift COPY, UNLOAD, or data-lake queries (external schemas/tables on S3).
Selects, deploys, and customizes AI models on Amazon SageMaker. Fine-tuning (SFT, DPO, RLVR, RLAIF), model selection, dataset preparation, evaluation, deployment to SageMaker endpoints or Bedrock, and endpoint diagnostics. Covers the full lifecycle from planning through production. Use when fine-tuning models on SageMaker, selecting base models from SageMaker Hub, finding a model to deploy without fine-tuning, transforming datasets for training, checking data readiness, evaluating model quality, deploying to endpoints, setting up IAM roles and S3 buckets for training jobs, or managing a SageMaker Managed MLflow app. Also use to check endpoint health, diagnose failures, debug latency or errors, or view container logs and CloudWatch metrics. Covers Serverless Model Customization, Nova and OSS deployment paths, and PySDK v3 usage. NOT for Ground Truth labeling, Feature Store, or general-purpose AWS infrastructure.