Menú
Look up any arxiv paper on alphaxiv.org to get a structured AI-generated overview
Instalar con Codex o Claude Copia este prompt, pégalo en Codex, Claude u otro asistente, y deja que revise la página de la skill y la instale por ti.
Basado en la clasificación ocupacional SOC
Orchestrate multi-agent teams with defined roles, task lifecycles, handoff protocols, and review workflows. Use when: (1) Setting up a team of 2+ agents with different specializations, (2) Defining task routing and lifecycle (inbox → spec → build → review → done), (3) Creating handoff protocols between agents, (4) Establishing review and quality gates, (5) Managing async communication and artifact sharing between agents.
Socratic questioning protocol + user communication. MANDATORY for complex requests, new features, or unclear requirements. Includes progress reporting and error handling.
Lighthouse-style efficiency audit for OpenClaw. Scores your instance A+ to F across 6 categories (context injection, cron health, session bloat, config, skills, transcripts). Identifies wasted tokens, bloated sessions, misconfigured crons, and model right-sizing opportunities. Zero dependencies (Python stdlib only).
Make your AI agent learn and improve automatically. Reviews sessions, extracts learnings, updates memory files, and compounds knowledge over time. Set up nightly review loops that make your agent smarter every day.
A multi-agent deliberation hub with 3 core agents and extensible extended agents. Can call user workspace skills when needed.
Automatically logs into email accounts (Gmail, Outlook, QQ Mail, etc.) and generates daily email summaries. Use when the user wants to get a summary of their emails, check important messages, or create daily email digests.
| name | alphaxiv-paper-lookup |
| description | Look up any arxiv paper on alphaxiv.org to get a structured AI-generated overview |
Look up any arxiv paper on alphaxiv.org to get a structured AI-generated overview. This is faster and more reliable than trying to read a raw PDF.
arxiv.org/abs/2401.12345)2401.12345)alphaxiv.org/overview/2401.12345)Parse the paper ID from whatever the user provides:
| Input | Paper ID |
|---|---|
https://arxiv.org/abs/2401.12345 | 2401.12345 |
https://arxiv.org/pdf/2401.12345 | 2401.12345 |
https://alphaxiv.org/overview/2401.12345 | 2401.12345 |
2401.12345v2 | 2401.12345v2 |
2401.12345 | 2401.12345 |
curl -s "https://alphaxiv.org/overview/{PAPER_ID}.md"
This returns the intermediate machine-readable report — a structured, detailed analysis of the paper optimized for LLM consumption. One call, plain markdown, no JSON parsing.
If this returns 404, the report hasn't been generated for this paper yet.
If the report doesn't contain the specific information the user is asking about (e.g. a particular equation, table, or section), fetch the full paper text:
curl -s "https://alphaxiv.org/abs/{PAPER_ID}.md"
This returns the full extracted text of the paper as markdown. Only use this as a fallback — the report is usually sufficient.
If this returns 404, the full text hasn't been processed yet. As a last resort, direct the user to the PDF at https://arxiv.org/pdf/{PAPER_ID}.