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:
- - INLINECODE0
- INLINECODE1
- INLINECODE2
- INLINECODE3
- INLINECODE4
- INLINECODE5
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
- - INLINECODE6
- INLINECODE7
- INLINECODE8
- INLINECODE9
- INLINECODE10
- INLINECODE11
- INLINECODE12
- INLINECODE13
- INLINECODE14
- INLINECODE15
Evidence checklist packs currently in use
Always run this first.
- - INLINECODE17
- INLINECODE18
- INLINECODE19
- INLINECODE20
- INLINECODE21
- INLINECODE22
- INLINECODE23
- INLINECODE24
- INLINECODE25
- INLINECODE26
- INLINECODE27
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?
- Why does that problem matter?
- What is the paper's main move?
- How does the technical mechanism, argument, benchmark, dataset, or system work step by step?
- What assumptions, approximations, identification logic, workload assumptions, or construction choices are doing the real work?
- What evidence actually supports the main claims?
- 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:
CODEBLOCK0
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. INLINECODE31
- INLINECODE32
- route the paper manually using INLINECODE33
- INLINECODE34
- INLINECODE35
- INLINECODE36
- INLINECODE37
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 INLINECODE38
- 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.
- Separate authors' claims from your evaluation. Mark the distinction clearly.
- 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.
- Trace claims to evidence. Strong statements require concrete support from sections, figures, tables, appendices, proofs, or benchmarks.
- Explain mechanisms, not just outcomes. Answer why the method, argument, benchmark, dataset design, or system should work and when it should fail.
- Prefer exactness over praise. Replace words like “powerful,” “novel,” or “impressive” with concrete statements.
- Do not hide uncertainty. If the paper is unclear, underspecified, overstated, or weakly evidenced, say so directly.
- Use scripts as drafts, not verdicts. Heuristic extraction must always be checked against the paper.
- 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?
- What concrete evidence supports it?
- How strong is that support?
- What would make me trust it less?
- Did I record that caveat in the note?
If you cannot answer these questions, keep reading or weaken the statement.
论文深度精读
使用此技能每次深入精读一篇选定论文,并将其转化为持久、基于证据的笔记。
此技能适用于严肃的论文阅读,而非以更清晰的措辞重写摘要。
首次加载
在起草之前,请阅读以下核心参考资料:
- - {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
然后对论文进行路由并加载:
- - 恰好一个主适配器
- 一到三个证据清单包
- 一个可选的辅助适配器,仅当第二个贡献独立承担重要负载时
- 一个可选的领域覆盖层,仅当仓库中存在且能实质性提升忠实度时
当前使用的适配器
- - {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
当前使用的证据清单包
- - {baseDir}/references/checklists/general.md
始终首先运行此清单。
- - {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
主要目标
生成一份笔记,使一名优秀的研究生无需重新打开论文即可回答以下所有问题:
- 1. 论文研究什么问题?
- 该问题为何重要?
- 论文的主要创新点是什么?
- 技术机制、论证、基准测试、数据集或系统是如何逐步运作的?
- 哪些假设、近似、识别逻辑、工作负载假设或构建选择在真正起作用?
- 哪些证据实际支持了主要主张?
- 论文中哪些方面真正强大、薄弱、狭窄、可复用或脆弱?
