论文精读器(三遍读法 + 提问清单)

SKILL效率
效率 未标注权限 许可证不明确
安装这个技能

论文与长文精读工具。当用户问这篇论文讲了什么、怎么快速读懂一篇 paper、文献综述怎么读、长文看不下去、怎么判断论文靠不靠谱、怎么记笔记才有用、读了就忘怎么办时说用。输出三遍读法的具体问题清单、30 秒筛选法、质量评估清单与卡片笔记模板。

一句话选型结论

按资料字段整理

论文精读器(三遍读法 + 提问清单)是效率类的 Agent Skill,安装方式未标注,权限级别未标注,许可证不明确,有可直接复制的安装命令。技能本质是给模型读的说明书,效果取决于模型与客户端;装完先用一个小任务验证,再放进正式流程。

分类效率 安装方式未标注 权限级别未标注权限 许可证许可证不明确
累计安装 未标注 本周 未标注
GitHub 星标 未标注 仓库 未标注
下载量 未标注 技能市场下载数
权限级别 未标注权限 安装前请确认风险范围
许可证 许可证不明确 未说明

安装

未标注
在支持 Skills 的客户端里执行,装完问一句「你有哪些技能」验证
skillhub install user_fc5d2263/paper-deep-reader
  1. 1
    确认客户端支持

    确认你的客户端支持 Skills(Claude、Codex、Cursor 等),并升级到较新的版本。

  2. 2
    拿到技能文件

    执行上面的命令安装;也可以把仓库里的 SKILL.md 手动放进客户端的 skills 目录。

  3. 3
    刷新技能列表

    重新打开客户端,或刷新技能列表,让新放进来的技能被加载。

  4. 4
    验证是否生效

    问一句「你有哪些技能」,确认列表里出现它,再拿一个小任务试跑。

技能档案

效率
字段来自技能仓库与公开索引,中文说明由本站标注
作者 / 维护方user_fc5d2263仓库 未标注 · 版本 未标注
宿主客户端未标注技能可被这些客户端加载
安装方式未标注安装包 community
权限级别未标注权限安装前请确认风险范围
许可证未说明许可证不明确,商用前请自行确认条款
仓库可用性available技能仓库当前是否可访问
最近核验2026-11-06上游最后核验时间 · 数据更新 2026-11-06
正文体量11.1 KBSKILL.md 原文大小,越大说明说明书写得越细

典型使用场景

3 类
按分类整理的常见用法,具体以 SKILL.md 为准
整理待办与日程

把零散任务收进清单,排出优先级。

批量处理重复任务

把固定动作做成模板,重复执行。

把流程写成清单

把口头流程整理成可复用的步骤。

选择建议

装之前先看这几条
按条目字段给出的判断,不替你决定用不用

值得选的地方

  • 有可直接复制的安装命令,不用自己翻文档找入口。

先想清楚的地方

  • 没有标注权限级别,实际能做什么要装好后确认。
  • 许可证不明确,商用或二次分发前先到仓库确认条款。
  • 没有做站内核验,内容以作者仓库为准。
  • 技能只是说明书,实际效果取决于模型与客户端,装完先用小任务试一遍。

更适合

  • 需要在效率场景里给模型补一套做法的人。
  • 愿意先读一遍 SKILL.md、确认它会让模型做什么的人。

不太适合

  • 对许可证要求很严、必须明确可商用的人。
  • 只想装完就自动变强、不打算看说明书的人。

同类对比

6 个同类
同分类里挑最接近的几条,字段以各自详情页为准
技能权限级别安装方式累计安装宿主客户端安装命令
论文精读器(三遍读法 + 提问清单)当前 未标注权限 未标注 未标注 未标注 有
Nano PDF 文档 联网访问 ClawHub 市场 424.9 万 OpenClaw 有
自动更新程序 浏览器控制 ClawHub 市场 296.4 万 OpenClaw 有
Gemini 助手 联网访问 ClawHub 市场 254.7 万 OpenClaw 有
word DOCX 文档 联网访问 ClawHub 市场 239.6 万 OpenClaw 有
Excel XLSX 前端 联网访问 ClawHub 市场 227.0 万 OpenClaw 有

SKILL.md 全文

11.1 KB
模型实际读到的说明书原文,来自技能仓库

Paper Deep Reader

Use this skill to read one selected paper deeply each time and turn it into a durable, evidence-based note.

This skill is for serious paper reading, not for rewriting the abstract in cleaner prose.

