Xpersona

Crawler Summary

daily-paper answer-first brief

具身智能论文速递 - 自动化学术调研工具 自动从 arXiv 获取具身智能领域最新论文，智能筛选高质量研究，生成结构化中文报告。 使用场景： - 用户要求"今日论文"、"论文速递"、"学术调研" - 需要追踪具身智能/自动驾驶领域最新研究 - 定时任务自动执行每日/每周调研 --- name: daily-paper description: | 具身智能论文速递 - 自动化学术调研工具 自动从 arXiv 获取具身智能领域最新论文，智能筛选高质量研究，生成结构化中文报告。 使用场景： - 用户要求"今日论文"、"论文速递"、"学术调研" - 需要追踪具身智能/自动驾驶领域最新研究 - 定时任务自动执行每日/每周调研 --- Daily Paper - 具身智能论文速递 自动化学术调研工具，专注于具身智能（Embodied AI）领域。 研究方向（按优先级排序） 1. **VLA / 多模态机器人** - Vision-Language-Action、多模态指令控制 2. **世界模型 (World Model)** - 视频预测、物理模拟、生成式世界模型 3. **强化学习 (RL)** - Robot RL、Imitation Learning、Offline RL 4. **仿真 (Simul Capability contract not published. No trust telemetry is available yet. 2 GitHub stars reported by the source. Last updated 2/24/2026.

Freshness

Last checked 2/24/2026

Best For

daily-paper 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: 89/100

daily-paper

具身智能论文速递 - 自动化学术调研工具 自动从 arXiv 获取具身智能领域最新论文，智能筛选高质量研究，生成结构化中文报告。 使用场景： - 用户要求"今日论文"、"论文速递"、"学术调研" - 需要追踪具身智能/自动驾驶领域最新研究 - 定时任务自动执行每日/每周调研 --- name: daily-paper description: | 具身智能论文速递 - 自动化学术调研工具 自动从 arXiv 获取具身智能领域最新论文，智能筛选高质量研究，生成结构化中文报告。 使用场景： - 用户要求"今日论文"、"论文速递"、"学术调研" - 需要追踪具身智能/自动驾驶领域最新研究 - 定时任务自动执行每日/每周调研 --- Daily Paper - 具身智能论文速递 自动化学术调研工具，专注于具身智能（Embodied AI）领域。 研究方向（按优先级排序） 1. **VLA / 多模态机器人** - Vision-Language-Action、多模态指令控制 2. **世界模型 (World Model)** - 视频预测、物理模拟、生成式世界模型 3. **强化学习 (RL)** - Robot RL、Imitation Learning、Offline RL 4. **仿真 (Simul

OpenClawself-declared

Public facts

5

Change events

1

Artifacts

0

Freshness

Feb 24, 2026

Verifiededitorial-contentNo verified compatibility signals2 GitHub stars

Capability contract not published. No trust telemetry is available yet. 2 GitHub stars reported by the source. Last updated 2/24/2026.

2 GitHub starsTrust evidence available

Trust score

Unknown

Compatibility

OpenClaw

Freshness

Feb 24, 2026

Vendor

Ychenjk Sudo

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Unpublished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. 2 GitHub stars reported by the source. Last updated 2/24/2026.

View Source

Setup snapshot

git clone https://github.com/ychenjk-sudo/daily-paper-skill.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

Ychenjk Sudo

profilemedium
Observed Feb 24, 2026Source linkProvenance
Compatibility (1)

Protocol compatibility

OpenClaw

contractmedium
Observed Feb 24, 2026Source linkProvenance
Adoption (1)

Adoption signal

2 GitHub stars

profilemedium
Observed Feb 24, 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

