bilingual chinese-english academic paper reading and latex report generation from research paper pdfs. use when the user uploads or references a research paper pdf and wants a structured latex reading note, paper summary, contribution analysis, method and equation explanation, representative baseline model explanation, term glossary, reproducibility assessment, or international research status analysis. first ground findings in the pdf; use web search only when the pdf lacks enough context for r
SkillScore73Maintained
Automatic
◆Research pack
Last verified 8/8/2026
What it changes
Passed 16 of 22 test cases with the skill, and 3 of 22 without it.
Without skill14%
With skill73%
Checks it passed that the model alone missed
The preamble includes \author{Generated by ChatGPT}.
The section heading is \section{重要名词解释 / Key Term Glossary}.
The method section includes a 直觉解释 / Intuitive Explanation subsection.
and 19 more in the full report
13 fixed3 passed either way6 still failing0 broke
Pass-rate lift
+59 pp
Tokens
+74%
Agent turns
0%
Response time
+19%
Model gemini-3.6-flashMeasured 8/8/2026v116 of 22 cases passed with skill
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 13 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 13
Prompt
I need a comprehensive paper reading report for the attached PDF formatted as a single ready-to-compile document. Please make the output a fully structured bilingual LaTeX file (Chinese first, English second) that details the main contributions, key mathematical formulas, representative baseline models, international research status, and potential limitations.
What was checked, without and with the skill
Checked
Without skill
With skill
The generated document includes all 15 required bilingual section headings.
Missed
Passed
The representative models section includes a tabular environment mapping models to their source and significance.
Missed
Passed
The output configures document geometry to a 1-inch margin using the geometry package.
Passed
Passed
case-03 · gemini-3.6-flash · 8/8/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md215 lines3 files
Paper LaTeX Review
Overview
Use this skill to turn a research paper PDF into a bilingual Chinese-English LaTeX review report. The report must prioritize the paper's own content, extract the truly important ideas, explain methods and representative comparison models, and assess reproducibility.
Source Policy
First analyze the PDF only.
Extract all claims that are available in the PDF: title, authors, venue if present, abstract, problem, contributions, method, equations, experiments, baselines, datasets, metrics, limitations, and reproducibility details.
Use web search only when the PDF lacks enough information for:
representative model background or method details,
current international status, SOTA, or mainstream research direction,
definitions of important technical terms,
code/data availability that is not stated in the PDF.
Clearly label every externally supplemented item as 外部补充 / External Supplement.
If a fact cannot be verified from the PDF or reliable external sources, write PDF 中未提供 / Not provided in the PDF or 未能确认 / Not verified instead of guessing.
Workflow
Read the PDF carefully and identify the paper type: theory, model architecture, dataset, benchmark, systems, empirical study, survey, or application paper.
Build a paper map:
research question,
motivation,
task definition,
proposed method,
important equations,
experiments and baselines,
stated contributions,
limitations and reproducibility evidence.
Decide which model comparisons are available from the PDF:
baselines in experimental tables,
models named in related work,
ablations that represent prior variants,
closest competing method discussed by the authors.
Explain representative models with method-level detail when possible:
Build, manipulate, execute, validate, and version-control Jupyter notebooks
programmatically. Use when working with .ipynb files, creating notebooks from
code, running parameterised analyses, diffing/merging notebooks in git,
stripping outputs, or converting notebooks to other formats. Triggers on:
jupyter, notebook, ipynb, nbformat, nbconvert, nbclient, papermill, nbdime,
cell, kernel, execute notebook, parameterise, notebook diff, notebook merge.