Skill UI

Generate images and videos using MuAPI's schema-driven asynchronous API. This skill handles model discovery, request preparation, secure submission, and polling for results, ensuring key protection and efficient media generation workflows.

This skill covers designing multi-agent systems to overcome single-agent context limits. It includes patterns like supervisor/orchestrator, swarm, and hierarchical structures. Key concepts involve context isolation, parallel execution, token economics, and specialization for complex tasks.

Expert guidance for designing distributed NoSQL databases like Cassandra and DynamoDB. Covers query-first modeling, partition key selection, single-table design, denormalization, and avoiding hot partitions in high-scale systems.

Validates 1EdTech/IMS Global OneRoster v1.1 and v1.2 CSV roster sets for manifest integrity, bulk vs delta strictness, foreign key references, and encoding sanitization. Use for pre-flight checks before SIS/Clever/ClassLink ingestion.

A comprehensive workflow bundle designed for system administrators and developers. It guides users through the entire lifecycle of system management and shell scripting across Linux, macOS, and Windows. Key phases include environment assessment, writing robust Bash scripts, advanced debugging techniques, linting with ShellCheck, and rigorous test automation using Bats, ensuring scalable and reliable automation.

A specialized AI agent designed to build and audit business models using Alexander Osterwalder’s comprehensive 9-block framework. It moves beyond mere filling of blocks, focusing on establishing the critical logical 'lock' between core components like Value Propositions, Customer Segments, and Cost Structures. This tool is ideal for initial business architecture design, auditing existing models for internal consistency (e.g., ensuring every key activity has a corresponding cost), or re-validating the core logic during a strategic pivot.

A comprehensive reference for 12 key software architecture patterns including CQRS, Event Sourcing, Saga, Circuit Breaker, Bulkhead, and more. Provides definitions, use cases, implementations, and trade-offs for each pattern.

This skill provides expertise in writing strict POSIX-compliant shell scripts for maximum portability across Unix-like systems. It focuses on shell-agnostic scripting compatible with dash, ash, sh, and bash in POSIX mode. Key areas include defensive programming, portable error handling, safe argument parsing, and cross-platform compatibility. It ensures scripts run on Linux, BSD, Solaris, AIX, and macOS without relying on GNU-specific features or bash extensions.

Privacy Mask is a CLI utility for detecting and redacting sensitive PII in screenshots and images locally. It supports various detection engines including regex and NER to identify IDs, financial data, and API keys. All processing is offline to ensure data security. Users can run dry-runs before masking. Ideal for debugging and sharing images without exposing private credentials or secrets.

This skill covers principles for identifying tasks suited to LLM processing, designing effective project architectures, and iterating rapidly using agent-assisted development. It applies to batch pipelines, multi-agent systems, and interactive applications. Key concepts include task-model fit recognition, manual prototyping, pipeline architecture, file system state management, and structured output design for reliable parsing.

A governance skill designed to secure AI agent tool calls using advanced authorization policies. It implements Cedar policies to control which tools agents can access and under what conditions. Key features include running in 'Shadow mode' for safe observation, 'Enforce mode' for strict blocking, and generating cryptographically signed Ed25519 receipts to provide an immutable, tamper-evident audit trail for every policy decision.

PydanticAI is a robust Python framework that integrates Pydantic's type-checking and validation capabilities into Large Language Models (LLMs). It allows developers to build production-ready AI agents that guarantee structured, validated outputs, moving beyond simple raw strings. Key features include supported tool calling, dependency injection for testability, and multi-model compatibility across major providers like OpenAI, Anthropic, and Gemini. Use this when reliability and correct data structure are paramount.