6

Snippets

0

Languages

typescript

Parameters

Executable Examples

bash

# arXiv
python scripts/fetch.py --output /tmp/arxiv_papers.json

# Semantic Scholar（重点作者）
python scripts/fetch_semantic_scholar.py --days 7 --output /tmp/s2_papers.json

# GitHub Trending
python scripts/fetch_github.py --output /tmp/github_repos.json

# Hugging Face
python scripts/fetch_huggingface.py --output /tmp/huggingface.json

text

# 具身智能论文速递 (日期)
## 📌 摘要
## 🔮 Crossing Trend（基于当期论文的客观事实）
## 📚 论文分类详情
  ### 🤖 VLA / 多模态
  ### 🌍 世界模型
  ### 🎮 强化学习
  ### 🚗 自动驾驶

text

### [论文标题](arXiv链接)
- **一句话摘要**：50字以内概括核心贡献
- **解决的工程/算法瓶颈**：（50-100字）具体说明针对什么问题，为什么之前的方法解决不了，要有技术细节
- **相对 SOTA 的核心改进点**（≤3条）：每条要具体，最好有数据支撑（如「LIBERO 上 98.5% 成功率」）
  1. 改进点1（带具体数据/对比）
  2. 改进点2
  3. 改进点3
- **工程落地潜力与前置条件**：（50-100字）分「潜力」和「前置条件」两部分写，要具体到硬件要求、数据需求等
- **风险与局限**：（50-100字）不是泛泛而谈，要指出具体在什么场景/任务下会失效
- **对自动驾驶/机器人系统的启示**：（50-100字）不是复述论文，而是从工程师视角提炼可迁移的洞见，可以类比其他领域（如 LLM、自动驾驶）的经验
- **潜在应用场景**：具体应用方向
- **论文链接**：arXiv链接（有代码附上GitHub）

bash

# 创建新文档并写入
python scripts/feishu.py --input /workspace/daily-papers/YYYY-MM-DD-cn.md --create --title "论文速递 YYYY-MM-DD"

# 写入已有文档
python scripts/feishu.py --input /workspace/daily-papers/YYYY-MM-DD-cn.md --doc-id <用户提供的DOC_ID>

bash

python /workspace/scripts/feishu_card.py --to <CHAT_ID> --template daily-paper --data <JSON_FILE>

bash

# 保存到本地
cat /workspace/daily-papers/YYYY-MM-DD-cn.md

# 或直接在消息中输出 Markdown 格式的报告

Docs & README

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

Self-declaredGITHUB OPENCLEW

Docs source

GITHUB OPENCLEW

Editorial quality

ready

具身智能论文速递 - 自动化学术调研工具 自动从 arXiv 获取具身智能领域最新论文，智能筛选高质量研究，生成结构化中文报告。 使用场景： - 用户要求"今日论文"、"论文速递"、"学术调研" - 需要追踪具身智能/自动驾驶领域最新研究 - 定时任务自动执行每日/每周调研 --- name: daily-paper description: | 具身智能论文速递 - 自动化学术调研工具 自动从 arXiv 获取具身智能领域最新论文，智能筛选高质量研究，生成结构化中文报告。 使用场景： - 用户要求"今日论文"、"论文速递"、"学术调研" - 需要追踪具身智能/自动驾驶领域最新研究 - 定时任务自动执行每日/每周调研 --- Daily Paper - 具身智能论文速递 自动化学术调研工具，专注于具身智能（Embodied AI）领域。 研究方向（按优先级排序） 1. **VLA / 多模态机器人** - Vision-Language-Action、多模态指令控制 2. **世界模型 (World Model)** - 视频预测、物理模拟、生成式世界模型 3. **强化学习 (RL)** - Robot RL、Imitation Learning、Offline RL 4. **仿真 (Simul

Full README

name: daily-paper description: | 具身智能论文速递 - 自动化学术调研工具

自动从 arXiv 获取具身智能领域最新论文，智能筛选高质量研究，生成结构化中文报告。

使用场景：

  • 用户要求"今日论文"、"论文速递"、"学术调研"
  • 需要追踪具身智能/自动驾驶领域最新研究
  • 定时任务自动执行每日/每周调研

Daily Paper - 具身智能论文速递

自动化学术调研工具，专注于具身智能（Embodied AI）领域。

研究方向（按优先级排序）

  1. VLA / 多模态机器人 - Vision-Language-Action、多模态指令控制
  2. 世界模型 (World Model) - 视频预测、物理模拟、生成式世界模型
  3. 强化学习 (RL) - Robot RL、Imitation Learning、Offline RL
  4. 仿真 (Simulation) - Sim2Real、物理仿真、可微仿真
  5. 自动驾驶 - 端到端驾驶、BEV、占用网络

