Skill UI

This skill enables building production-ready LLM applications, advanced RAG systems, and intelligent agents. It covers vector search, multimodal AI, agent orchestration, and enterprise integrations. Learn to design architectures, optimize embeddings, ensure safety, and deploy models at scale using frameworks like LangChain and vector databases.

This toolkit provides six production-ready AI engineering workflows including prompt evaluation, context budget planning, RAG pipeline design, agent security audits, evaluation harness building, and product sense coaching. It transforms AI coding assistants into senior engineering partners with structured methodologies, quantitative scoring, and checklists for consistent results in LLM system optimization and security.

Set up effective alerting rules, configure on-call rotations, and manage incident response workflows for production systems. Covers Prometheus alerting, Alertmanager routing, PagerDuty integration, and alert design best practices.

This skill helps design event-driven architectures, webhook systems, and API chaining flows. It covers integration patterns between services, ETL pipelines, and Pub/Sub topics. You can use it for API composition strategies, Saga patterns for distributed transactions, and Outbox patterns for reliable event publishing. It ensures robust system design with idempotency, retry logic, and circuit breakers.

This skill provides expert-level review and guidance for complex software systems. It covers modern architecture patterns like microservices, event-driven design, and clean architecture. The architect evaluates scalability, resilience, security, and maintainability. It helps ensure architectural integrity and compliance with best practices across distributed systems and cloud-native environments.

This framework provides a comprehensive, structured approach for making critical architectural decisions. It guides users through requirements analysis, detailed trade-off evaluation, and documenting decisions using Architecture Decision Records (ADRs). It is essential when analyzing or designing complex system architectures to ensure simplicity, robustness, and maintainability.

This skill provides expertise in proven backend architectural patterns, including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design (DDD). It guides users in building highly maintainable, testable, and scalable systems. Use it when designing new services, refactoring complex monoliths, establishing team standards, or planning microservice decompositions. It emphasizes defining clear boundaries and handling complex, durable workflows.

This skill designs the structural foundation of a system, including data models, API contracts, and file organization. It ensures architectural decisions are documented and justified before implementation. Used by System Architects to create blueprints for developers to follow during coding.

Atlas Ledger is a critical companion designed to provide lasting 'memory' to project contracts. It automatically processes detected deviations or 'drift' (e.g., from audits or reviews) and distills these instances into formal, actionable contract clauses (WHEN/DON'T/INSTEAD). These clauses are written to a persistent project memory file, Atlas.md. This mechanism ensures that lessons learned from failure are systematically captured, allowing future contract cycles to incorporate these rules, thereby strengthening overall project governance and reliability.

Master secure authentication and authorization implementation using industry-standard patterns. Covers user login systems, REST/GraphQL API security, OAuth2, SSO, session management, and RBAC design. Includes guidance on token lifecycle, secrets storage, and threat modeling to protect resource access boundaries effectively.

Design patterns for building autonomous coding agents, including tool calling APIs, permission systems, browser automation, and human-in-the-loop workflows. Inspired by Cline and OpenAI Codex, this skill provides guidance for creating efficient and safe AI agents.

This skill covers AWS development focusing on infrastructure automation and cloud architecture patterns. It provides guidance and best practices for building scalable cloud solutions using AWS services. Suitable for tasks involving infrastructure as code, resource management, and architectural design within the AWS ecosystem.