submission-guide
This skill covers academic journal submission, referee responses, and revision management
Install / Use
npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill submission-guideInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
Education & ResearchSupported Platforms
Tags
Our assessment of submission-guide
submission-guide scores 89/100 on our quality scale, 81st of 212 Education & Research skills we index (top 39%).
Its SKILL.md is 14 KB long, well organised into 28 sections with 1 code example: a thorough specification that gives an agent plenty to work with.
With 4,360 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 3 days ago, so submission-guide is actively maintained.
- No license is declared. By default that means all rights are reserved: you can read it, but reusing or redistributing it is not clearly permitted. Ask the author before building on it commercially.
- Its trust signals score 88/100, with 1 caution from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
submission-guide compared with similar skills
All 4 of these similar skills score higher than submission-guide; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| submission-guide (this skill)by brycewang-stanford | 89 | 4.4k | 3d ago | SKILL.md |
| last30days-skillby mvanhorn | 100 | 62.9k | 4d ago | CLAUDE.md |
| algorithmic-artby anthropics | 100 | 177.9k | 4d ago | SKILL.md |
| pptxby anthropics | 100 | 177.9k | 4d ago | SKILL.md |
| designby nextlevelbuilder | 100 | 130.2k | 5d ago | SKILL.md |
Frequently asked questions
- How do I install submission-guide?
- Run
npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill submission-guide. The install tabs above show the steps for each supported agent. - Which AI agents does submission-guide work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is submission-guide safe to use?
- It declares no license and scores 88/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is submission-guide still maintained?
- The repository was last updated 3 days ago, so submission-guide is actively maintained.
Skill content
View source on GitHubname: 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-inferenceorempirical-playbookskill) - The task is structural estimation implementation (use
structural-modelingskill) - The task is setting up a replication package (use
reproducible-pipelinesskill)
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-refereeagent for an adversarial review and theeconometric-revieweragent 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 name: Address to the specific editor, not "Dear Editor." Check the journal website for the handling editor or co-editors by field.
- [ ] One paragraph summary: State the paper's question, method, and main result.
- [ ] Contribution statement: Why this paper is a good fit for this specific journal.
- [ ] Conflicts of interest: Disclose any relevant relationships.
- [ ] Suggested referees: 3-5 names with affiliations and emails. Choose experts who will understand the method but are not close collaborators. Avoid suggesting people who are known to be hostile to the approach.
- [ ] Excluded referees: Optional but available at most journals. Use sparingly and only for genuine conflicts.
Journal-Specific Formatting
For per-journal tables covering spacing, abstract limits, stars conventions, submission systems, and special requirements across Economics (Top 5, AEJ, Field), Finance, Political Science, Sociology, Marketing, and Statistics journals, see: references/journal-profiles.md
Quick lookup:
- AER: 1.5-line spacing, 100-word abstract, Editorial Express
- Econometrica: Double spacing, numbered proof environments required,
ecta.cls - QJE: No significance stars — report exact p-values, ScholarOne
- JPE: University of Chicago Press style, ScholarOne
- JFE: Requires "Highlights" (3-5 bullets ≤ 85 chars each), Elsevier Editorial Manager
- APSR/AJPS: Structured abstract (Purpose / Methods / Findings / Value) required
Referee Response Strategy
Response Letter Structure
The response letter is the most important document in the revision. Structure: Opening (thank editor and referees) → summary of major changes (3-5 sentences) → point-by-point responses organized by referee, with Major and Minor sections. Quote each referee comment, then respond with specific page/section references to changes in the revised manuscript. Use tracked changes or color highlighting. For full response templates and revision routing, see references/referee-response-templates.md.
Tone and Framing
| Principle | Good Example | Bad Example | |-----------|-------------|-------------| | Thank the referee | "This is an excellent point that led us to strengthen Section 4." | "We disagree with the referee's interpretation." | | Be specific about changes | "We have added Table A3 (Online Appendix, p.15) showing results with alternative bandwidth." | "We have addressed this concern." | | Concede gracefully | "The referee is correct that our original discussion was unclear. We have rewritten paragraphs 2-3 of Section 3 to..." | "We believe our original discussion was clear, but we have added a footnote." | | Defend with evidence | "We respectfully maintain our baseline specification because: (1) the Hausman test does not reject (p=0.34, Table A5), (2) results are quantitatively similar with the referee's preferred specification (Table A6)." | "We disagree." | | Never be dismissive | "Thank you for this suggestion. While our setting differs from [Paper] because [reason], we have added a discussion of this connection in footnote 12." | "This comment reflects a misunderstanding of our method." |
What to Concede vs Defend
Concede when:
- The referee is factually correct about an error
- The suggestion improves the paper without changing the core contribution
- Adding a robustness check is low-cost and reassuring
- The concern is shared by multiple referees (editor will weight this heavily)
- The requested analysis is standard for the method (e.g., pre-trends for DiD)
Defend when:
- Conceding would undermine the paper's core identification strategy
- The requested specification is econometrically inappropriate for the setting
- The referee misunderstands a key aspect of the method or data
- The suggestion would change the paper into a different paper entirely
Response Matrix
Track every referee comment in a table with columns: Ref | # | Comment Summary | Category | Action | Status | Location. Categories: Identification, Data, Inference, Exposition, Literature, Robustness. Rule: every Status cell must be filled before resubmission.
Method-Specific Referee Concerns
For per-method concern tables (IV, DiD, Structural Estimation, RDD, Matching), including typical phrasing and detailed response strategies, see: references/referee-tactics.md
Revision Management
Track Changes Workflow
# Tag each submission and generate diff PDF
git tag -a v1-submitted -m "First submission to AER"
git tag -a v2-submitted -m "Revised submission"
latexdiff old.tex new.tex > diff.tex && pdflatex diff.tex
Reference page numbers from the clean revised manuscript, not the diff. Editors expect a diff PDF alongside the clean revision.
Multi-Round Revision Strategy
| Round | Focus | Response length | |-------|-------|----------------| | R1 (first R&R) | Address all major concerns thoroughly. Over-deliver on robustness. | Detailed, often 15-30 pages | | R2 (second R&R) | Fine-tune remaining concerns. Show that R1 issues are fully resolved. | Concise, 5-15 pages | | R3 (rare, conditional accept) | Minor copyediting, final clarifications only. | Very brief, 2-5 pages |
After each round: wait 24-48 hours → read all reports → categorize (major/minor) → build response matrix → prioritize identification concerns → draft major responses → fill minor comments → co-author review → generate diff PDF → submit.
Editor Communication
Decision Types
| Decision | Meaning | Typical Next Step | |----------|---------|-------------------| | Desk reject | Editor decided not to send to referees. | Submit elsewhere. Do not appeal unless there is a clear factual error. | | Reject after review | Referees recommended rejection. | Substantially revise and submit elsewhere, incorporating feedback. | | Revise and resubmit (R&R) | Paper has potential but needs significant revision. | Address all comments thoroughly. | | Conditional accept | Minor revi
Truncated for display — read the full file on GitHub.
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Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