不收录：开源工具/框架、效率优化、纯数据集、纯 LLM、纯视觉

数据源

  • arXiv（主要）: cs.RO, cs.LG, cs.CV, cs.AI
  • Semantic Scholar: 追踪重点作者（Jim Fan, Pieter Abbeel, Sergey Levine 等）
  • GitHub Trending: 新开源项目
  • Hugging Face: robotics、RL、world-model 标签

执行流程

步骤 1：获取数据

# arXiv
python scripts/fetch.py --output /tmp/arxiv_papers.json

# Semantic Scholar（重点作者）
python scripts/fetch_semantic_scholar.py --days 7 --output /tmp/s2_papers.json

# GitHub Trending
python scripts/fetch_github.py --output /tmp/github_repos.json

# Hugging Face
python scripts/fetch_huggingface.py --output /tmp/huggingface.json

步骤 2：筛选论文

日报：3-6 篇 | 周报：4-6 篇

评分维度：

  • Novelty（新颖性）
  • Impact（潜在影响力）
  • Engineering Value（工程价值）

重点机构优先：NVIDIA, DeepMind, Berkeley, Stanford, MIT, Tesla AI, Physical Intelligence

步骤 3：生成报告

报告结构：

# 具身智能论文速递 (日期)
## 📌 摘要
## 🔮 Crossing Trend（基于当期论文的客观事实）
## 📚 论文分类详情
  ### 🤖 VLA / 多模态
  ### 🌍 世界模型
  ### 🎮 强化学习
  ### 🚗 自动驾驶

每篇论文的固定输出结构：

⚠️ 重要：写每篇论文前，必须先用 web_fetch 读取论文的 arXiv HTML 版本（如 https://arxiv.org/html/2602.18224v1），理解技术细节后再写。只看 abstract 写出来的内容会很浅。

### [论文标题](arXiv链接)
- **一句话摘要**：50字以内概括核心贡献
- **解决的工程/算法瓶颈**：（50-100字）具体说明针对什么问题，为什么之前的方法解决不了，要有技术细节
- **相对 SOTA 的核心改进点**（≤3条）：每条要具体，最好有数据支撑（如「LIBERO 上 98.5% 成功率」）
  1. 改进点1（带具体数据/对比）
  2. 改进点2
  3. 改进点3
- **工程落地潜力与前置条件**：（50-100字）分「潜力」和「前置条件」两部分写，要具体到硬件要求、数据需求等
- **风险与局限**：（50-100字）不是泛泛而谈，要指出具体在什么场景/任务下会失效
- **对自动驾驶/机器人系统的启示**：（50-100字）不是复述论文，而是从工程师视角提炼可迁移的洞见，可以类比其他领域（如 LLM、自动驾驶）的经验
- **潜在应用场景**：具体应用方向
- **论文链接**：arXiv链接（有代码附上GitHub）

Crossing Trend 格式：

  • 本周证据：哪些论文体现了这个趋势
  • 技术迁移：哪项技术从哪个领域迁移过来
  • 趋势判断：基于事实的客观判断

步骤 4：发布

根据当前渠道自动选择输出方式：

飞书渠道

  1. 创建或使用飞书文档：
    • 如果用户未指定文档 ID，使用飞书 API 创建新文档
    • 如果用户指定了文档 ID/链接，写入该文档
    • 新内容插入文档顶部
# 创建新文档并写入
python scripts/feishu.py --input /workspace/daily-papers/YYYY-MM-DD-cn.md --create --title "论文速递 YYYY-MM-DD"

# 写入已有文档
python scripts/feishu.py --input /workspace/daily-papers/YYYY-MM-DD-cn.md --doc-id <用户提供的DOC_ID>
  1. 发送飞书卡片（可选）：
python /workspace/scripts/feishu_card.py --to <CHAT_ID> --template daily-paper --data <JSON_FILE>

非飞书渠道（Telegram/Discord/终端等）

直接输出 Markdown 文档内容，或保存到本地文件：

# 保存到本地
cat /workspace/daily-papers/YYYY-MM-DD-cn.md

# 或直接在消息中输出 Markdown 格式的报告

输出示例（非飞书）：

# 具身智能论文速递 (2026-02-24)

## 📌 摘要
今日精选 4 篇论文，覆盖 VLA、世界模型、强化学习领域...

## 🔮 Crossing Trend
...

## 📚 论文详情
### 🤖 VLA / 多模态
#### [论文标题](https://arxiv.org/abs/xxxx)
...

配置

重点关注机构

NVIDIA, DeepMind, UC Berkeley/BAIR, Stanford, MIT, 
Tesla AI, Physical Intelligence, 1X Technologies, Figure AI,
OpenAI, Anthropic, Meta AI/FAIR, Covariant

