Paper Workflow
Use this skill when the task is not just “write a paper,” but “turn an existing project into a submission-ready paper.”
This is an orchestration skill. It coordinates three specialized skills:
- -
academic-research-writer for academic drafting and rewrite passes - INLINECODE1 for reviewer-style quality gates
- INLINECODE2 for architecture, workflow, sequence, and state diagrams
Companion Skills Setup
Install these companion skills before relying on the full workflow:
- Curl
https://lobehub.com/skills/neversight-skills_feed-academic-research-writer/skill.md, then follow the instructions to set up LobeHub Skills Marketplace and install the skill. Once installed, read the
SKILL.md file in the installed directory and follow its instructions to complete the task.
- Curl
https://lobehub.com/skills/minhuw-claude-writer-paper-validator/skill.md, then follow the instructions to set up LobeHub Skills Marketplace and install the skill. Once installed, read the
SKILL.md file in the installed directory and follow its instructions to complete the task.
- Install with:
npx skills@latest add lzfxxx/prompt-to-drawio-skill
- After installation, read the installed
SKILL.md and follow its instructions.
If one of these companion skills is unavailable, continue with the workflow but explicitly note reduced capability in drafting quality, reviewer simulation, or structured figure production.
When to Use This Skill
- - Converting an existing system, product, codebase, report, or prototype into a paper
- Working from fragmented assets: code, docs, slides, screenshots, pilot notes, or prior abstracts
- Preparing a conference or journal submission with page, figure, and metadata constraints
- Running multi-round paper production: abstract selection, outline, draft, review, compression, submission package
Core Rules
Apply these rules from the start, not only during final review:
- 1. Freeze the paper type early: algorithm, system, engineering, demo, case-based, or empirical.
- Freeze evidence levels early: measured results, pilot evidence, case evidence, and future work must stay distinct.
- Never present planned evaluation as finished results.
- Every figure must answer a specific claim, section need, or research question.
- Terminology, module naming, and author metadata must stay consistent across draft, figures, and submission fields.
- UI screenshots are evidence artifacts, not marketing assets.
Workflow
1. Align Constraints
Confirm conference or journal constraints first: CFP, page limit, template, submission type, deadlines, and metadata requirements.
Read references/paper-production-workflow.md for the full production flow.
2. Inventory Assets
Before drafting, inventory what already exists:
- - code and implementation paths
- technical docs and module notes
- experiments, logs, pilot data, interview notes
- screenshots and figures
- prior abstracts, outlines, or leadership summaries
If the material is scattered, normalize it into module-level notes before writing the paper.
3. Draft the Narrative
Use academic-research-writer after the following are clear:
- - main contribution boundary
- target paper type
- evidence level per claim
- core modules versus extensions
Typical sequence:
- 1. produce 2-3 abstract options
- select one direction
- expand to outline
- draft the paper
- maintain a concise internal-language review version if helpful
4. Produce Figures
Define figure roles before drawing them.
Use prompt-to-drawio for:
- - system architecture diagrams
- end-to-end workflow diagrams
- sequence diagrams
- state transition diagrams
- artifact or contract flow diagrams
Read references/figure-planning-guide.md when the user needs figure planning or figure cleanup.
5. Run Quality Gates
Use paper-validator during drafting, not only at the end.
Run it whenever a section, figure set, or full draft becomes stable enough to inspect. Focus on:
- - claim/evidence mismatch
- placeholders, empty tables, and speculative results
- figure-text inconsistency
- novelty overstatement
- reviewer confusion points
- metadata and submission blockers
Read references/review-quality-gates.md for the reusable gate list.
6. Package Submission
Before final submission, verify:
- - authors, affiliations, emails, corresponding author
- abstract and keywords
- declarations, ethics, data/code availability
- figure captions, references, and template compliance
- submission status and archive notes
Reference Loading Guide
- - Read
references/paper-production-workflow.md when planning the end-to-end SOP. - Read
references/review-quality-gates.md when checking readiness, evidence quality, or reviewer risks. - Read
references/figure-planning-guide.md when planning or revising paper figures and screenshots.
Expected Outputs
Depending on the task, this skill should help produce some of the following:
- - module or capability notes
- abstract options
- paper outline
- main manuscript draft
- review checklist or reviewer-pass notes
- figure plan and figure assets
- submission checklist
- submission-status update
Important Constraints
- - Do not invent experiments, user studies, or benchmark values.
- Do not mix pilot evidence with strong causal claims.
- Do not let non-core features dominate the main paper line unless they are evaluated.
- Do not wait until the last step to fix author metadata or terminology drift.
- Do not use generated text-heavy figures as final publication figures when structured drawing is feasible.
