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Found 112 Skills
Build code-first notification workflows with @novu/framework. Use when defining workflows in TypeScript (Zod / JSON Schema / Class Validator), composing channel steps (email, SMS, push, chat, in-app) with action steps (delay, digest, custom), exposing Step Controls for non-technical teammates, rendering React/Vue/Svelte Email templates, hosting the Bridge Endpoint inside Next.js, Express, NestJS, Remix, Nuxt, SvelteKit, H3, or AWS Lambda, syncing to Novu Cloud via CLI / GitHub Actions, securing production with HMAC, or implementing translations, hydration, multi-channel orchestration, and LLM-powered notification logic in code.
Workload-aware architecture design for Apache Doris. MUST USE when designing data architectures, choosing between data models, planning ingestion strategies, sizing clusters, or translating business requirements into Apache Doris system designs. Complements doris-best-practices with decision frameworks and sizing-first workflow. Use when user describes a workload involving: IoT, sensor data, telemetry, real-time analytics, dashboard, log analysis, log search, CDC sync, time-series, device monitoring, point query service, ad-hoc analytics, lakehouse federation, ETL/ELT pipeline, report analytics, clickstream, user behavior, observability, metrics, fleet tracking, or any OLAP workload requiring table design from scratch. Also triggers on prompts like: "design a table for...", "how should I store...", "build an architecture for...", "we have X devices sending data every Y seconds", "recommend a cluster size for...", "what data model should I use for...", "we need to ingest X GB/day", "migrate from MySQL/PostgreSQL to Apache Doris". Also use for legacy analytics/search/serving stack consolidation prompts even when Apache Doris is not named explicitly, including replacing or migrating from Impala, Kudu, Elasticsearch/ES, Greenplum, Presto, HBase, Hive, Hadoop, Redis, or Lambda-style multi-engine data platforms.
Routes PubNub events to external systems with no code via Events & Actions (E&A). Covers event listeners (Messages, Users, Channels, Push, Memberships), action targets (Webhook, SQS, Kinesis, S3, Kafka, IFTTT, AMQP), filter types (basic vs JSONPath), retry policy, envelopes, and batching. Use when integrating PubNub with Lambda, Kafka, SQS, S3, EventBridge, an analytics pipeline, or any external system.
Comprehensive Java development best practices covering SOLID principles, DRY, Clean Code, Java-specific patterns (Optional, immutability, streams, lambdas), exception handling, collections, concurrency, testing with JUnit 5 and Mockito, code organization, performance optimization, and common anti-patterns. Essential reference for uncle-duke-java agent during code reviews and architecture guidance.
Assess and migrate cross-cloud workloads to Azure with migration reports and code conversion guidance. Supports AWS, GCP, and other providers. WHEN: migrate Lambda to Azure Functions, migrate AWS to Azure, Lambda migration assessment, convert AWS serverless to Azure, migration readiness report, migrate from AWS, migrate from GCP, cross-cloud migration.
Trade execution modelling framework (backtesting analysis only) via Longbridge — covers slippage models (linear / square-root market impact), VWAP/TWAP execution logic, market impact cost estimation (Kyle lambda), volume participation rate (POV) strategy. Helps quant traders build realistic execution assumptions in backtests. Triggers: "执行模型", "滑点模型", "VWAP执行", "TWAP执行", "市场冲击", "执行成本", "成交量参与率", "交易执行", "執行模型", "滑點模型", "VWAP執行", "TWAP執行", "市場冲擊", "執行成本", "交易執行", "execution model", "slippage model", "VWAP", "TWAP", "market impact", "execution cost", "volume participation rate", "Kyle lambda", "square root model", "POV strategy".
Always use when user asks to create, generate, or build an AWS architecture diagram, cloud infrastructure diagram, or system diagram with AWS services. Also activates for draw.io diagrams mentioning AWS services like Lambda, DynamoDB, S3, API Gateway, etc.
AWS cloud services including EC2, EKS, S3, Lambda, RDS, and IAM. Activate for AWS infrastructure, cloud deployment, and Amazon Web Services integration.
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.
Translate an existing Remotion (React-based) video composition into a HyperFrames HTML composition. Use ONLY when the user explicitly asks to port, convert, migrate, translate, or rewrite a Remotion composition as HyperFrames (e.g. "port my Remotion project to HyperFrames"). Do NOT use when (a) authoring a NEW HyperFrames composition (even if A/B-testing a Remotion video); (b) Remotion is mentioned in passing; (c) Remotion code is shared as reference, not for translation; (d) the user wants "the same video as my Remotion one" without explicitly asking to migrate the source — treat as a fresh HyperFrames build. When in doubt, default to the `hyperframes` skill. Detects unsupported patterns (useState, useEffect side effects, async calculateMetadata, third-party React component libraries, `@remotion/lambda`) and recommends the runtime interop escape hatch instead of a lossy translation.
Analyze AWS costs, find savings, manage budgets, evaluate Savings Plans and Reserved Instances, right-size EC2/Lambda/RDS/EBS with Compute Optimizer, look up service pricing, query CUR with Athena, detect cost anomalies, scope costs to billing views, and monitor Free Tier usage. Triggers on: AWS bill, cost analysis, reduce spend, savings plan, reserved instance, right-size, budget alert, cost optimization, pricing, free tier, cost anomaly, CUR, cost audit, billing view, billing view ARN.
Generates a Jupyter notebook that fine-tunes a base model using SageMaker serverless training jobs. Use when the user says "start training", "fine-tune my model", "I'm ready to train", or when the plan reaches the finetuning step. Supports SFT, DPO, and RLVR trainers, including RLVR Lambda reward function creation.