| name | submission-audit |
| description | Use when a manuscript is close to submission or resubmission and you need a preflight audit for claim support, figure-panel coverage, legend sync, methods references, terminology stability, and venue-facing risks. |
Submission Audit
Overview
Use this skill for late-stage manuscript QA. It is narrower than manuscript-optimizer: do not use it to redesign a paper from scratch. Use it when the structure mostly exists and the main task is to catch the failures that survive normal revision cycles.
The core rule is simple: never treat a clean-looking manuscript as submission-ready until the front half, figures, legends, methods, supplement, and venue expectations have been checked against each other.
Use the helper script when you want a fast local pass over figure citations:
python ~/.codex/skills/submission-audit/scripts/check_figure_refs.py path/to/manuscript.md
When To Use
Use this skill when:
- The draft is near submission, resubmission, or internal circulation
- Figures and legends are mostly finalized
- The paper needs a last pass for overclaim, missing references, or cross-section drift
- A revision round compressed the prose and may have dropped supporting detail
- The supplement exists and may no longer match the main text
Do not use this skill for:
- Early brainstorming
- Initial section drafting
- Citation discovery from scratch
- Heavy structural rewrites that belong in
manuscript-optimizer
Audit Order
- Front-half alignment
- check title, abstract, introduction, and discussion against the actual Results
- flag any claim stronger than the downstream evidence
- Figure and legend coverage
- verify that every main-figure panel and supplementary panel cited in the paper actually exists
- verify that panel letters, metrics, datasets, and numbers agree across figure, legend, and main text
- Methods and supplement anchoring
- check that methods are cited where needed from Results
- check that supplementary figures, tables, and notes are referenced precisely enough to be usable
- Terminology and metrics
- enforce one canonical name per concept
- check abbreviations, metric naming, domain-shift labels, cohort names, and model names
- Risk pass
- overclaim
- evidence gaps
- unsupported mechanism language
- venue-specific style drift
- Nature Portfolio preflight when relevant
- reporting-summary readiness
- data and code availability statements
- accession IDs, repositories, and disclosure of sharing restrictions
- image-integrity and raw-data readiness
- AI-use disclosure
- preprint, related-manuscript, and conference-proceedings disclosure
- Reviewer-side rejection pass
- contribution sufficiency
- writing clarity and reproducibility
- empirical strength
- evaluation completeness
- design or framework soundness
Required Checks
- Does every substantive abstract claim map to a figure, table, or supplement item?
- Does every Results subsection cite the correct panel range?
- Does every figure legend still reflect the current plot content?
- Are
Methods cross-references present where interpretation depends on setup or metric definition?
- Is the supplement indexed precisely enough, including panel letters when needed?
- Are strong causal or mechanism words used only where direct evidence exists?
- Are title, abstract, and discussion consistent about the paper's actual contribution type?
- If the target is
Nature Portfolio, are the reporting-summary inputs, data/code statements, image-integrity materials, and disclosure items actually ready rather than merely planned?
- If a submission form or portal draft already exists, do the title, abstract, keywords, availability statements, and related metadata still match the manuscript exactly?
- Has the paper been pressure-tested against the main rejection dimensions: insufficient contribution, weak clarity, weak empirical effect, incomplete evaluation, and questionable design?
Finding Format
Report findings in this order:
- High: submission-blocking or claim-distorting issues
- Medium: credibility or reader-friction issues
- Low: consistency and polish issues
Each finding should include:
- exact file reference
- what is wrong
- why it matters
- the minimum safe fix
If no major problems exist, say that explicitly and then list only the residual risks or final checks still worth doing.
Common Failure Modes
- Abstract promise stronger than Results support
- Figure panel mentioned in text but not actually indexed or explained
- Legend still describing an old version of the plot
- Supplementary figure cited at whole-figure level when the argument depends on one panel
- Metric names drifting between sections
- Discussion slipping into mechanism-level language not earned by the evidence
- Nature Portfolio submission blocked late by missing accession IDs, undeclared sharing restrictions, undisclosed AI use, or missing raw image support
- Submission-form title or abstract drifting away from the latest manuscript
- The manuscript reading cleanly on the surface while still failing a reviewer-style contribution or evaluation check
Output Standard
End the audit with:
- a one-sentence readiness assessment
- the top remaining risk
- the next highest-leverage fix before submission
