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Found 1,266 Skills
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.
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.
MUST READ before writing or modifying ADK agent code. ADK API quick reference for Python — agent types, tool definitions, orchestration patterns, callbacks, and state management. Includes an index of all ADK documentation pages. Do NOT use for creating new projects (use adk-scaffold).
TensorLake SDK for building agentic workflows, sandboxed code execution, and document parsing/extraction. Use when the user mentions tensorlake, or asks about TensorLake APIs/docs/capabilities. Also use when the user is building AI agents or agentic applications that need serverless workflow orchestration (parallel map/reduce DAGs), sandboxed execution of LLM-generated code, or document parsing, structured extraction, and OCR from PDFs/images. Works with any LLM provider (OpenAI, Anthropic), agent framework (LangChain, CrewAI, LlamaIndex), database, or API as the infrastructure layer.
Expert full-cycle enterprise sales strategist for B2B SaaS. Use when planning sales strategy, pipeline management, deal progression, account planning, competitive displacement, or territory optimization. Covers multi-threading, executive engagement, champion development, buying committee navigation, and complex deal orchestration. Use for enterprise selling, account expansion, land-and-expand, and quota attainment.
Patterns and architectures for building AI agents and workflows with LLMs. Use when designing systems that involve tool use, multi-step reasoning, autonomous decision-making, or orchestration of LLM-driven tasks.
Repo Updater - Multi-repo synchronization with AI-assisted review orchestration. Parallel sync, agent-sweep for dirty repos, ntm integration, git plumbing. 17K LOC Bash CLI.
Google Gemini CLI orchestration for AI-assisted development. Capabilities: second opinion/cross-validation, real-time web search (Google Search), codebase architecture analysis, parallel code generation, code review from different perspective. Actions: query, search, analyze, generate, review with Gemini. Keywords: Gemini CLI, second opinion, cross-validation, Google Search, web research, current information, parallel AI, code review, architecture analysis, gemini prompt, AI comparison, real-time search, alternative perspective, code generation. Use when: needing second AI opinion, searching current web information, analyzing codebase architecture, generating code in parallel, getting alternative code review, researching current events/docs.
Design, implement, and refactor Ports & Adapters systems with clear domain boundaries, dependency inversion, and testable use-case orchestration across TypeScript, Java, Kotlin, and Go services.
SPEC workflow orchestration with EARS format, requirement clarification, and Plan-Run-Sync integration for MoAI-ADK development methodology
Skill for Tauri 2.0 and Rust backend development in LocalCowork. Use when working on the Rust backend, Tauri IPC commands, frontend-backend communication, Tauri permissions/capabilities, the application shell, or the Agent Core modules (ConversationManager, ToolRouter, MCP Client, Inference Client, ContextWindowManager). MANDATORY TRIGGERS: "Tauri", "Rust backend", "IPC command", "tauri.conf.json", "Cargo.toml", "capabilities", "agent core", "tool router", "conversation manager", "inference client", "MCP client", "context window", or anything related to the desktop application shell or the Rust-side orchestration layer.
Senior End-to-End (E2E) Test Architect for 2026. Specialized in Playwright orchestration, visual regression testing, and high-performance CI/CD sharding. Expert in building resilient, auto-waiting test suites using the Page Object Model (POM), automated accessibility auditing (Axe-core), and deep-trace forensic debugging.