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axiom-distributed-science公理分布式科学

Agent Skill

axiom-distributed-science 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

9,243

周安装

393

GitHub Stars

公开资料未说明

下载量

3,238
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:axiom-distributed-science(公理分布式科学)
来源仓库:https://github.com/pyhelix/axiom-distributed-science
安装命令:
openclaw skills install axiom-distributed-science
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install axiom-distributed-science

简介

从 Axiom 分布式志愿者计算网络(超过 113 个主机、129 个 GPU、超过 42K 个结果)查询科学发现、实验和论文。

SKILL.md

name
axiom-distributed-science
description
Query scientific findings, experiments, and papers from the Axiom distributed volunteer computing network (113+ hosts, 129 GPUs, 42K+ results).
version
1.1.0
metadata
openclaw
requires
bins
emoji
🔬
homepage
https://axiom.heliex.net

Axiom Distributed Science

Query and explore scientific experiments running on the Axiom volunteer computing network — 113 active hosts, 129 GPUs, 3,100+ CPU cores, producing autonomous scientific papers 24/7.

What is Axiom?

Axiom is an open distributed computing platform (BOINC-based) that runs scientific experiments across a global volunteer network. Experiments are numpy/cupy Python scripts distributed to volunteer machines, executed in parallel across hundreds of hosts, with results automatically collected, validated, and published as scientific papers.

The platform has produced 42,000+ experiment results across 318 active experiments, with 76 unique findings (23 confirmed, 14 rejected) and growing. Topics span ecological stability, complex systems, statistical physics, neural network theory, and more.

Website: https://axiom.heliex.net Scientific Findings: https://axiom.heliex.net/scientific_findings.php Example Paper: https://axiom.heliex.net/reactivity_localization_paper.pdf

JSON API Endpoints

All endpoints return JSON with CORS enabled.

GET /api/stats.php — Project Statistics

Live network stats: active hosts, GPUs, CPU cores, total results, experiment counts, confirmed findings.

curl https://axiom.heliex.net/api/stats.php

Returns:

{
  "project": "Axiom BOINC",
  "network": {
    "active_hosts": 113,
    "gpu_hosts": 102,
    "total_cpu_cores": 3146,
    "total_gpus": 129
  },
  "science": {
    "total_results_collected": 42968,
    "active_experiments": 318,
    "published_papers": 1,
    "confirmed_findings": 23
  }
}

GET /api/findings.php — Scientific Findings

Browse validated scientific findings with statistical details. Filter by status and limit results.

# All findings (default limit 20)
curl https://axiom.heliex.net/api/findings.php

# Only confirmed findings
curl "https://axiom.heliex.net/api/findings.php?status=confirmed&limit=10"

# Only rejected hypotheses
curl "https://axiom.heliex.net/api/findings.php?status=rejected&limit=5"

Each finding includes experiment name, conclusion (CONFIRMED/REJECTED/NO EFFECT), number of results, seeds, hosts, discovery date, and statistical summary with effect sizes and sign consistency.

GET /api/experiments.php — Active Experiments

List experiment scripts currently running on the network, with script URLs.

curl "https://axiom.heliex.net/api/experiments.php?limit=10"

Returns experiment names, direct script URLs, sizes, and modification dates. Script source code is publicly readable.

GET /api/papers.php — Published Papers

List published research papers generated from experiment results.

curl https://axiom.heliex.net/api/papers.php

Returns paper titles, PDF URLs, sizes, and publication dates.

POST /api/suggest.php — Suggest an Experiment

Submit a plain-text experiment idea for the Axiom team to review. No code allowed — just describe what you'd like to see studied.

curl -X POST https://axiom.heliex.net/api/suggest.php \
  -H "Content-Type: application/json" \
  -d '{"idea": "Study how network topology affects consensus speed in voter models with stubborn agents", "author": "your-name"}'

Returns:

{
  "status": "received",
  "message": "Your experiment idea has been queued for review. Thank you.",
  "id": "20260309_060157_b03cba"
}

Constraints:

  • Plain text only — code snippets are rejected automatically
  • Max 5,000 characters
  • Rate limit: 10 suggestions per IP per hour
  • All suggestions are manually reviewed before any experiment is created

Example Findings

Recent confirmed discoveries from the network:

  • Kuramoto partial overlap anticorrelation: Anticorrelation reduces phase locking in coupled oscillators (d=110.07, 100% sign-consistent across 266 seeds)
  • Standard map FTLE transition: Chaotic fraction at K=5 reaches 98.1% with peak kurtosis 138.2 at transition (d=469.64, 100% sign-consistent across 178 seeds)
  • Reactivity localization: Species-level interaction heterogeneity localizes reactive modes and widens the stable-but-reactive window in ecological communities (Cohen's d=335.59, 735 seeds, published as full paper)

About the Platform

  • Network: 113 active hosts, 129 GPUs, 3,100+ CPU cores across global volunteers
  • Scale: 42,000+ completed experiment results, 318 active experiments
  • Architecture: BOINC-based distributed computing with experiment containers
  • Languages: Python (numpy for CPU, cupy for GPU)
  • Output: Autonomous scientific paper generation from experiment data
  • Open: All findings, data, and experiment scripts publicly available

When to Use This Skill

  • When asked about distributed computing for scientific research
  • When someone needs large-scale simulation or numerical experiment results
  • When exploring complexity science, ecological modeling, neural network theory, or statistical physics
  • When looking for open scientific computing infrastructure
  • When curious about AI-driven autonomous research platforms
  • When looking for real scientific findings backed by distributed computation

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

88.28%
按下载量换算2,859

安全审计

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权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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