/submission-guide
This skill covers academic journal submission, referee responses, and revision management. Use when the user is preparing a manuscript for submission, formatting for a specific journal, responding to referees, or managing revisions. Triggers on "submit", "referee", "revision",
$ npx -y skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill submission-guide --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/submission-guide
Context preview
The summary Claude sees to decide when to auto-load this skill.
This skill covers academic journal submission, referee responses, and revision management. Use when the user is preparing a manuscript for submission, formatting for a specific journal, responding to referees, or managing revisions. Triggers on "submit", "referee", "revision",
SKILL.md
submission-guide.SKILL.mdname: submission-guide
argument-hint: "<journal name or submission task>"
description: >-
This skill covers academic journal submission, referee responses, and revision management. Use when the user is preparing a manuscript for submission, formatting for a specific journal, responding to referees, or managing revisions. Triggers on "submit", "referee", "revision", "R&R", "response letter", "journal", "formatting", "submission", "resubmit", "cover letter", "referee report", "revise and resubmit".
Journal Submission
Reference for the full journal submission lifecycle: pre-submission preparation, journal-specific formatting, referee response strategy, and revision management. Covers conventions for top journals in economics, finance, political science, sociology, marketing, and statistics.
When to Use This Skill
Use when the user is:
- Preparing a manuscript for first submission to an academic journal
- Formatting a paper to meet a specific journal's requirements
- Writing a response letter to referee reports after receiving an R&R
- Managing tracked changes and revision logistics
- Anticipating common referee objections for a particular empirical method
- Writing a cover letter to the editor
Skip when:
- The task is choosing an empirical method (use `causal-inference` or `empirical-playbook` skill)
- The task is structural estimation implementation (use `structural-modeling` skill)
- The task is setting up a replication package (use `reproducible-pipelines` skill)
Pre-Submission Checklist
Complete every item before submitting. Missing any one of these is a common reason for desk rejection or delayed processing.
Manuscript
- [ ] **Title**: Concise, informative, no unnecessary jargon. Under 15 words is ideal.
- [ ] **Abstract**: States the question, method, data, and main finding. Respects journal word limit (typically 100-150 words for econ journals).
- [ ] **JEL codes**: 2-4 codes, primary code first. Check https://www.aeaweb.org/econlit/jelCodes.php for current classification.
- [ ] **Keywords**: 3-6 terms not already in the title.
- [ ] **Introduction**: Clearly states contribution in first two paragraphs. Includes a "roadmap" paragraph at the end.
- [ ] **Literature review**: Positions paper relative to 3-5 closest papers. Explains what this paper does that they do not.
- [ ] **Identification section**: Formal statement of assumptions, not just prose. Numbered assumptions preferred.
- [ ] **Results**: Main results first, robustness second. Do not bury the lead.
- [ ] **Conclusion**: No new results. Discuss limitations honestly. Suggest future work briefly.
- [ ] **References**: Every citation in text appears in references and vice versa. Use a bibliography manager (BibTeX/BibLaTeX).
- [ ] **Anonymization**: Remove all author-identifying information. Check PDF metadata, acknowledgments, file paths in code, dataset names that reveal institution.
- [ ] **Page/word count**: Within journal limits. Many journals have strict limits (e.g., AER Papers & Proceedings: 5 pages).
- [ ] **Spell check and grammar**: Run a final pass. Typos in the abstract signal carelessness.
- [ ] **Agent review**: Run the `journal-referee` agent for an adversarial review and the `econometric-reviewer` agent to audit tables against code output.
Tables
- [ ] **Self-contained**: Each table has a descriptive title and notes explaining all variables, sample, and significance stars.
- [ ] **Significance stars**: Use journal convention. Most econ journals: `* p<0.10, ** p<0.05, *** p<0.01`. Some journals (QJE) discourage stars entirely.
- [ ] **Standard errors**: Report in parentheses below coefficients. State clustering level in notes.
- [ ] **Number of observations**: Report N for every regression. Report N by group for DiD/panel.
- [ ] **R-squared or fit measure**: Report adjusted R-squared, within R-squared for FE models, or pseudo R-squared for nonlinear models.
- [ ] **Decimal places**: 2-3 significant digits. Do not report 8 decimal places from Stata/R output.
- [ ] **Consistent formatting**: Same variable names across all tables. Same order of controls.
- [ ] **No vertical lines**: Use horizontal rules only (booktabs style in LaTeX).
Figures
- [ ] **Vector format**: PDF or EPS for line plots and diagrams. High-resolution PNG (300+ DPI) only for heatmaps or photos.
- [ ] **Readable in grayscale**: Use shapes/patterns in addition to colors. At least 20% of readers print in black and white.
