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1,928 results in Identity, Observability, Skills, Sub-Agents · page 10 of 81
Evidence-first automation inventory and overlap audit workflow for ECC. Use when the user wants to know which jobs, hooks, connectors, MCP servers, or wrappers are live, broken, redundant, or missing before fixing anything.
Transform Claude Code into a fully autonomous agent system with persistent memory, scheduled operations, computer use, and task queuing. Replaces standalone agent frameworks (Hermes, AutoGPT) by leveraging Claude Code's native crons, dispatch, MCP tools, and memory. Use when the user wants contin…
Design patterns for building autonomous coding agents. Covers tool integration, permission systems, browser automation, and human-in-the-loop workflows. Use when building AI agents, designing tool APIs, implementing permission systems, or creating autonomous coding assistants.
Autonomous agents are AI systems that can independently decompose goals, plan actions, execute tools, and self-correct without constant human guidance. The challenge isn't making them capable - it's making them reliable. Every extra decision multiplies failure probability. This skill covers agent loops (ReAct, Plan-Execute), goal decomposition, reflection patterns, and production reliability. Key insight: compounding error rates kill autonomous agents. A 95% success rate per step drops to 60% b
Activation-aware weight quantization for 4-bit LLM compression with 3x speedup and minimal accuracy loss. Use when deploying large models (7B-70B) on limited GPU memory, when you need faster inference than GPTQ with better accuracy preservation, or for instruction-tuned and multimodal models. MLSys 2024 Best Paper Award winner.
This skill should be used when the user asks to "pentest AWS", "test AWS security", "enumerate IAM", "exploit cloud infrastructure", "AWS privilege escalation", "S3 bucket testing", "metadata SSRF", "Lambda exploitation", or needs guidance on Amazon Web Services security assessment.
Expert patterns for Azure Functions development including isolated worker model, Durable Functions orchestration, cold start optimization, and production patterns. Covers .NET, Python, and Node.js programming models. Use when: azure function, azure functions, durable functions, azure serverless, function app.
Export existing Azure resources to Infrastructure as Code templates via Azure Resource Graph analysis, Azure Resource Manager API calls, and azure-iac-generator integration. Use this skill when the user asks to export, convert, migrate, or extract existing Azure resources to IaC templates (Bicep, ARM Templates, Terraform, Pulumi).
Central hub for generating Infrastructure as Code (Bicep, ARM, Terraform, Pulumi) with format-specific validation and best practices. Use this skill when the user asks to generate, create, write, or build infrastructure code, deployment code, or IaC templates in any format (Bicep, ARM Templates, Terraform, Pulumi).
Expert backend architect specializing in scalable API design, microservices architecture, and distributed systems. Masters REST/GraphQL/gRPC APIs, event-driven architectures, service mesh patterns, and modern backend frameworks. Handles service boundary definition, inter-service communication, resilience patterns, and observability. Use PROACTIVELY when creating new backend services or APIs.
Backend system architecture and API design specialist. Use PROACTIVELY for greenfield service design, monolith decomposition, API paradigm selection (REST/gRPC/GraphQL), microservice boundaries, database schemas, scalability planning, event-driven architecture, and observability design. This agent focuses on architecture and design decisions — for writing implementation code use the backend-developer agent instead.\n\n<example>\nContext: An existing Rails monolith is growing too large and needs to be split into independent services.\nuser: \"We need to split our Rails monolith into services — where do we start?\"\nassistant: \"I'll analyze the monolith's bounded contexts, data dependencies, and traffic patterns to produce a phased decomposition roadmap with service boundary definitions, API contracts between services, and a strangler-fig migration strategy.\"\n<commentary>\nMonolith decomposition is a core architecture concern: service boundaries, migration sequencing, and managing the transition period without downtime. Use backend-architect for design decisions; use backend-developer to implement the resulting services.\n</commentary>\n</example>\n\n<example>\nContext: A startup is building a new real-time ride-sharing platform from scratch and needs an initial backend architecture.\nuser: \"Design the backend architecture for a real-time ride-sharing platform expected to handle 50k concurrent users at launch.\"\nassistant: \"I'll design a service architecture covering trip lifecycle management, driver matching, real-time location tracking, and payment processing — including API contracts, event-driven communication via Kafka, PostgreSQL + PostGIS schema, caching strategy with Redis, an OpenAPI 3.1 spec for the public API, and an observability plan with OpenTelemetry and SLO thresholds.\"\n<commentary>\nGreenfield service architecture requires upfront decisions on API paradigms, data consistency, scaling approach, and observability before any code is written. This is backend-architect territory.\n</commentary>\n</example>