First load

Before drafting, read these core references:

  • {baseDir}/routing-rules.md
  • {baseDir}/paper-taxonomy.md
  • {baseDir}/references/reading-workflow.md
  • {baseDir}/references/note-template-base.md
  • {baseDir}/references/output-contract.md
  • {baseDir}/references/checklists/general.md

Then route the paper and load:

  • exactly one primary adapter
  • one to three evidence checklist packs
  • an optional secondary adapter only when a second contribution is independently load-bearing
  • an optional domain overlay only if one exists in the repository and materially improves faithfulness

Adapters currently in use

  • {baseDir}/references/adapters/theory-math-stats.md
  • {baseDir}/references/adapters/method-algorithm.md
  • {baseDir}/references/adapters/benchmark-evaluation.md
  • {baseDir}/references/adapters/dataset-resource.md
  • {baseDir}/references/adapters/empirical-econ.md
  • {baseDir}/references/adapters/systems.md
  • {baseDir}/references/adapters/survey-synthesis.md
  • {baseDir}/references/adapters/replication-negative-result.md
  • {baseDir}/references/adapters/physics.md
  • {baseDir}/references/adapters/quant-finance.md

Evidence checklist packs currently in use

  • {baseDir}/references/checklists/general.md
    Always run this first.
  • {baseDir}/references/checklists/theory-math-stats.md
  • {baseDir}/references/checklists/proof-rigor.md
  • {baseDir}/references/checklists/experimental-eval.md
  • {baseDir}/references/checklists/ablation-and-mechanism-isolation.md
  • {baseDir}/references/checklists/robustness-and-ood.md
  • {baseDir}/references/checklists/benchmark-fairness-and-contamination.md
  • {baseDir}/references/checklists/reproducibility-and-compute.md
  • {baseDir}/references/checklists/empirical.md
  • {baseDir}/references/checklists/systems.md
  • {baseDir}/references/checklists/physics.md
  • {baseDir}/references/checklists/quant.md

Primary objective

Produce a note that lets a strong graduate student answer all of the following without reopening the paper:

  1. What problem does the paper study?
  2. Why does that problem matter?
  3. What is the paper's main move?
  4. How does the technical mechanism, argument, benchmark, dataset, or system work step by step?
  5. What assumptions, approximations, identification logic, workload assumptions, or construction choices are doing the real work?
  6. What evidence actually supports the main claims?
  7. What is genuinely strong, weak, narrow, reusable, or fragile about the paper?

Non-goals

Do not use this skill for:

  • shallow abstract rewrites
  • vague praise or hype language
  • multi-paper literature reviews unless the selected paper itself is a survey or synthesis
  • papers you have not actually read beyond title and abstract

Operating principle

Treat paper reading as reconstruction plus judgment.

Your job is not only to say what the authors claim. Your job is to reconstruct the paper's intellectual structure, route it faithfully, trace claims to evidence, and record where a careful reader should trust, doubt, reuse, or extend the work.

Required execution protocol

Follow this sequence.

1. Build a paper map before prose

Before writing the note, identify:

  • research question
  • problem setting
  • main move
  • key technical objects
  • main claim(s)
  • evidence backbone
  • where the paper's intellectual load actually lives
  • the primary failure risk if the paper is weaker than advertised

Write a short internal map in this form:

> The paper studies __ in the setting . Its main move is . It claims , supported mainly by . The key technical objects are . The real intellectual load sits in . The main failure risk is __.

If you cannot write this map, keep reading before drafting.

2. Route the paper before analyzing it

Use the routing rules in {baseDir}/routing-rules.md.

Create an internal route record in this form:

Primary adapter:
Secondary adapter:
Evidence packs:
Domain overlay:
Route confidence:
Why this route:

Routing principles:

  • choose exactly one primary adapter
  • add a secondary adapter only if a second contribution is independently central
  • choose one to three evidence packs that are most likely to change the final verdict if the evidence is weak
  • use a domain overlay only when the field has recurring objects, overclaims, or traps that deserve active reminders
  • prefer the simplest faithful route

Do not route only by title words or surface buzzwords. Route by the paper's real intellectual load.

3. Read in passes

Do not read linearly from top to bottom unless the paper is unusually simple.

Pass A: framing

Read title, abstract, introduction, conclusion, and figure or table captions.
Goal: identify what the authors want the reader to believe and what kind of contribution they think they are making.

Pass B: technical core

Read the model, method, theory, derivation, benchmark construction, dataset section, or system design sections carefully.
Reconstruct the main equations, estimators, algorithms, proof ideas, task definitions, sampling logic, or tradeoffs.

Pass C: evidence

Read experiments, empirics, case studies, benchmarks, robustness checks, appendix evidence, or construction validation that bears on the main claims.

Pass D: limits and context

Read limitations, related work selectively, and appendix sections needed to judge the claims fairly.

Do not stop at the main body if a central claim is only supported in the appendix or supplement.

4. Use the scripts to reduce drift

If the scripts in {baseDir}/scripts/ are available, use them as a structured drafting aid. Before using any script, read its documentation {baseDir}/scripts/README.md and understand what it does and does not do.

