---
name: ljg-paper-flow
description: "Paper workflow: read papers + cast cards in one go. Takes one or more arxiv links, paper URLs, PDFs, or paper names. For each paper, runs ljg-paper (generates org analysis) then ljg-card -l (generates long reading card PNG). Use when user says '论文流', 'paper flow', '读论文并做卡片', '论文卡片', or provides multiple papers wanting both analysis and cards."
user_invocable: true
version: "1.0.1"
---

## 是什么

一条指令把"读论文 → 出深度解读 → 铸成可分享卡片"串成流水线，多篇论文还能并行跑，帮你在一杯咖啡的时间内把一摞 arXiv 链接变成一组可发圈的研究卡片。

## 怎么用

1. 把论文来源（arXiv 链接 / PDF 路径 / 论文名）一次性丢给流水线，不用一篇一篇发。
2. 选卡片模具：默认长图、`-c` 多卡、`-i` 信息图（按你要分享的渠道决定）。
3. 流水线为每篇论文起一个子智能体，串行执行"读论文 → 铸卡片"两步。
4. 多篇论文之间并行，互不阻塞，等所有子智能体收工。
5. 最后看汇总报告，每篇论文都带 org 解读路径 + PNG 卡片路径，可直接转发或归档。

## 架构图

```mermaid
flowchart LR
  A[论文清单] --> B[并行分发]
  B --> C[读论文 ljg-paper]
  C --> D[生成 org 解读]
  D --> E[铸卡片 ljg-card]
  E --> F[PNG + 汇总报告]
```

# ljg-paper-flow: 论文流

一条命令完成：读论文 → 生成解读 → 铸成卡片。支持多篇并行。

## 模式

**强制 NATIVE 模式。** 本 workflow 是纯 skill 管道（ljg-paper → ljg-card），不需要 Algorithm 的七步流程。直接按下方执行步骤调用 skill，不走 OBSERVE/THINK/PLAN/BUILD/EXECUTE/VERIFY/LEARN。

## 参数

| 参数 | 说明 |
|------|------|
| 无参数 | 对话中已提供的论文链接/文件 |
| `-c` | 卡片模具改用多卡模式（默认 `-l` 长图） |
| `-i` | 卡片模具改用信息图模式 |

## 执行

### 1. 收集论文列表

从用户消息中提取所有论文来源（arxiv URL、PDF 路径、论文名称等）。

### 2. 并行处理每篇论文

对每篇论文，启动一个 Agent subagent，每个 subagent 按顺序执行两步：

**步骤 A — 读论文（ljg-paper）：**

调用 Skill tool 执行 `ljg-paper`，传入该论文的来源。等待完成，获得生成的 org 文件路径。

**步骤 B — 铸卡片（ljg-card）：**

读取步骤 A 生成的 org 文件，调用 Skill tool 执行 `ljg-card`（默认 `-l`，或按用户指定的模具参数），以 org 文件内容为输入。等待完成，获得 PNG 文件路径。

### 3. 汇总报告

所有论文处理完成后，汇总输出：

```
════ 论文流完成 ═══════════════════════
📄 {论文标题1}
   📝 解读: {org 文件路径}
   🖼️ 卡片: {PNG 文件路径}

📄 {论文标题2}
   📝 解读: {org 文件路径}
   🖼️ 卡片: {PNG 文件路径}
...
```

## 关键约束

- 每篇论文的两步必须串行（先 paper 后 card），但多篇论文之间并行
- ljg-paper 和 ljg-card 各自的质量标准、红线、品味准则不变
- 卡片内容来自生成的 org 文件，不是原始论文


---
Source attribution: MARUCIE
Original project: https://github.com/MARUCIE/openclaw-foundry/blob/f4c52cb78ad4506edbd088fde628b7a6b8468b5d/web/public/packs/research-analyst/skills/ljg-paper-flow/SKILL.md
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Dave AI.

## Upstream license notice

MIT License

Copyright (c) 2026 Maurice Wen

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Dave AI resource metadata

Creator / publisher: MARUCIE
Original project: https://github.com/MARUCIE/openclaw-foundry/blob/f4c52cb78ad4506edbd088fde628b7a6b8468b5d/web/public/packs/research-analyst/skills/ljg-paper-flow/SKILL.md
Attribution basis: Source repository record

Fields of work: Education & Research
Roles: Academic Writer, Researcher, Tutor / Instructor
Specialties: Frontend
Tools: Ljg Card, Ljg Paper
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: d78a2d448557c619d26ee954c466dab27ece2f447588bbf481bb9913f908b6de