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Found 1,195 Skills
Build automated AI workflows combining multiple models and services. Patterns: batch processing, scheduled tasks, event-driven pipelines, agent loops. Tools: inference.sh CLI, bash scripting, Python SDK, webhook integration. Use for: content automation, data processing, monitoring, scheduled generation. Triggers: ai automation, workflow automation, batch processing, ai pipeline, automated content, scheduled ai, ai cron, ai batch job, automated generation, ai workflow, content at scale, automation script, ai orchestration
SPEC workflow orchestration with EARS format requirements, acceptance criteria, and Plan-Run-Sync integration for MoAI-ADK development methodology. Use when creating SPEC documents, writing EARS requirements, defining acceptance criteria, planning features, or orchestrating the /moai plan phase. Do NOT use for implementation (use moai-workflow-ddd instead) or documentation generation (use moai-workflow-project instead).
Azure AI Projects SDK for .NET. High-level client for Azure AI Foundry projects including agents, connections, datasets, deployments, evaluations, and indexes. Use for AI Foundry project management, versioned agents, and orchestration. Triggers: "AI Projects", "AIProjectClient", "Foundry project", "versioned agents", "evaluations", "datasets", "connections", "deployments .NET".
Docker and Docker Compose patterns for local development, container security, networking, volume strategies, and multi-service orchestration.
Query decomposition and multi-source search orchestration. Breaks natural language questions into targeted searches per source, translates queries into source-specific syntax, ranks results by relevance, and handles ambiguity and fallback strategies.
Google Agent Development Kit (ADK) for Python. Capabilities: AI agent building, multi-agent systems, workflow agents (sequential/parallel/loop), tool integration (Google Search, Code Execution), Vertex AI deployment, agent evaluation, human-in-the-loop flows. Actions: build, create, deploy, evaluate, orchestrate AI agents. Keywords: Google ADK, Agent Development Kit, AI agent, multi-agent system, LlmAgent, SequentialAgent, ParallelAgent, LoopAgent, tool integration, Google Search, Code Execution, Vertex AI, Cloud Run, agent evaluation, human-in-the-loop, agent orchestration, workflow agent, hierarchical coordination. Use when: building AI agents, creating multi-agent systems, implementing workflow pipelines, integrating LLM agents with tools, deploying to Vertex AI, evaluating agent performance, implementing approval flows.
Multiagent AI system for scientific research assistance that automates research workflows from data analysis to publication. This skill should be used when generating research ideas from datasets, developing research methodologies, executing computational experiments, performing literature searches, or generating publication-ready papers in LaTeX format. Supports end-to-end research pipelines with customizable agent orchestration.
Build LLM applications with LangChain and LangGraph. Use when creating RAG pipelines, agent workflows, chains, or complex LLM orchestration. Triggers on LangChain, LangGraph, LCEL, RAG, retrieval, agent chain.
Guides agents in compiling and packaging C/C++ source code into dynamic or static libraries (Code Assets) using Dart's Native Assets hook system (via hook/build.dart and hook/link.dart utilizing package:hooks and package:native_toolchain_c). Use when a user asks to: 'setup native assets', 'compile C/C++ source code', 'bundle dynamic libraries', 'build native C code', 'link native assets', 'implement build.dart or link.dart hooks', or 'integrate C/C++ interop in Dart/Flutter'. Helps agents avoid manual toolchain orchestration and configures secure hash-validated binary downloads or advanced linker tree-shaking with package:record_use mapping.
Create and configure AI agents, upload files for RAG, manage MCP servers, and handle agent memories using the Cargo CLI. Use when the user wants to create or update agents, upload knowledge base files, connect MCP tool servers, or manage agent memories. For sending messages to agents, use the cargo-orchestration skill instead.
Clari Copilot (formerly Wingman) platform help — conversation intelligence with real-time battlecards, live coaching during calls, AI call summaries, coaching scorecards, gametapes, deal intelligence, and CRM auto-update within Clari's revenue orchestration platform. Use when setting up Clari Copilot for a sales team, battlecards popping up too often during calls, meeting bot not joining or joining late, Clari Copilot vs Gong pricing or features, Clari API integration for forecast export or data ingestion, CRM field mapping not syncing correctly, coaching scorecards not scoring accurately, or evaluating Clari Copilot for enterprise conversation intelligence. Do NOT use for picking a note-taker across vendors (use /sales-note-taker) or building a coaching program (use /sales-coaching).
Implement cross-cutting Hotwire UX feedback patterns: loading states, busy indicators, progress bars, optimistic UI, render interception, and view/page transitions. Prefer this skill when the core goal is perceived performance and user feedback, independent of a single feature domain. Use hwc-forms-validation for form correctness and validation behavior, hwc-navigation-content for navigation/history/cache mechanics, hwc-realtime-streaming for push/stream orchestration, hwc-media-content for media-specific behavior, and hwc-stimulus-fundamentals for base Stimulus API questions.