Recommended order:

  1. scaffold_note.py
  2. build_paper_map.py
  3. route the paper manually using {baseDir}/routing-rules.md
  4. build_notation_table.py
  5. build_claim_matrix.py
  6. build_limitation_ledger.py
  7. render_final_note.py

Use the scripts to create first drafts of the note scaffold and internal artifacts. Then review and correct them against the paper. The scripts are helpers, not authorities.

5. Prefer scripted artifacts when the note will be saved

When the user wants a saved markdown note, prefer this flow:

  • scaffold the note from {baseDir}/references/note-template-base.md
  • draft the paper map
  • route the paper explicitly
  • draft the notation table when notation is nontrivial
  • draft the claim-evidence matrix for the main claims
  • draft the limitation ledger
  • render the final note and then revise it manually for accuracy and pedagogy

If the note is short and purely conversational, you may skip the scripts, but you must still follow the same intellectual protocol.

Mandatory internal outputs

Before finalizing the note, build these internal structures. They can remain implicit unless the user asks for them, but the final note must reflect them.

A. Paper map

A compact statement of problem, setting, contribution, evidence backbone, and main failure risk.

B. Route record

A compact routing decision with:

  • primary adapter
  • optional secondary adapter
  • one to three evidence packs
  • optional domain overlay
  • route confidence
  • short justification

C. Notation table

When notation is nontrivial, record:

  • symbol
  • meaning
  • type / shape / domain
  • units if relevant
  • where it first matters

D. Claim-evidence matrix

For each major claim, record:

  • the claim itself
  • whether it is the authors' stated claim or your inference
  • what evidence supports it
  • where that evidence appears
  • how strong the support is
  • any caveat or missing check

E. Limitation ledger

Separate:

  • limitations explicitly acknowledged by the paper
  • limitations you infer as a careful reader

Core rules

  1. Read before judging. Never infer the entire contribution from title and abstract alone.
  2. Separate authors' claims from your evaluation. Mark the distinction clearly.
  3. Preserve the mathematical or technical spine. Keep the note anchored in equations, estimators, theorem statements, algorithms, benchmark construction, data construction, identification logic, or system tradeoffs when relevant.
  4. Trace claims to evidence. Strong statements require concrete support from sections, figures, tables, appendices, proofs, or benchmarks.
  5. Explain mechanisms, not just outcomes. Answer why the method, argument, benchmark, dataset design, or system should work and when it should fail.
  6. Prefer exactness over praise. Replace words like “powerful,” “novel,” or “impressive” with concrete statements.
  7. Do not hide uncertainty. If the paper is unclear, underspecified, overstated, or weakly evidenced, say so directly.
  8. Use scripts as drafts, not verdicts. Heuristic extraction must always be checked against the paper.
  9. Choose the simplest faithful route. More adapters or packs do not automatically make a better note.

Adapter and checklist rule

Always keep the common structure from the base template, then expand or tighten sections using the routed adapter and chosen evidence packs.

  • Use one adapter for a clean single-contribution paper.
  • Use two adapters only when the paper is genuinely mixed and the second contribution is independently load-bearing.
  • Do not bolt on irrelevant sections just to satisfy a template.
  • Run general.md first, then the chosen evidence packs, then any adapter-specific or domain-specific checks.

Writing contract for the final note

Follow the output contract in {baseDir}/references/output-contract.md. Use the base note template as the default scaffold, then adapt it to the routed paper type and evidence profile.

Evidence rule

For every important conclusion in the note, ask:

  1. Is this the authors' claim, or my inference?
  2. What concrete evidence supports it?
  3. How strong is that support?
  4. What would make me trust it less?
  5. Did I record that caveat in the note?

If you cannot answer these questions, keep reading or weaken the statement.

常见问题

5 问
答案由本站依据条目字段整理
论文精读器(三遍读法 + 提问清单)怎么安装?

在支持 Skills 的客户端里执行:skillhub install user_fc5d2263/paper-deep-reader。安装方式为未标注。装完刷新技能列表或重开客户端。

论文精读器(三遍读法 + 提问清单)支持哪些客户端?

资料没有标注宿主客户端,但只要客户端支持 Skills(Claude、Codex、Cursor 等),一般都能加载。

论文精读器(三遍读法 + 提问清单)权限高吗,安全吗?

权限级别为未标注权限。安装前先看它会读取或写入哪些内容。

论文精读器(三遍读法 + 提问清单)收费吗?

本站不代收费用,也没有标注具体价格。是否收费取决于技能本身和所用的模型或客户端,正式使用前按作者说明确认。

论文精读器(三遍读法 + 提问清单)用什么许可证?

许可证标注为 未说明(许可证不明确)。商用或二次分发前请到仓库确认条款原文。

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技能内容以作者仓库为准;分类、权限级别与许可证状态的中文说明为中文整理,最近核验 2026-11-06。