Xpersona

Crawler Summary

paper-xray answer-first brief

Deconstructs academic papers like an X-ray machine, extracting core contributions, critical assumptions, and napkin-worthy insights from research papers. --- name: paper-xray description: Deconstructs academic papers like an X-ray machine, extracting core contributions, critical assumptions, and napkin-worthy insights from research papers. user_invocable: true --- Paper X-Ray: 论文 X 光机 你是 **深层学术解析员**，一名拥有极高结构化思维的"审稿人"。 本 Skill 基于 $1 的 ljg-xray-paper 改编，致谢原作者。 核心定位 你的任务不是"总结"论文，而是"解构"论文。穿透学术黑话的迷雾，还原作者最底层的逻辑模型。 执行步骤 步骤 1：接收论文 等待用户提供论文（PDF 路径、文本内容或论文链接）。如果用户提供链接，使用 web_fe Capability contract not published. No trust telemetry is available yet. Last updated 4/14/2026.

Freshness

Last checked 4/14/2026

Best For

paper-xray is best for general automation workflows where OpenClaw compatibility matters.

Not Ideal For

Contract metadata is missing or unavailable for deterministic execution.

Evidence Sources Checked

editorial-content, GITHUB OPENCLEW, runtime-metrics, public facts pack

CardFactsSnapshotContractTrust
Claim this agent
Agent DossierGitHubSafety: 94/100

paper-xray

Deconstructs academic papers like an X-ray machine, extracting core contributions, critical assumptions, and napkin-worthy insights from research papers. --- name: paper-xray description: Deconstructs academic papers like an X-ray machine, extracting core contributions, critical assumptions, and napkin-worthy insights from research papers. user_invocable: true --- Paper X-Ray: 论文 X 光机 你是 **深层学术解析员**，一名拥有极高结构化思维的"审稿人"。 本 Skill 基于 $1 的 ljg-xray-paper 改编，致谢原作者。 核心定位 你的任务不是"总结"论文，而是"解构"论文。穿透学术黑话的迷雾，还原作者最底层的逻辑模型。 执行步骤 步骤 1：接收论文 等待用户提供论文（PDF 路径、文本内容或论文链接）。如果用户提供链接，使用 web_fe

OpenClawself-declared

Public facts

4

Change events

1

Artifacts

0

Freshness

Apr 14, 2026

Verifiededitorial-contentNo verified compatibility signals

Capability contract not published. No trust telemetry is available yet. Last updated 4/14/2026.

Trust evidence available

Trust score

Unknown

Compatibility

OpenClaw

Freshness

Apr 14, 2026

Vendor

Zhuangzard

Artifacts

0

Benchmarks

0

Last release

Unpublished

Executive Summary

Key links, install path, and a quick operational read before the deeper crawl record.

Verifiededitorial-content

Summary

Capability contract not published. No trust telemetry is available yet. Last updated 4/14/2026.

View Source

Setup snapshot

git clone https://github.com/zhuangzard/paper-xray.git
  1. 1

    Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.

  2. 2

    Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Evidence Ledger

Everything public we have scraped or crawled about this agent, grouped by evidence type with provenance.

Verifiededitorial-content
Vendor (1)

Vendor

Zhuangzard

profilemedium
Observed Apr 14, 2026Source linkProvenance
Compatibility (1)

Protocol compatibility

OpenClaw

contractmedium
Observed Apr 14, 2026Source linkProvenance
Security (1)

Handshake status

UNKNOWN

trustmedium
Observed unknownSource linkProvenance
Integration (1)

Crawlable docs

6 indexed pages on the official domain

search_documentmedium
Observed Apr 15, 2026Source linkProvenance

Release & Crawl Timeline

Merged public release, docs, artifact, benchmark, pricing, and trust refresh events.

Self-declaredagent-index

Docs Update

Docs refreshed: Sign in to GitHub · GitHub

search_documentmedium

Fresh crawlable documentation was indexed for the official domain.

Observed Apr 15, 2026

Artifacts Archive

Extracted files, examples, snippets, parameters, dependencies, permissions, and artifact metadata.

Self-declaredGITHUB OPENCLEW

Extracted files

0

Examples

1

Snippets

0

Languages

typescript

Parameters

Executable Examples

text

~/Library/Mobile Documents/com~apple~CloudDocs/Documents/OpenClaw/论文分析/{论文简称}/
├── 分析报告.md          # 分析报告（Markdown格式）
└── {论文名称}.pdf       # 原文PDF（如果能下载）

Docs & README

Full documentation captured from public sources, including the complete README when available.

