skills

Look up any arxiv paper on alphaxiv.org to get a structured AI-generated overview. Use this skill whenever the user shares an arxiv URL (arxiv.org/abs/...), an arxiv paper ID (e.g. 2401.12345), an alphaxiv URL, or asks you to explain, summarize, or analyze a research paper by ID or link. This is faster and more reliable than reading a raw PDF. Trigger proactively even when the user says things like "can you read this paper", "summarize this arxiv link", or "what does this paper say".

Design a codebase to work well with AI coding agents (Claude Code, Codex, Cursor, Aider). Use this skill when the user is starting or retrofitting a repository for agents, asking what AGENTS.md or CLAUDE.md should contain, designing project structure for AI assistance, asking about harness engineering, saying an agent keeps making the same mistake, asking how to make agents reliable on long-running tasks, or trying to make their codebase legible to coding agents. Trigger on indirect phrasings too. Examples include "set up my project for Claude Code", "make my repo agent-friendly", "stop my agent from doing X", "best architecture for AI-generated code", or "the agent keeps reinventing utilities". Use proactively when the user describes building a project with agent assistance and has not yet thought about scaffolding, AGENTS.md, custom linters, hooks, or feedback loops.

Use this skill whenever you need to elicit context, preferences, constraints, or choices from the user before proceeding. This is the default mechanism for all user-facing elicitation. The skill picks the best available tool, choosing a rich inline form (with cards, free-text, file uploads, multi-select, dates, sliders, and multi-round flows) when the visualizer is loaded, falling back to ask_user_input_v0 for choice questions, and prose for everything else. Trigger this any time you would otherwise ask a clarifying question in prose, call ask_user_input_v0 directly, or write a numbered list of questions for the user. This includes requests where intent is underspecified, decisions between options, gathering preferences for a recommendation, confirming assumptions before producing a deliverable, or collecting form-like data. Replaces ask_user_input_v0 as the default elicitation mechanism.

Build Python workflows and agents using the Claude Agent SDK (claude-agent-sdk). Use this skill whenever the user wants to create, design, or debug agent workflows, multi-agent systems, automation scripts, or any Python code that uses the Claude Agent SDK (formerly Claude Code SDK). Trigger on mentions of: "agent sdk", "claude-agent-sdk", "claude_agent_sdk", "query()", "ClaudeSDKClient", "subagents", "AgentDefinition", "agent workflow", "multi-agent", "claude code sdk", or any request to build an autonomous agent that reads files, runs commands, edits code, or orchestrates tasks programmatically. Also trigger when the user asks about architecting agent systems, choosing between SDK patterns, or integrating custom tools/hooks/MCP servers with the Agent SDK. Even if the user just says "build me an agent" or "automate this with Claude", use this skill.

Help the user understand and internalize complex topics through a structured pedagogical approach calibrated to how they learn. Triggers on "explain X to me", "help me understand Y", "what is Z and why does it matter", "break down this concept", "teach me about W", "how does X work", "walk me through Y", "I keep hearing about X but do not really get it", "what is the intuition behind X", or any request where the user wants to build a mental model of something they do not yet understand. Also trigger when the user asks conceptual "why" questions about systems, architectures, or paradigms. Do NOT trigger on simple factual lookups ("when was X founded"), summarization requests, problem-solving or decision-making (use the solve skill), or requests where the user already understands the topic and wants information organized.