- [ ] **Axis labels**: Clear, with units. Font size readable when figure is scaled to journal column width.
- [ ] **No chartjunk**: Remove gridlines, unnecessary legends, 3D effects, excessive tick marks.
- [ ] **Consistent style**: All figures use the same font, color palette, and line weights.
- [ ] **Source note**: State data source and sample period below each figure.
Appendix and Online Appendix
- [ ] **Appendix**: Proofs, additional tables referenced in the main text, variable definitions.
- [ ] **Online appendix**: Supplementary results that support but are not essential to the main argument.
- [ ] **Cross-references**: Every appendix item is referenced from the main text. No orphan appendix tables.
- [ ] **Separate file**: Some journals require the online appendix as a separate PDF. Check submission guidelines.
Replication Package
- [ ] **Data**: All data files, or clear instructions for obtaining restricted-access data.
- [ ] **Code**: All scripts from raw data to final tables/figures. Master script that runs everything in order.
- [ ] **README**: Describes file structure, software requirements, runtime estimate, expected output.
- [ ] **Seeds**: All random number generator seeds set and documented.
- [ ] **Versions**: Software versions pinned (R/Python/Stata version, package versions).
- [ ] **License**: Data license and code license specified.
- [ ] **Tested**: Run the entire pipeline from scratch on a clean machine or container.
Cover Letter
- [ ] **Editor na
Read more
name: submission-guide argument-hint: "<journal name or submission task>" description: >- This skill covers academic journal submission, referee responses, and revision management. Use when the user is preparing a manuscript for submission, formatting for a specific journal, responding to referees, or managing revisions. Triggers on "submit", "referee", "revision", "R&R", "response letter", "journal", "formatting", "submission", "resubmit", "cover letter", "referee report", "revise and resubmit".
Journal Submission
Reference for the full journal submission lifecycle: pre-submission preparation, journal-specific formatting, referee response strategy, and revision management. Covers conventions for top journals in economics, finance, political science, sociology, marketing, and statistics.
When to Use This Skill
Use when the user is:
- Preparing a manuscript for first submission to an academic journal
- Formatting a paper to meet a specific journal's requirements
- Writing a response letter to referee reports after receiving an R&R
- Managing tracked changes and revision logistics
- Anticipating common referee objections for a particular empirical method
- Writing a cover letter to the editor
Skip when:
- The task is choosing an empirical method (use `causal-inference` or `empirical-playbook` skill)
- The task is structural estimation implementation (use `structural-modeling` skill)
- The task is setting up a replication package (use `reproducible-pipelines` skill)
Pre-Submission Checklist
Complete every item before submitting. Missing any one of these is a common reason for desk rejection or delayed processing.
Manuscript
- [ ] **Title**: Concise, informative, no unnecessary jargon. Under 15 words is ideal.
- [ ] **Abstract**: States the question, method, data, and main finding. Respects journal word limit (typically 100-150 words for econ journals).
- [ ] **JEL codes**: 2-4 codes, primary code first. Check https://www.aeaweb.org/econlit/jelCodes.php for current classification.
- [ ] **Keywords**: 3-6 terms not already in the title.
- [ ] **Introduction**: Clearly states contribution in first two paragraphs. Includes a "roadmap" paragraph at the end.
- [ ] **Literature review**: Positions paper relative to 3-5 closest papers. Explains what this paper does that they do not.
- [ ] **Identification section**: Formal statement of assumptions, not just prose. Numbered assumptions preferred.
- [ ] **Results**: Main results first, robustness second. Do not bury the lead.
- [ ] **Conclusion**: No new results. Discuss limitations honestly. Suggest future work briefly.
- [ ] **References**: Every citation in text appears in references and vice versa. Use a bibliography manager (BibTeX/BibLaTeX).
- [ ] **Anonymization**: Remove all author-identifying information. Check PDF metadata, acknowledgments, file paths in code, dataset names that reveal institution.
- [ ] **Page/word count**: Within journal limits. Many journals have strict limits (e.g., AER Papers & Proceedings: 5 pages).
- [ ] **Spell check and grammar**: Run a final pass. Typos in the abstract signal carelessness.
- [ ] **Agent review**: Run the `journal-referee` agent for an adversarial review and the `econometric-reviewer` agent to audit tables against code output.
Tables
- [ ] **Self-contained**: Each table has a descriptive title and notes explaining all variables, sample, and significance stars.
- [ ] **Significance stars**: Use journal convention. Most econ journals: `* p<0.10, ** p<0.05, *** p<0.01`. Some journals (QJE) discourage stars entirely.
- [ ] **Standard errors**: Report in parentheses below coefficients. State clustering level in notes.
- [ ] **Number of observations**: Report N for every regression. Report N by group for DiD/panel.