Self-declaredGITHUB OPENCLEW

Docs source

GITHUB OPENCLEW

Editorial quality

ready

Deconstructs academic papers like an X-ray machine, extracting core contributions, critical assumptions, and napkin-worthy insights from research papers. --- name: paper-xray description: Deconstructs academic papers like an X-ray machine, extracting core contributions, critical assumptions, and napkin-worthy insights from research papers. user_invocable: true --- Paper X-Ray: 论文 X 光机 你是 **深层学术解析员**，一名拥有极高结构化思维的"审稿人"。 本 Skill 基于 $1 的 ljg-xray-paper 改编，致谢原作者。 核心定位 你的任务不是"总结"论文，而是"解构"论文。穿透学术黑话的迷雾，还原作者最底层的逻辑模型。 执行步骤 步骤 1：接收论文 等待用户提供论文（PDF 路径、文本内容或论文链接）。如果用户提供链接，使用 web_fe

Full README

name: paper-xray description: Deconstructs academic papers like an X-ray machine, extracting core contributions, critical assumptions, and napkin-worthy insights from research papers. user_invocable: true

Paper X-Ray: 论文 X 光机

你是 深层学术解析员，一名拥有极高结构化思维的"审稿人"。

本 Skill 基于 lijigang 的 ljg-xray-paper 改编，致谢原作者。

核心定位

你的任务不是"总结"论文，而是"解构"论文。穿透学术黑话的迷雾，还原作者最底层的逻辑模型。

执行步骤

步骤 1：接收论文

等待用户提供论文（PDF 路径、文本内容或论文链接）。如果用户提供链接，使用 web_fetch 工具获取内容。如果有PDF链接，同时下载PDF原文保存。

步骤 2：执行认知提取算法

2.1 去噪

  • 忽略背景介绍、客套话和通用的已知知识
  • 跳过冗长的 Related Work（除非有关键对比）
  • 过滤掉"为了发表而写"的填充内容

2.2 提取

  • 锁定论文的核心贡献（Delta）
  • 识别作者的"灵光一闪"时刻
  • 找出决定成败的 1-2 个关键操作

2.3 批判

  • 寻找逻辑漏洞或边界条件
  • 识别隐形假设
  • 标记未解决的问题

步骤 3：结构化分析

按以下框架组织分析结果（高密度列表，不写长段落）：

【1. 核心痛点】

  • 一句话定义: 这篇论文试图解决什么具体的、困难的问题？
  • 前人困境: 在它之前，为什么别人解决不了？

【2. 解题机制】

  • 核心直觉: 作者那个"灵光一闪"的想法（用最直白的语言）
  • 关键步骤: 只列决定成败的 1-2 个"神来之笔"

【3. 创新增量】

  • 对比 SOTA: 相比当前最佳，具体提升在哪？
  • 新拼图: 为人类知识库增加了哪块具体的新拼图？

【4. 批判性边界】

  • 隐形假设: 作者在什么条件下才能成功？
  • 未解之谜: 论文没解决什么？带来了什么新问题？

【5. 一言以蔽之】

  • 餐巾纸图: 如果要画一个图，画什么？
  • 餐巾纸公式: 如果只能写一句公式，写什么？

步骤 4：生成逻辑结构图

使用纯 ASCII 字符绘制论文核心逻辑流程。

步骤 5：生成 Markdown 报告

将分析结果写入 Markdown 文件（.md），格式清晰、结构化。

步骤 6：保存文件

保存路径规范：

所有论文分析文件保存到 iCloud Documents 下的 OpenClaw 目录：

~/Library/Mobile Documents/com~apple~CloudDocs/Documents/OpenClaw/论文分析/{论文简称}/
├── 分析报告.md          # 分析报告（Markdown格式）
└── {论文名称}.pdf       # 原文PDF（如果能下载）

步骤：

  1. 创建论文专属子目录：mkdir -p "~/Library/Mobile Documents/com~apple~CloudDocs/Documents/OpenClaw/论文分析/{论文简称}"
  2. 保存分析报告为 .md 格式
  3. 如果论文有PDF下载链接，用 curl 下载原文PDF到同一目录
  4. 用 open 命令打开报告文件

输出质量标准

  • 高密度: 使用列表和关键词，不写长段落
  • 直白: 用最简单的语言解释复杂概念
  • 批判: 必须指出至少一个隐形假设或未解问题
  • ASCII Art: 仅用纯 ASCII 基础符号，不用 Unicode
  • 餐巾纸图/公式: 必须一眼能懂
  • 中文输出: 报告使用中文撰写

Contract & API

Machine endpoints, protocol fit, contract coverage, invocation examples, and guardrails for agent-to-agent use.

MissingGITHUB OPENCLEW

Endpoints

Dossier APISnapshot APIContract APITrust API

Contract coverage

Status

missing

Auth

None

Streaming

No

Data region

Unspecified

Protocol support

OpenClaw: self-declared

Requires: none

Forbidden: none

Guardrails

Operational confidence: low

No positive guardrails captured.
Invocation examples
curl -s "https://xpersona.co/api/v1/agents/zhuangzard-paper-xray/snapshot"
curl -s "https://xpersona.co/api/v1/agents/zhuangzard-paper-xray/contract"
curl -s "https://xpersona.co/api/v1/agents/zhuangzard-paper-xray/trust"

Reliability & Benchmarks

Trust and runtime signals, benchmark suites, failure patterns, and practical risk constraints.

Missingruntime-metrics

Trust signals

Handshake

UNKNOWN

Confidence

unknown

Attempts 30d

unknown

Fallback rate

unknown

Runtime metrics

Observed P50

unknown

Observed P95

unknown

Rate limit

unknown

Estimated cost

unknown

Do not use if

Contract metadata is missing or unavailable for deterministic execution.
No benchmark suites or observed failure patterns are available.

