LLM & Agents

Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch jobs, scheduling tasks, serving APIs with GPU acceleration, or scaling compute-intensive workloads. Triggers on requests for serverless GPU infrastructure, LLM inference, model training/fine-tuning, parallel data processing, cron jobs in the cloud, or deploying Python web endpoints.

Fetch web content from URLs, extract specific topics using subagents, and save structured summaries as markdown. This skill should be used when other skills or workflows need to retrieve and analyze web documentation. Input is URL(s) and topic names, output is detailed markdown summaries saved to specified paths.

This skill should be used when users ask questions about pod network development, pod smart contract language, pod APIs, pod tooling, or pod-specific features. It provides semantic search over the pod network knowledge base to retrieve relevant documentation, code examples, and best practices.

CloudBase Run backend development rules (Function mode/Container mode). Use this skill when deploying backend services that require long connections, multi-language support, custom environments, or AI agent development.

Agent-to-Agent (A2A) protocol implementation patterns for Google ADK - exposing agents via A2A, consuming external agents, multi-agent communication, and protocol configuration. Use when building multi-agent systems, implementing A2A protocol, exposing agents as services, consuming remote agents, configuring agent cards, or when user mentions A2A, agent-to-agent, multi-agent collaboration, remote agents, or agent orchestration.

Code review and audit agent for pull requests and code quality

Validates agent configurations for model selection appropriateness, tool restriction accuracy, focus area quality, and approach completeness. Use when reviewing, auditing, improving, or troubleshooting agents, checking model choice (Sonnet/Haiku/Opus), validating tool permissions, assessing focus area specificity, or ensuring approach methodology is complete. Also triggers when user asks about agent best practices, wants to optimize agent design, needs help with agent validation, or is debugging agent issues.

Design, generate, and fully deploy a stylish, production-ready Retrieval-Augmented Generation (RAG) chatbot embedded directly into any website/project. Uses OpenAI ChatKit widget + Cohere embeddings + Qdrant Cloud + Neon Serverless Postgres + FastAPI backend. Supports selected-text questioning and full conversation history.

Generate atomic implementation tasks from high-level plans, providing coding agents with clear, actionable work items. Only invoke when user explicitly requests to create tasks, break down tasks, generate implementation tasks, or create a task breakdown.

Three-layer verification architecture (CoVe, HSP, RAG) for self-verification, fact-checking, and hallucination prevention

Expert guidance on building production-ready multi-agent AI systems using CrewAI, LangChain, AutoGen, and custom architectures. Use when building agent systems, selecting frameworks, designing multi-agent workflows, debugging agent behavior, or deploying agents to production.

List all active Claude workers and their git worktrees. Shows branch status, commits, and suggests next actions. Use to see what workers are running.

Single-skill vs multi-skill subagent architectures. Use when designing subagents.

Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.

Regenerate the Available Skill Index in AGENTS.md for IDEs without native skill support (Kiro, Gemini, etc.). ONLY use when the user EXPLICITLY asks to "update skill index", "sync agents", "regenerate index", or "update AGENTS.md". Do NOT auto-invoke after creating/modifying skills - Claude Code has native skill support and does not need this.

Create Amp-native skills with proper SKILL.md format, optional bundled tools, MCP servers, and directory structure. Use this skill as the default skill creation skill, unless specifically told to create a generic or Claude code-specific skill. Activates with phrases like "create a skill", "new skill", "skill for amp", or when user wants bundled tools, mcp.json servers, or toolbox-compatible skills.

Develop AI agents, tools, and workflows with Mastra v1 Beta and Hono servers. This skill should be used when creating Mastra agents, defining tools with Zod schemas, building workflows with step data flow, setting up Hono API servers with Mastra adapters, or implementing agent networks. Keywords: mastra, hono, agent, tool, workflow, AI, LLM, typescript, API, MCP.

Creates, analyzes, updates, and optimizes prompts using Claude 4.5 best practices, guardrails, context management, and prompt engineering patterns. Use when user asks how to write effective prompts, explaining prompt engineering techniques, understanding Claude 4.5 best practices, describing prompt patterns and structures, creating new prompts, evaluating existing prompts for improvements, determining if current logic should be extracted to prompts, identifying outdated prompt techniques, optimizing context usage, implementing guardrails, or when user mentions "prompt engineering", "hallucinations", "context optimization", "prompt caching", "chain-of-thought", or asks if logic should become a prompt.

Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.

Applies Anthropic's official brand colors and typography to any sort of artifact that may benefit from having Anthropic's look-and-feel. Use it when brand colors or style guidelines, visual formatting, or company design standards apply.