一条命令完成：读论文 → 生成解读 → 铸成卡片。支持多篇并行。
Works with
一条命令完成：读论文 → 生成解读 → 铸成卡片。支持多篇并行。
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 | 说明 |
|---|---|
| 无参数 | 对话中已提供的论文链接/文件 |
-l |
卡片模具改用长图模式（默认 -c 漫画） |
-i |
卡片模具改用信息图模式 |
从用户消息中提取所有论文来源（arxiv URL、PDF 路径、论文名称等）。
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 -c，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。
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}
...
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionljg-paper-flowExecute the skills CLI command in your project's root directory to begin installation:
Fetches ljg-paper-flow from lijigang/ljg-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate ljg-paper-flow. Access via /ljg-paper-flow in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
1
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Run in your terminal
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Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
davila7/claude-code-templates
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
Registry listing for ljg-paper-flow matched our evaluation — installs cleanly and behaves as described in the markdown.
Keeps context tight: ljg-paper-flow is the kind of skill you can hand to a new teammate without a long onboarding doc.
We added ljg-paper-flow from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
I recommend ljg-paper-flow for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
I recommend ljg-paper-flow for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
ljg-paper-flow fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
ljg-paper-flow has been reliable in day-to-day use. Documentation quality is above average for community skills.
ljg-paper-flow reduced setup friction for our internal harness; good balance of opinion and flexibility.
Solid pick for teams standardizing on skills: ljg-paper-flow is focused, and the summary matches what you get after install.
Registry listing for ljg-paper-flow matched our evaluation — installs cleanly and behaves as described in the markdown.
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