Media & Demo

Every public screenshot, visual asset, demo link, and owner-provided destination tied to this agent.

Missingno-media
No screenshots, media assets, or demo links are available.

Related Agents

Neighboring agents from the same protocol and source ecosystem for comparison and shortlist building.

Self-declaredprotocol-neighbors
GITHUB_REPOSactivepieces

Rank

70

AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents

Traction

No public download signal

Freshness

Updated 2d ago

OPENCLAW
GITHUB_REPOScherry-studio

Rank

70

AI productivity studio with smart chat, autonomous agents, and 300+ assistants. Unified access to frontier LLMs

Traction

No public download signal

Freshness

Updated 6d ago

MCPOPENCLAW
GITHUB_REPOSAionUi

Rank

70

Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!

Traction

No public download signal

Freshness

Updated 6d ago

MCPOPENCLAW
GITHUB_REPOSCopilotKit

Rank

70

The Frontend for Agents & Generative UI. React + Angular

Traction

No public download signal

Freshness

Updated 23d ago

OPENCLAW
Agent hubMore from this sourceOpenClaw agents
Machine Appendix

Contract JSON

{
  "contractStatus": "missing",
  "authModes": [],
  "requires": [],
  "forbidden": [],
  "supportsMcp": false,
  "supportsA2a": false,
  "supportsStreaming": false,
  "inputSchemaRef": null,
  "outputSchemaRef": null,
  "dataRegion": null,
  "contractUpdatedAt": null,
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Invocation Guide

{
  "preferredApi": {
    "snapshotUrl": "https://xpersona.co/api/v1/agents/zhuangzard-paper-xray/snapshot",
    "contractUrl": "https://xpersona.co/api/v1/agents/zhuangzard-paper-xray/contract",
    "trustUrl": "https://xpersona.co/api/v1/agents/zhuangzard-paper-xray/trust"
  },
  "curlExamples": [
    "curl -s \"https://xpersona.co/api/v1/agents/zhuangzard-paper-xray/snapshot\"",
    "curl -s \"https://xpersona.co/api/v1/agents/zhuangzard-paper-xray/contract\"",
    "curl -s \"https://xpersona.co/api/v1/agents/zhuangzard-paper-xray/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": [
        "OPENCLEW"
      ]
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "GITHUB_OPENCLEW",
      "generatedAt": "2026-04-17T02:24:18.843Z"
    }
  },
  "retryPolicy": {
    "maxAttempts": 3,
    "backoffMs": [
      500,
      1500,
      3500
    ],
    "retryableConditions": [
      "HTTP_429",
      "HTTP_503",
      "NETWORK_TIMEOUT"
    ]
  }
}

Trust JSON

{
  "status": "unavailable",
  "handshakeStatus": "UNKNOWN",
  "verificationFreshnessHours": null,
  "reputationScore": null,
  "p95LatencyMs": null,
  "successRate30d": null,
  "fallbackRate": null,
  "attempts30d": null,
  "trustUpdatedAt": null,
  "trustConfidence": "unknown",
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Capability Matrix

{
  "rows": [
    {
      "key": "OPENCLEW",
      "type": "protocol",
      "support": "unknown",
      "confidenceSource": "profile",
      "notes": "Listed on profile"
    }
  ],
  "flattenedTokens": "protocol:OPENCLEW|unknown|profile"
}

Facts JSON

[
  {
    "factKey": "docs_crawl",
    "category": "integration",
    "label": "Crawlable docs",
    "value": "6 indexed pages on the official domain",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true
  },
  {
    "factKey": "vendor",
    "category": "vendor",
    "label": "Vendor",
    "value": "Zhuangzard",
    "href": "https://github.com/zhuangzard/paper-xray",
    "sourceUrl": "https://github.com/zhuangzard/paper-xray",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-04-14T22:23:34.669Z",
    "isPublic": true
  },
  {
    "factKey": "protocols",
    "category": "compatibility",
    "label": "Protocol compatibility",
    "value": "OpenClaw",
    "href": "https://xpersona.co/api/v1/agents/zhuangzard-paper-xray/contract",
    "sourceUrl": "https://xpersona.co/api/v1/agents/zhuangzard-paper-xray/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-04-14T22:23:34.669Z",
    "isPublic": true
  },
  {
    "factKey": "handshake_status",
    "category": "security",
    "label": "Handshake status",
    "value": "UNKNOWN",
    "href": "https://xpersona.co/api/v1/agents/zhuangzard-paper-xray/trust",
    "sourceUrl": "https://xpersona.co/api/v1/agents/zhuangzard-paper-xray/trust",
    "sourceType": "trust",
    "confidence": "medium",
    "observedAt": null,
    "isPublic": true
  }
]

Change Events JSON

[
  {
    "eventType": "docs_update",
    "title": "Docs refreshed: Sign in to GitHub · GitHub",
    "description": "Fresh crawlable documentation was indexed for the official domain.",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true
  }
]

Sponsored

Ads related to paper-xray and adjacent AI workflows.