非目标
不要将此技能用于:
- - 浅显的摘要重写
- 模糊的赞美或炒作性语言
- 多篇论文的文献综述,除非所选论文本身是综述或综合类文章
- 你仅阅读了标题和摘要而未实际阅读全文的论文
操作原则
将论文阅读视为重构加判断。
你的工作不仅是陈述作者的主张。你的工作是重构论文的知识结构,忠实地对其进行路由,将主张追溯到证据,并记录一个细心的读者应在何处信任、质疑、复用或扩展该工作。
必需执行协议
请遵循以下顺序。
1. 在撰写正文前构建论文地图
在撰写笔记之前,确定:
- - 研究问题
- 问题设定
- 主要创新点
- 关键技术对象
- 主要主张
- 证据主干
- 论文的知识负载实际所在
- 如果论文弱于宣传,主要失败风险是什么
以如下形式撰写一个简短的内部地图:
论文在设定下研究。其主要创新点是。它主张,主要由支持。关键技术对象是。真正的知识负载在于。主要失败风险是。
如果你无法写出此地图,请继续阅读后再起草。
2. 在分析论文之前进行路由
使用{baseDir}/routing-rules.md中的路由规则。
创建一个如下形式的内部路由记录:
markdown
主适配器:
辅助适配器:
证据包:
领域覆盖层:
路由置信度:
选择此路由的原因:
路由原则:
- - 选择恰好一个主适配器
- 仅当第二个贡献独立核心时才添加辅助适配器
- 选择一到三个最可能因证据薄弱而改变最终结论的证据包
- 仅当该领域存在值得主动提醒的反复出现的对象、过度主张或陷阱时,才使用领域覆盖层
- 优先选择最简单的忠实路由
不要仅根据标题词汇或表面流行词进行路由。要根据论文真正的知识负载进行路由。
3. 分轮次阅读
除非论文异常简单,否则不要从头到尾线性阅读。
轮次A:框架
阅读标题、摘要、引言、结论以及图表标题。
目标:确定作者希望读者相信什么,以及他们认为自己做出了何种贡献。
轮次B:技术核心
仔细阅读模型、方法、理论、推导、基准构建、数据集部分或系统设计部分。
重构主要方程、估计量、算法、证明思路、任务定义、采样逻辑或权衡。
轮次C:证据
阅读与主要主张相关的实验、实证、案例研究、基准测试、鲁棒性检查、附录证据或构建验证。
轮次D:局限性与背景
阅读局限性、选择性相关文献,以及公正判断主张所需的附录部分。
如果核心主张仅在附录或补充材料中得到支持,不要止步于正文。
4. 使用脚本减少偏差
如果{baseDir}/scripts/中的脚本可用,请将其用作结构化的起草辅助工具。在使用任何脚本之前,请阅读其文档{baseDir}/scripts/README.md,了解其功能与限制。
推荐顺序:
- 1. scaffoldnote.py
- buildpapermap.py
- 使用{baseDir}/routing-rules.md手动路由论文
- buildnotationtable.py
- buildclaimmatrix.py
- buildlimitationledger.py
- renderfinal_note.py
使用脚本创建笔记框架和内部产物的初稿。然后对照论文进行审查和修正。脚本是辅助工具,而非权威。
5. 当笔记需要保存时,优先使用脚本生成的产物
当用户希望保存为Markdown笔记时,优先采用以下流程:
- - 从{baseDir}/references/note-template-base.md搭建笔记框架
- 起草论文地图
- 明确路由论文
- 当符号体系不平凡时,起草符号表
- 为主要主张起草主张-证据矩阵
- 起草局限性账本
- 渲染最终笔记,然后手动修订以确保准确性和教学性
如果笔记简短且纯粹是对话式的,可以跳过脚本,但仍必须遵循相同的知识协议。
强制内部输出
在最终确定笔记之前,构建以下内部结构。除非用户要求,它们可以保持隐式,但最终笔记必须反映它们。
A. 论文地图
关于问题、设定、贡献、证据主干和主要失败风险的紧凑陈述。
B. 路由记录
包含以下内容的紧凑路由决策:
- - 主适配器
- 可选辅助适配器
- 一到三个证据包
- 可选领域覆盖层
- 路由置信度
- 简短理由
C. 符号表
当符号体系不平凡时,记录:
- - 符号
- 含义
- 类型/形状/域
- 相关单位
- 首次出现的重要位置
D. 主张-证据矩阵
对于每个主要主张,记录:
- - 主张本身
- 是作者陈述的主张还是你的推断
- 支持该主张的证据
- 该证据出现的位置
- 支持的强度
- 任何注意事项或缺失的检查
E. 局限性账本
区分:
- - 论文明确承认的局限性
- 你作为细心读者推断出的局限性
核心规则
- 1. 先阅读,后判断。 永远不要仅从标题和摘要推断全部贡献。
- 区分作者的主张与你的评价。 明确标记这一区别。
- 保留数学或技术主干。 在相关时,让笔记锚定在方程、估计量、定理陈述、算法、基准构建、数据构建、识别逻辑或系统权衡上。
- 将主张追溯到证据。 强有力的陈述需要来自章节、图表、附录、证明或基准测试的具体支持。
- 解释机制,而不仅仅是结果。 回答