The package manager for agent skills and context

This skill enables Claude to validate Cross-Origin Resource Sharing (CORS) policies. It uses the cors-policy-validator plugin to analyze CORS configurations and identify potential security vulnerabilities. Use this skill when the user requests to "validate CORS policy", "check CORS configuration", "analyze CORS headers", or asks about "CORS security". It helps ensure that CORS policies are correctly implemented, preventing unauthorized cross-origin requests and protecting sensitive data.

This skill enables Claude to analyze and optimize system throughput. It is triggered when the user requests throughput analysis, performance improvements, or bottleneck identification. The skill uses the `throughput-analyzer` plugin to assess request throughput, data throughput, concurrency limits, queue processing, and resource saturation. Use this skill when the user mentions "analyze throughput", "optimize performance", "identify bottlenecks", or asks about system capacity. It helps determine limiting factors and evaluate scaling strategies.

This skill enables Claude to monitor and analyze CPU usage patterns within applications. It helps identify CPU hotspots, analyze algorithmic complexity, and detect blocking operations. Use this skill when the user asks to "monitor CPU usage", "optimize CPU performance", "analyze CPU load", or "find CPU bottlenecks". It assists in identifying inefficient loops, regex performance issues, and provides optimization recommendations. This skill is designed for improving application performance by addressing CPU-intensive operations.

This skill empowers Claude to build reusable Terraform modules based on user specifications. It leverages the terraform-module-builder plugin to generate production-ready, well-documented Terraform module code, incorporating best practices for security, scalability, and multi-platform support. Use this skill when the user requests to create a new Terraform module, generate Terraform configuration, or needs help structuring infrastructure as code using Terraform. The trigger terms include "create Terraform module," "generate Terraform configuration," "Terraform module code," and "infrastructure as code."

This skill enables Claude to detect infrastructure drift from a desired state. It uses the `drift-detect` command to identify discrepancies between the current infrastructure configuration and the intended configuration, as defined in infrastructure-as-code tools like Terraform. Use this skill when the user asks to check for infrastructure drift, identify configuration changes, or ensure that the current infrastructure matches the desired state. It is particularly useful in DevOps workflows for maintaining infrastructure consistency and preventing configuration errors. Trigger this skill when the user mentions "drift detection," "infrastructure changes," "configuration drift," or requests a "drift report."

This skill enables Claude to generate Helm charts for Kubernetes applications. It should be used when the user requests the creation of a new Helm chart, the modification of an existing chart, or assistance with packaging and deploying Kubernetes applications using Helm. The skill is triggered by requests that mention "Helm chart", "Kubernetes deployment", "package application for Kubernetes", or similar phrases related to Helm and Kubernetes. It helps streamline the process of creating and managing Kubernetes deployments.

This skill allows Claude to construct and configure neural network architectures using the neural-network-builder plugin. It should be used when the user requests the creation of a new neural network, modification of an existing one, or assistance with defining the layers, parameters, and training process. The skill is triggered by requests involving terms like "build a neural network," "define network architecture," "configure layers," or specific mentions of neural network types (e.g., "CNN," "RNN," "transformer").

This skill enables Claude to provide interpretability and explainability for machine learning models. It is triggered when the user requests explanations for model predictions, insights into feature importance, or help understanding model behavior. The skill leverages techniques like SHAP and LIME to generate explanations. It is useful when debugging model performance, ensuring fairness, or communicating model insights to stakeholders. Use this skill when the user mentions "explain model", "interpret model", "feature importance", "SHAP values", or "LIME explanations".

This skill trains machine learning models using automated workflows. It analyzes datasets, selects appropriate model types (classification, regression, etc.), configures training parameters, trains the model with cross-validation, generates performance metrics, and saves the trained model artifact. Use this skill when the user requests to "train" a model, needs to evaluate a dataset for machine learning purposes, or wants to optimize model performance. The skill supports common frameworks like scikit-learn.

This skill should be used when the user asks to "understand context", "explain context windows", "design agent architecture", "debug context issues", "optimize context usage", or discusses context components, attention mechanics, progressive disclosure, or context budgeting. Provides foundational understanding of context engineering for AI agent systems.

Suggest better variable, function, and class names based on context and conventions.

Use when building RAG systems, vector databases, or knowledge-grounded AI applications requiring semantic search, document retrieval, or context augmentation.