Paper Read Batch

Community

Keming-Shen

paper-read-batch

面向 MotionSurf 本地 tex_source markdown 资产的批量论文分析入口。当用户希望批量分析多篇本地论文、处理所有尚未生成研究笔记的 markdown 论文、按标题/目录名/匹配条件筛选一批论文生成 ReadNote/ResearchPaper/* 下的 note.md 与 meta.json 时，优先使用这个 skill。它只基于本地 markdown，不走 direct PDF 分析，并复用 paper-read-local 的单篇 LLM 生成链路，而不是维护第二套 Python 语义模板。

Overview

Publisher	Keming-Shen
Repository	`MotionSurf`
Skill name	`paper-read-batch`
Stars	104
Forks	0
Bundled files	1
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
1 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by Keming-Shen on GitHub. Read the source before you install it.

Installation

Install the Paper Read Batch AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/Keming-Shen/MotionSurf/tree/main/.claude/skills/paper-read-batch
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/Keming-Shen/MotionSurf.git /tmp/MotionSurf
mkdir -p .claude/skills
cp -r /tmp/MotionSurf/.claude/skills/paper-read-batch .claude/skills/paper-read-batch

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Paper Read Batch in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Paper Read Batch on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Paper Read Batch is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Paper Read Batch

你负责批量分析 MotionSurf 仓库中已经存在于 paper/tex_source/ 下的多篇论文，并将分析结果逐篇写入：

ReadNote/ResearchPaper/<PaperName>/note.md
ReadNote/ResearchPaper/<PaperName>/meta.json

适用场景

当用户有以下意图时使用本 skill：

想批量分析本地 markdown 论文
想处理所有尚未生成研究笔记的论文
想按标题、目录名或匹配条件分析一组本地论文
想先 dry-run 看看哪些论文会被处理

以下情况不要把它当主工具：

用户只想分析单篇论文：交给 paper-read-local
用户想维护领域总览：交给 motion-overview
用户想直接从 PDF 做 OCR 分析：当前不支持，仍以 paper/tex_source 为主输入

输入原则

本 skill 只使用本地 markdown 资产：paper/tex_source/*/*.md。
候选选择优先依赖 ReadNote/Wiki/paper_registry.json。
是否跳过已完成条目，以 note.md + meta.json 是否都已存在为准。
单篇 note/meta 的写法统一复用 paper-read-local / readpaper-core 既有规范。
batch 只负责候选筛选、dry-run、调度与汇报；单篇论文的语义生成必须复用 paper-read-local 的同一条 LLM 链路。

运行要求

默认行为应保守：无参数时只处理少量未完成候选，不直接扫完整个库。
--all 才表示显式全量处理。
应清楚汇报：
- 选中了哪些论文
- 跳过了哪些论文以及原因
- 成功 / 失败 / 跳过统计

汇报要求

回复时简短说明：

本次批量处理的选择方式
生成或跳过了多少论文
是否建议随后重跑 bootstrap_registry.py 以把新 meta 并回 registry

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

scripts/batch_generate_research_notes.py9 KB

Frequently asked questions

What does the Paper Read Batch AI skill do?

Why use Paper Read Batch on TypingMind?

Because you install it once and use it with any model. Paper Read Batch is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Paper Read Batch in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Keming-Shen/MotionSurf/tree/main/.claude/skills/paper-read-batch. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Paper Read Batch?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Paper Read Batch?

As many as you like. As long as a model supports skills, you can use Paper Read Batch with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Paper Read Batch AI skill free?

It is published on GitHub by Keming-Shen. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview