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Found 3,519 Skills
Run and control interactive CLI sessions for AI agents. Handles TUI prompts (select lists, checkboxes, confirms), persistent shell state, and long-running processes. Use when you need to execute terminal commands, respond to interactive prompts, navigate scaffolding wizards like create-vue or create-vite, or manage dev servers.
Best practices for prompt engineering and context engineering for Coding Agent prompts
Best practices for using agent-browser with Kernel cloud browsers. Use when automating websites with agent-browser -p kernel, dealing with bot detection, iframes, login persistence, or needing to find Kernel browser session IDs and live view URLs.
Knowledge base for designing, reviewing, and linting agentic AI infrastructure. Use when: (1) designing a new agentic system and need to choose patterns, (2) reviewing an existing agentic architecture ADR or design doc for gaps/risks, (3) applying the lint script to an ADR markdown file to get structured findings, (4) looking up a specific agentic pattern (prompt chaining, routing, parallelization, reflection, tool use, planning, multi-agent collaboration, memory management, learning/adaptation, MCP, goal setting, exception handling, HITL, RAG, A2A, resource optimization, reasoning techniques, guardrails, evaluation, prioritization, exploration/discovery). All rules and guidance are grounded in the PDF "Agentic Design Patterns" (482 pages).
Use this skill when the user wants any MCP-capable agent or IDE assistant to interact with Google ADK agents through the adk-agent-extension MCP server. Trigger for requests like wiring ADK tools into Codex/Claude Code/Cursor/Cline/Gemini, registering a stdio MCP server, listing ADK servers/agents, creating sessions, and chatting with ADK agents.
Use when generating multiple curriculum-aligned concept files in parallel (5+ concepts) - researches curriculum, creates concept list, spawns parallel generation agents, orchestrates review loop until all pass
Implement feature tasks using AI agents in logical batches, track completion status, identify blockers, and manage task handoffs. Use when you have an execution sequence and need AI agents to build tasks while maintaining progress tracking.
Sequence tasks from a feature breakdown into an optimal execution order, identify dependencies and parallelization opportunities, and create an agent-ready execution sequence. Use when you have a feature breakdown and need to determine the correct order to build tasks and which can run in parallel.
Sets up Claude Code agent teams with role-based composition. Use when creating dev teams, defining team roles, or organizing multi-agent collaboration. Do NOT use for single sub-agent creation (use agent-creator instead).
Generates project context (code structure + architecture intent). Use when starting sessions, understanding codebase structure, onboarding to a project, after major refactoring, or delegating complex work to agents.
Generates custom Claude Code subagents with specialized expertise. Activates when user wants to create a subagent, specialized agent, or task-specific AI assistant. Creates properly formatted .md files with YAML frontmatter, suggests tool restrictions and model selection, generates effective system prompts. Use when user mentions "create subagent", "new agent", "specialized agent", "task-specific agent", or wants isolated context for domain-specific work.
Validate agent skills for correctness, readability, workflow clarity, and isolation, ensuring they can be installed independently without dependencies on other skills.