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itsmostafa

itsmostafa

27 Skills published on GitHub.

agents

Patterns and architectures for building AI agents and workflows with LLMs. Use when designing systems that involve tool use, multi-step reasoning, autonomous decision-making, or orchestration of LLM-driven tasks.

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context-engineering

Strategies for managing LLM context windows effectively in AI agents. Use when building agents that handle long conversations, multi-step tasks, tool orchestration, or need to maintain coherence across extended interactions.

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api-gateway

AWS API Gateway for REST and HTTP API management. Use when creating APIs, configuring integrations, setting up authorization, managing stages, implementing rate limiting, or troubleshooting API issues.

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bedrock

AWS Bedrock foundation models for generative AI. Use when invoking foundation models, building AI applications, creating embeddings, configuring model access, or implementing RAG patterns.

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cloudformation

AWS CloudFormation infrastructure as code for stack management. Use when writing templates, deploying stacks, managing drift, troubleshooting deployments, or organizing infrastructure with nested stacks.

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cloudwatch

AWS CloudWatch monitoring for logs, metrics, alarms, and dashboards. Use when setting up monitoring, creating alarms, querying logs with Insights, configuring metric filters, building dashboards, or troubleshooting application issues.

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cognito

AWS Cognito user authentication and authorization service. Use when setting up user pools, configuring identity pools, implementing OAuth flows, managing user attributes, or integrating with social identity providers.

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dynamodb

AWS DynamoDB NoSQL database for scalable data storage. Use when designing table schemas, writing queries, configuring indexes, managing capacity, implementing single-table design, or troubleshooting performance issues.

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ec2

AWS EC2 virtual machine management for instances, AMIs, and networking. Use when launching instances, configuring security groups, managing key pairs, troubleshooting connectivity, or automating instance lifecycle.

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ecs

AWS ECS container orchestration for running Docker containers. Use when deploying containerized applications, configuring task definitions, setting up services, managing clusters, or troubleshooting container issues.

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eks

AWS EKS Kubernetes management for clusters, node groups, and workloads. Use when creating clusters, configuring IRSA, managing node groups, deploying applications, or integrating with AWS services.

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eventbridge

AWS EventBridge serverless event bus for event-driven architectures. Use when creating rules, configuring event patterns, setting up scheduled events, integrating with SaaS, or building cross-account event routing.

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iam

AWS Identity and Access Management for users, roles, policies, and permissions. Use when creating IAM policies, configuring cross-account access, setting up service roles, troubleshooting permission errors, or managing access control.

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lambda

AWS Lambda serverless functions for event-driven compute. Use when creating functions, configuring triggers, debugging invocations, optimizing cold starts, setting up event source mappings, or managing layers.

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rds

AWS RDS relational database service for managed databases. Use when provisioning databases, configuring backups, managing replicas, troubleshooting connectivity, or optimizing performance.

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s3

AWS S3 object storage for bucket management, object operations, and access control. Use when creating buckets, uploading files, configuring lifecycle policies, setting up static websites, managing permissions, or implementing cross-region replication.

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secrets-manager

AWS Secrets Manager for secure secret storage and rotation. Use when storing credentials, configuring automatic rotation, managing secret versions, retrieving secrets in applications, or integrating with RDS.

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sns

AWS SNS notification service for pub/sub messaging. Use when creating topics, managing subscriptions, configuring message filtering, sending notifications, or setting up mobile push.

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sqs

AWS SQS message queue service for decoupled architectures. Use when creating queues, configuring dead-letter queues, managing visibility timeouts, implementing FIFO ordering, or integrating with Lambda.

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step-functions

AWS Step Functions workflow orchestration with state machines. Use when designing workflows, implementing error handling, configuring parallel execution, integrating with AWS services, or debugging executions.

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lora

Parameter-efficient fine-tuning with Low-Rank Adaptation (LoRA). Use when fine-tuning large language models with limited GPU memory, creating task-specific adapters, or when you need to train multiple specialized models from a single base.

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mlx

Running and fine-tuning LLMs on Apple Silicon with MLX. Use when working with models locally on Mac, converting Hugging Face models to MLX format, fine-tuning with LoRA/QLoRA on Apple Silicon, or serving models via HTTP API.

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prompt-engineering

Crafting effective prompts for LLMs. Use when designing prompts, improving output quality, structuring complex instructions, or debugging poor model responses.

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pytorch

Building and training neural networks with PyTorch. Use when implementing deep learning models, training loops, data pipelines, model optimization with torch.compile, distributed training, or deploying PyTorch models.

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qlora

Memory-efficient fine-tuning with 4-bit quantization and LoRA adapters. Use when fine-tuning large models (7B+) on consumer GPUs, when VRAM is limited, or when standard LoRA still exceeds memory. Builds on the lora skill.

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rlhf

Understanding Reinforcement Learning from Human Feedback (RLHF) for aligning language models. Use when learning about preference data, reward modeling, policy optimization, or direct alignment algorithms like DPO.

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transformers

Loading and using pretrained models with Hugging Face Transformers. Use when working with pretrained models from the Hub, running inference with Pipeline API, fine-tuning models with Trainer, or handling text, vision, audio, and multimodal tasks.

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