submission-prep
community[skill]
Pre-submission checklist for JF, RFS, JFE, or other target journals
$
/plugin install ai-asset-pricingdetails
Submission Prep Skill
Run a pre-submission checklist tailored to the target journal. Catches common rejection-worthy issues before you submit.
Examples
/submission-prep-- run full checklist (uses target journal from project's CLAUDE.md)/submission-prep JF-- run checklist with JF-specific requirements/submission-prep --strict-- flag warnings as failures
Workflow
Step 1: Load Target Journal
Read the project's CLAUDE.md for the target journal. If not specified, ask the user. Common targets: JF, RFS, JFE, RoF, JFQA, MS.
Step 2: Run Checks
2a. Document Structure
- Abstract present and within word limit (100--150 words for JF/RFS/JFE)
- Title length reasonable (<15 words recommended)
- All expected body sections present (check project's
CLAUDE.mdfor section list) - Page count within typical range (40--60 pages including appendices for top-3)
2b. Content Completeness
- No
[HUMAN EDIT REQUIRED]tags remaining in any.texfile - No
TODO,FIXME,XXXcomments in.tex - No
\lipsumor placeholder text - No commented-out sections that should be removed or restored
2c. Terminology Compliance
- Project-specific terminology used consistently (check project's
CLAUDE.md) - No banned words from
academic-writing.mdSection 1
2d. Tables and Figures
- All tables have self-contained captions (sample period, units, variable definitions)
- All figures have self-contained captions with axis labels
- All tables and figures are referenced in the text (
\refcheck) - Numbers use 2--3 significant digits (not computer output)
- Tables use booktabs style (
\toprule/\midrule/\bottomrule, no vertical lines) - Figures use vector format (PDF) where possible
2e. Bibliography
- All
\cite{}keys resolve to.bibentries - No unused
.bibentries - No duplicate
.bibentries - Consistent BibTeX format (all
@articlehavejournal,year,volume,pages) - Proper nouns protected in titles:
{CAPM},{U.S.},{NYSE}, etc.
2f. Cross-References
- All
\ref{}and\eqref{}resolve to valid labels - Equations use
\eqrefnot\ref - Non-breaking spaces used (
Table~\ref,Eq.~\eqref,Figure~\ref)
2g. Writing Quality
- No banned words (run
/style-checkif not done recently) - No AI-marker words (see
academic-writing.mdfor full list) - No em-dashes (
---) in prose - No structural AI tells: naked "this", adverb openers, "Together, these results..."
- Soft-ban words within limits: "highlights" (max 2/paper), "insights" (max 1/paper)
- No hedge words: somewhat, quite, very (intensifier), arguably, perhaps
- No previewing: "as we show below", "we will show", "Recall from"
- Active voice throughout
- Specific numbers for quantitative claims
- First sentence is concrete, not throat-clearing
2h. Compilation
- Clean compile with no errors
- Acceptable warning count (flag if >10 non-font warnings)
- PDF renders correctly (no missing figures, no ?? references)
2i. Journal-Specific Requirements
- Author information complete (names, affiliations, emails)
- Acknowledgments section present
- JEL classification codes present
- Keywords present (if required by target journal)
- Data availability statement present (increasingly required)
2j. Key Results Verification
- Key claims in the project's
CLAUDE.mdmatch the numbers in tables/text - Sample period stated consistently across abstract, introduction, and table captions
- Main results discussed in both introduction and results section
Step 3: Output
SUBMISSION PREP CHECKLIST
=========================
Target: [journal]
Paper: [title from project CLAUDE.md]
PASS: N checks passed
FAIL: M checks failed
WARN: K warnings
--- FAILURES ---
[ ] Line X: [HUMAN EDIT REQUIRED] tag found in section Y
[ ] Table Z: caption missing sample period
[ ] \cite{smith2023}: key not in .bib
--- WARNINGS ---
[!] Abstract is 168 words (target: 100-150)
[!] 14 compilation warnings (non-font)
[!] Page count: 65 pages (typical: 40-60)
--- PASSED ---
[x] All body sections present
[x] All figures referenced in text
[x] Clean compile (0 errors)
[x] Terminology compliant
[etc.]
RECOMMENDATION: [READY TO SUBMIT / FIX N ISSUES FIRST]
technical
- github
- Alexander-M-Dickerson/ai-asset-pricing
- stars
- 49
- license
- MIT
- contributors
- 1
- last commit
- 2026-04-19T07:58:01Z
- file
- .claude/skills/submission-prep/SKILL.md