- [ ] **R-squared or fit measure**: Report adjusted R-squared, within R-squared for FE models, or pseudo R-squared for nonlinear models.
- [ ] **Decimal places**: 2-3 significant digits. Do not report 8 decimal places from Stata/R output.
- [ ] **Consistent formatting**: Same variable names across all tables. Same order of controls.
- [ ] **No vertical lines**: Use horizontal rules only (booktabs style in LaTeX).
Figures
- [ ] **Vector format**: PDF or EPS for line plots and diagrams. High-resolution PNG (300+ DPI) only for heatmaps or photos.
- [ ] **Readable in grayscale**: Use shapes/patterns in addition to colors. At least 20% of readers print in black and white.
- [ ] **Axis labels**: Clear, with units. Font size readable when figure is scaled to journal column width.
- [ ] **No chartjunk**: Remove gridlines, unnecessary legends, 3D effects, excessive tick marks.
- [ ] **Consistent style**: All figures use the same font, color palette, and line weights.
- [ ] **Source note**: State data source and sample period below each figure.
Appendix and Online Appendix
- [ ] **Appendix**: Proofs, additional tables referenced in the main text, variable definitions.
- [ ] **Online appendix**: Supplementary results that support but are not essential to the main argument.
- [ ] **Cross-references**: Every appendix item is referenced from the main text. No orphan appendix tables.
- [ ] **Separate file**: Some journals require the online appendix as a separate PDF. Check submission guidelines.
Replication Package
- [ ] **Data**: All data files, or clear instructions for obtaining restricted-access data.
- [ ] **Code**: All scripts from raw data to final tables/figures. Master script that runs everything in order.
- [ ] **README**: Describes file structure, software requirements, runtime estimate, expected output.
- [ ] **Seeds**: All random number generator seeds set and documented.
- [ ] **Versions**: Software versions pinned (R/Python/Stata version, package versions).
- [ ] **License**: Data license and code license specified.
- [ ] **Tested**: Run the entire pipeline from scratch on a clean machine or container.
Cover Letter
- [ ] **Editor na
📌 文档结构(2026-07-22 起): 本文件是中文默认入口 —— banner + badges + 信任面 + 9 阶段流水线速览 + 76 行合集总表。 每个合集的完整描述、按用途分组、精确数字、验证方法在 docs/CONTENT_ZH.md(扩展正文,总表行内的 → 直接跳转到对应锚点)。 English version: README-en.md · 中文扩展正文:docs/CONTENT_ZH.md · README-zh-CN.md 已弃用(重定向占位) 🌐 语言: English |
Other skills on auto-empirical-research-skills.
- /pipeline
Classical end-to-end empirical analysis workflow in the traditional Python econometric stack — pandas + numpy + scipy + statsmodels + linearmodels + pyfixest + rdrobust + econml + causalml + matplotlib/seaborn. **Defaults to economics empirical-paper style** (AER / QJE / AEJ) —
Open skill - /pipeline
Classical end-to-end empirical analysis workflow in the modern tidyverse + econometrics R ecosystem — dplyr + tidyr + haven + fixest + sandwich + lmtest + clubSandwich + AER + ivreg + did + bacondecomp + HonestDiD + eventstudyr + rdrobust + rddensity + Synth + gsynth + synthdid
Open skill - /pipeline
Classical end-to-end empirical analysis workflow in the traditional Stata ecosystem — native Stata + reghdfe + ivreg2 + csdid + did_imputation + eventstudyinteract + sdid + rdrobust + rddensity + synth + synth_runner + psmatch2 + teffects + ebalance + coefplot + esttab + asdoc +
Open skill - /00-Full-empirical-analysis-skill_StatsPAI
Use when the user asks to run a full empirical / causal analysis in Python — by default in the style of an applied economics paper (AER / QJE / JPE / ReStud / AEJ) with DID / RD / IV / SCM / DML / matching, written-out estimating equation + identifying assumption, Table 1 /
Open skill - /00.1-Full-empirical-analysis-skill_Python
Classical end-to-end empirical analysis workflow in the traditional Python econometric stack — pandas + numpy + scipy + statsmodels + linearmodels + pyfixest + rdrobust + econml + causalml + matplotlib/seaborn. **Defaults to economics empirical-paper style** (AER / QJE / AEJ) —
Open skill - /00.2-Full-empirical-analysis-skill_Stata
Classical end-to-end empirical analysis workflow in the traditional Stata ecosystem — native Stata + reghdfe + ivreg2 + csdid + did_imputation + eventstudyinteract + sdid + rdrobust + rddensity + synth + synth_runner + psmatch2 + teffects + ebalance + coefplot + esttab + asdoc +
Open skill