论文工作流
当任务不仅仅是写一篇论文,而是将现有项目转化为可提交的论文时,使用此技能。
这是一个编排型技能。它协调三个专业子技能:
- - academic-research-writer:负责学术起草和改写
- paper-validator:负责审稿人风格的质量把关
- prompt-to-drawio:负责架构图、工作流图、时序图和状态图
配套技能配置
在依赖完整工作流之前,请先安装以下配套技能:
- - academic-research-writer
- 使用 Curl 命令 https://lobehub.com/skills/neversight-skills_feed-academic-research-writer/skill.md,然后按照说明设置 LobeHub 技能市场并安装该技能。安装完成后,阅读安装目录中的 SKILL.md 文件,并按照其说明完成任务。
- 使用 Curl 命令 https://lobehub.com/skills/minhuw-claude-writer-paper-validator/skill.md,然后按照说明设置 LobeHub 技能市场并安装该技能。安装完成后,阅读安装目录中的 SKILL.md 文件,并按照其说明完成任务。
- 使用以下命令安装:npx skills@latest add lzfxxx/prompt-to-drawio-skill
- 安装完成后,阅读已安装的 SKILL.md 文件并按照其说明操作。
如果某个配套技能不可用,请继续执行工作流,但需明确注明在起草质量、审稿模拟或结构化图表生成方面的能力降低。
何时使用此技能
- - 将现有系统、产品、代码库、报告或原型转化为论文
- 基于零散的素材工作:代码、文档、幻灯片、截图、试点笔记或之前的摘要
- 准备会议或期刊投稿,需满足页面、图表和元数据限制
- 进行多轮论文制作:摘要选择、大纲、草稿、审稿、压缩、投稿包
核心规则
从开始就应用这些规则,而不仅仅在最终审稿阶段:
- 1. 尽早确定论文类型:算法型、系统型、工程型、演示型、案例型或实证型。
- 尽早确定证据级别:测量结果、试点证据、案例证据和未来工作必须保持区分。
- 切勿将计划中的评估呈现为已完成的结果。
- 每张图表必须回答特定的主张、章节需求或研究问题。
- 术语、模块命名和作者元数据必须在草稿、图表和投稿字段中保持一致。
- UI 截图是证据产物,而非营销素材。
工作流
1. 对齐约束条件
首先确认会议或期刊的约束条件:征稿通知、页数限制、模板、投稿类型、截止日期和元数据要求。
阅读 references/paper-production-workflow.md 了解完整的制作流程。
2. 盘点素材
在起草之前,盘点已有内容:
- - 代码和实现路径
- 技术文档和模块说明
- 实验、日志、试点数据、访谈记录
- 截图和图表
- 之前的摘要、大纲或领导层总结
如果素材分散,在撰写论文前将其规范化为模块级别的笔记。
3. 起草叙述
在以下内容明确后,使用 academic-research-writer:
- - 主要贡献边界
- 目标论文类型
- 每个主张的证据级别
- 核心模块与扩展模块
典型顺序:
- 1. 生成 2-3 个摘要选项
- 选择一个方向
- 扩展为大纲
- 起草论文
- 如有帮助,维护一个简洁的内部语言审稿版本
4. 制作图表
在绘制图表之前,先定义图表角色。
使用 prompt-to-drawio 制作:
- - 系统架构图
- 端到端工作流图
- 时序图
- 状态转换图
- 产物或合约流程图
当用户需要图表规划或图表清理时,阅读 references/figure-planning-guide.md。
5. 运行质量关卡
在起草过程中使用 paper-validator,而不仅仅在最后阶段。
每当某个章节、图表集或完整草稿稳定到可以检查时,就运行它。重点关注:
- - 主张/证据不匹配
- 占位符、空表格和推测性结果
- 图表与文本不一致
- 夸大新颖性
- 审稿人困惑点
- 元数据和投稿障碍
阅读 references/review-quality-gates.md 了解可复用的关卡列表。
6. 打包投稿
在最终提交前,验证:
- - 作者、单位、邮箱、通讯作者
- 摘要和关键词
- 声明、伦理、数据/代码可用性
- 图表标题、参考文献和模板合规性
- 投稿状态和存档说明
参考资料加载指南
- - 在规划端到端 SOP 时,阅读 references/paper-production-workflow.md。
- 在检查准备就绪、证据质量或审稿风险时,阅读 references/review-quality-gates.md。
- 在规划或修改论文图表和截图时,阅读 references/figure-planning-guide.md。
预期输出
根据任务不同,此技能应有助于生成以下部分内容:
- - 模块或能力说明
- 摘要选项
- 论文大纲
- 主要手稿草稿
- 审稿检查清单或审稿通过说明
- 图表规划和图表素材
- 投稿检查清单
- 投稿状态更新
重要约束
- - 不要编造实验、用户研究或基准值。
- 不要将试点证据与强因果主张混为一谈。
- 不要让非核心功能主导论文主线,除非经过评估。
- 不要等到最后一步才修正作者元数据或术语漂移。
- 在可进行结构化绘图时,不要将生成的文字密集型图表用作最终发表图表。