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Found 1,267 Skills
Use to execute an implementation plan with automatic sequential/parallel orchestration - handles worktree verification, resume detection, phase dispatch, and quality verification
Multi-instance (Multi-Agent) orchestration workflow for deep research: Split a research goal into parallel sub-goals, run child processes in the default `workspace-write` sandbox using Codex CLI (`codex exec`); prioritize installed skills for networking and data collection, followed by MCP tools; aggregate sub-results with scripts and refine them chapter by chapter, and finally deliver "finished report file path + key conclusions/recommendations summary". Applicable to: systematic web/data research, competitor/industry analysis, batch link/dataset shard retrieval, long-form writing and evidence integration, or scenarios where users mention "deep research/Deep Research/Wide Research/multi-Agent parallel research/multi-process research".
Expert-level Apache Airflow orchestration, DAGs, operators, sensors, XComs, task dependencies, and scheduling
Implement real-time Hotwire behavior: Turbo Streams over WebSocket/SSE, custom stream actions, inline stream tags, live list updates, and cross-tab state synchronization. Prefer this skill when the core problem is push-based updates or stream action orchestration. Use hwc-navigation-content for pull-based pagination/tab/lazy-navigation flows, hwc-forms-validation for form lifecycle and validation, hwc-media-content for media upload/playback behavior, hwc-ux-feedback for generic loading/progress/transitions, and hwc-stimulus-fundamentals for non-stream Stimulus fundamentals.
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.
Build single-agent and multi-agent systems using Google's Agent Development Kit (ADK) in Python, Java, Go, or TypeScript. Use when creating AI agents with ADK, designing multi-agent architectures, implementing agent tools, configuring agent callbacks, managing agent state, orchestrating sequential/parallel/loop agent workflows, or when the user mentions ADK, google-adk, google agent development kit, agentic AI with Gemini, or agent orchestration with Google tools. Also use when setting up ADK projects, writing agent tests, deploying agents, or integrating MCP tools with ADK.
Workflow orchestration expert using Temporal.io for durable executionUse when "temporal workflow, durable execution, saga pattern, workflow orchestration, long running process, activity retry, workflow versioning, temporal, workflows, durable-execution, saga, orchestration, activities, long-running, ml-memory" mentioned.
Provides comprehensive Oracle Cloud Infrastructure (OCI) guidance including compute instances, networking (VCN, load balancers, VPN), storage (block, object, file), database services (Autonomous Database, MySQL, NoSQL), container orchestration (OKE), identity and access management (IAM), resource management, cost optimization, and infrastructure as code (Terraform OCI provider, Resource Manager). Produces infrastructure code, deployment scripts, configuration guides, and architectural diagrams. Use when designing OCI architecture, provisioning cloud resources, migrating to Oracle Cloud, implementing OCI security, setting up OCI databases, deploying containerized applications on OKE, managing OCI resources, or when users mention "Oracle Cloud", "OCI", "Autonomous Database", "VCN", "OKE", "OCI Terraform", "Resource Manager", "Oracle Cloud Infrastructure", or "OCI migration".
Guides development with SAP AI Core and SAP AI Launchpad for enterprise AI/ML workloads on SAP BTP. Use when: deploying generative AI models (GPT, Claude, Gemini, Llama), building orchestration workflows with templating/filtering/grounding, implementing RAG with vector databases, managing ML training pipelines with Argo Workflows, configuring content filtering and data masking for PII protection, using the Generative AI Hub for prompt experimentation, or integrating AI capabilities into SAP applications. Covers service plans (Free/Standard/Extended), model providers (Azure OpenAI, AWS Bedrock, GCP Vertex AI, Mistral, IBM), orchestration modules, embeddings, tool calling, and structured outputs.
Designs multi-agent system architectures with orchestration patterns, tool schemas, and performance evaluation. Use when building AI agent systems, designing agent workflows, creating tool schemas, or evaluating agent performance.
RFC-driven multi-agent DAG execution pattern with quality gates, merge queues, and work unit orchestration.
OmniStudio Integration Procedure creation and validation with 110-point scoring. Use when building server-side process orchestrations that combine Data Mapper actions, Apex Remote Actions, HTTP callouts, and conditional logic. TRIGGER when: user creates Integration Procedures, adds Data Mapper steps, configures Remote Actions, or reviews existing IP configurations. DO NOT TRIGGER when: building OmniScripts (use sf-industry-commoncore-omniscript), creating Data Mappers directly (use sf-industry-commoncore-datamapper), or analyzing cross-component dependencies (use sf-industry-commoncore-omnistudio-analyze).