重点作者（Semantic Scholar 追踪）

Jim Fan (Linxi Fan), Pieter Abbeel, Sergey Levine, Chelsea Finn,
Danijar Hafner, Yann LeCun, Kaiming He, Ilya Sutskever

重点论文系列

Dreamer 系列, DreamZero/DreamDojo, RT 系列, OpenVLA/Octo, ALOHA, JEPA 系列

用户配置（可选）

用户可以在对话中指定：

  • 飞书文档 ID：--doc-id WPmJdLKAvohbGaxBRmLc08MVn5f 或直接粘贴文档链接
  • 输出格式：--format md 强制输出 Markdown
  • 推送对象：--to <open_id> 指定飞书消息接收人

如果未指定，根据当前会话渠道自动选择输出方式。

Prompt 文件

  • 日报卡片：/workspace/prompts/daily-paper-card.md
  • 周报卡片：/workspace/prompts/weekly-paper-card.md

定时任务示例

{
  "name": "Daily Paper",
  "schedule": {"kind": "cron", "expr": "0 9 * * *", "tz": "Asia/Shanghai"},
  "sessionTarget": "isolated",
  "payload": {
    "kind": "agentTurn",
    "model": "gemini",
    "message": "执行今日论文速递，输出到飞书文档",
    "deliver": true,
    "channel": "feishu",
    "to": "<your_open_id>"
  }
}

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/ychenjk-sudo-daily-paper-skill/snapshot"
curl -s "https://xpersona.co/api/v1/agents/ychenjk-sudo-daily-paper-skill/contract"
curl -s "https://xpersona.co/api/v1/agents/ychenjk-sudo-daily-paper-skill/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/ychenjk-sudo-daily-paper-skill/snapshot",
    "contractUrl": "https://xpersona.co/api/v1/agents/ychenjk-sudo-daily-paper-skill/contract",
    "trustUrl": "https://xpersona.co/api/v1/agents/ychenjk-sudo-daily-paper-skill/trust"
  },
  "curlExamples": [
    "curl -s \"https://xpersona.co/api/v1/agents/ychenjk-sudo-daily-paper-skill/snapshot\"",
    "curl -s \"https://xpersona.co/api/v1/agents/ychenjk-sudo-daily-paper-skill/contract\"",
    "curl -s \"https://xpersona.co/api/v1/agents/ychenjk-sudo-daily-paper-skill/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": [
        "OPENCLEW"
      ]
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "GITHUB_OPENCLEW",
      "generatedAt": "2026-04-17T02:21:39.891Z"
    }
  },
  "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": "Ychenjk Sudo",
    "href": "https://github.com/ychenjk-sudo/daily-paper-skill",
    "sourceUrl": "https://github.com/ychenjk-sudo/daily-paper-skill",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-02-24T19:43:14.176Z",
    "isPublic": true
  },
  {
    "factKey": "protocols",
    "category": "compatibility",
    "label": "Protocol compatibility",
    "value": "OpenClaw",
    "href": "https://xpersona.co/api/v1/agents/ychenjk-sudo-daily-paper-skill/contract",
    "sourceUrl": "https://xpersona.co/api/v1/agents/ychenjk-sudo-daily-paper-skill/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-02-24T19:43:14.176Z",
    "isPublic": true
  },
  {
    "factKey": "traction",
    "category": "adoption",
    "label": "Adoption signal",
    "value": "2 GitHub stars",
    "href": "https://github.com/ychenjk-sudo/daily-paper-skill",
    "sourceUrl": "https://github.com/ychenjk-sudo/daily-paper-skill",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-02-24T19:43:14.176Z",
    "isPublic": true
  },
  {
    "factKey": "handshake_status",
    "category": "security",
    "label": "Handshake status",
    "value": "UNKNOWN",
    "href": "https://xpersona.co/api/v1/agents/ychenjk-sudo-daily-paper-skill/trust",
    "sourceUrl": "https://xpersona.co/api/v1/agents/ychenjk-sudo-daily-paper-skill/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 daily-paper and adjacent AI workflows.