Paper Reading Workflow

Paper Reading Workflow

Core Rule

Use this as the default paper-reading router for the user.

The target output is normally one polished Chinese Obsidian Markdown note, not three separate reports. Treat deeppapernote as the main production workflow, and force two lenses into its planning and final note:

• literature-method-data-miner: method, data, experiment, figure/table evidence, reproducibility, reusable ideas.
• scientific-critical-thinking: evidence strength, overclaiming, limitations, bias, generalization, and replication risk.

Only create separate method-mining or critique files when the user explicitly asks for comparison, audit, review, or multi-paper synthesis.

Required Sub-Skills

• REQUIRED MAIN SKILL: Use deeppapernote for a single-paper deep note, PDF processing, note planning, figure/table placement, linting, and Obsidian save.
• REQUIRED LENS: Use literature-method-data-miner whenever the user asks or implies "这篇文献怎么做的", "方法", "数据", "实验", "复现", or "借鉴".
• REQUIRED LENS: Use scientific-critical-thinking before finalizing the note whenever the user wants quality judgment, limitations, evidence strength, claim boundaries, or serious reading rather than a shallow summary.
• REQUIRED FIGURE/TABLE LENS: Use scientific-explanatory-schematics rules whenever the note needs original Figure/Table insertion, Figure/Table unpacking, technical-route diagrams, mechanism diagrams, or supplemental schematics.

If one of these skills is unavailable, say which skill is missing and continue with the same checklist manually.

Workflow

1. Resolve the paper source.

   • Prefer the user's local PDF path, then DOI/arXiv/URL.
   • If identity is ambiguous, clarify before writing.
   • For deeppapernote, honor its Python and pipeline requirements instead of shortcutting.

2. Run the DeepPaperNote pipeline as the main path.

   • Produce the normal evidence bundle, figure/table decisions, note plan, linted final note, and Obsidian save.
   • Do not present an abstract-only or title-only summary as a finished reading note.

3. Force method/data coverage into the note plan.

   • Research question and task definition.
   • Data/materials, datasets, samples, splits, sources, or corpus.
   • Method workflow with input, operation, and output.
   • Model/software/parameters/statistics/evaluation protocol.
   • Main figure/table evidence and key numbers.
   • Supplement/code/repository/reproducibility details.
   • What can be reused in the user's project and what is risky.

4. Force original Figure/Table coverage into the note plan.

   • Inventory all source visuals that affect method understanding, task definition, main results, ablations, comparisons, limitations, or project decisions.
   • Insert high-value original figures/tables when a usable image or crop is available.
   • If an important visual cannot be inserted, add a text-only unpacking block with the source location and concrete reason.
   • For every inserted or text-only high-value visual, explain: what is shown, which route step it corresponds to, how to read the result, what conclusion it supports, what it cannot prove, and what it suggests for the user's project.
   • Use self-drawn schematics only as optional interpretation; caption them as 项目解读示意图，非原文证据.

5. Force critical-thinking coverage before final save.

   • What the paper proves.
   • What it does not prove.
   • Whether conclusions are proportional to evidence.
   • Whether results depend on narrow datasets, tasks, metrics, model choices, or prompts.
   • Missing ablations, weak baselines, statistical issues, hallucination risk, bias/confounding, and generalization limits.
   • Concrete follow-up checks or replication experiments.

6. Save one integrated Chinese note unless instructed otherwise.

   • Keep DeepPaperNote's required structure.
   • Add method/data and rigor checks as sections or subsections, not detached chat commentary.
   • Prefer durable Obsidian output under the user's knowledge-base path when provided.

Success Criteria

A paper-reading run is successful only if the final artifact can answer these questions:

Common Mistakes

• Do not generate three long files by default. The normal output is one integrated DeepPaperNote-style note.
• Do not treat literature-method-data-miner as a replacement for DeepPaperNote; it is a method/data extraction lens.
• Do not treat scientific-critical-thinking as generic criticism; tie every critique to evidence, experiment design, result interpretation, or missing information.
• Do not leave valuable original figures as unexamined thumbnails or one-line captions; decode the figure/table and state the evidence boundary.
• Do not call the run complete before DeepPaperNote's required lint/review/save stages are actually complete.
• Do not leave useful judgments only in chat if the user asked for a knowledge-base artifact; write them into the note.

Reusable Invocation

When the user asks to read a paper, apply this instruction internally:

Use DeepPaperNote as the main workflow. In the note plan and final Chinese Obsidian note, force the literature-method-data-miner checklist for method/data/experiment/reproducibility/reuse, and force the scientific-critical-thinking checklist for evidence strength, claim boundaries, limitations, overclaiming, and replication risk. Output one integrated Markdown note unless the user explicitly asks for separate files.
Also force the scientific-explanatory-schematics Figure/Table rule: every high-value original visual should be inserted and explained when usable, or explicitly unpacked without image with the reason it was not inserted.