| name | pre-submission-reviewer |
| description | Runs a pre-submission review of a technical paper across five dimensions: macro logic, writing details, English grammar, LaTeX formatting, and figure quality. Uses a reviewer-style severity taxonomy (CRITICAL / MAJOR / MINOR) and flags banned AI-tone vocabulary and em-dash misuse. Use when the user asks to 'review this paper', 'audit before submission', 'check the draft', 'find issues', 'proofread', or within one week of a submission deadline. |
| license | CC-BY-4.0 |
Pre-Submission Reviewer
Overview
Three to five days before a submission deadline is the window where
a careful external review pays off most. This skill takes a full
paper or key sections and produces a structured review across five
dimensions, each with severity-tagged findings and concrete
rewrite suggestions. It enforces the mechanical rules from the
writing-checklist section (no em-dashes, no banned AI-tone
vocabulary, leading text per paragraph, topic-sentence discipline,
citation-format uniformity) and surfaces the patterns that
non-native English-speaking authors most commonly violate
(articles, subject-verb agreement, tense consistency, which versus
that, Chinglish phrasing).
The output is not a rewrite. It is a prioritised list of findings
with severity tags; the author decides which to fix. CRITICAL items
should block submission until addressed.
When to use this skill
- Three to five days before a submission deadline.
- The user asks to 'review this paper', 'audit before submission',
'check the draft', 'find issues', 'proofread'.
- After a camera-ready revision, before sending the final version.
- After any major rewrite (rebuttal responses, Section 3 overhaul).
- When the user suspects AI-tone contamination in a section.
When NOT to use this skill
- The paper is still being structured. Use
tech-paper-template,
intro-drafter, or benchmark-paper-template (separate plugin) first.
- The user wants structural advice rather than review. Use the
drafting skills instead.
Core procedure
Step 0: paradigm and venue fit
Before the dimensional review, settle two things.
Paradigm, judged by research method, because what counts as a
severe problem differs by paradigm:
- STEM / technical (CS, engineering, materials, chemistry): weight
the Introduction chain, contribution-to-section mapping, baseline
coverage, ablation-based attribution, figure quality. Benchmark
papers additionally get coverage, reproducibility, and
contamination checks; chemistry and materials get characterization
completeness, purity, controls, replicates.
- Humanities (literature, history, philosophy, discourse
analysis): weight whether the thesis is explicit and defensible,
core concepts pinned down and stable across sections, the
literature genuinely engaged, and the material (texts, archives,
cases) able to carry the claims. Do not demand baselines or
ablations here; check instead whether sub-arguments build on each
other rather than sit in parallel, and whether conclusions outrun
the material.
- Empirical social science: weight operationalized research
questions, sampling and data-source justification, statistics
matched to data types, conclusions bounded by the sample. For
theory papers, "experiments" reads as "proofs": check the proofs,
and never call the evidence thin merely because there is no results
table.
- Finance / economics: weight identification credibility,
endogeneity handling, robustness checks (their absence is a
first-round flag), and economic versus merely statistical
significance.
- Law: weight the accuracy of statutes, case numbers, and
holdings (an invented or wrong citation is rejection-level), the
clarity of the interpretive approach, and whether comparative
arguments state their scope.
When the paradigm is unclear, ask the author before reviewing with
the wrong ruler.
Venue fit: if the stated target venue's scope visibly mismatches
the paper's topic or contribution type, that is a real rejection
risk, not a taste note. Flag it as a finding and suggest two or three
better-fitting venues.
Step 1: Dimension 1 Macro logic review
See: references/logic-and-structure.md for the Logic First rule,
Self-contained rule, Leading Text rule, and Running Example rule.
Check:
- Introduction flowchart is intact (Background, Limitations, Goal
or Key Idea, Challenges, Methodology, Contributions).
- Contributions map one-to-one with methodology modules and with
section numbers.
- Experiments validate the paper's main claims, not tangential
ones.
- Related Work covers the necessary prior art.
- Running example is consistent across Introduction, Methodology,
Experiments.
- The headline result's attribution is isolated: an ablation
separates the core mechanism from peripheral factors (a routing
step, post-processing, a stronger base model, favorable samples).
No such ablation: flag "attribution unverified" as MAJOR.
- Claims match their evidence: "solves" is stronger than most papers
earn (usually "improves"); "state-of-the-art" needs the benchmark
and conditions; "we are the first" gets checked or flagged.
Every break in the chain is CRITICAL.
Retrieval-grounded checks (when the environment has a
literature-search capability: a scholarly tool, web search over
scholarly indexes, or shell access to public APIs):
- Novelty verification: extract two or three keyword groups from
the paper's core method and problem setting, retrieve, and identify
the three to five closest published works. If Related Work already
covers them, the paper's positioning stands; a highly relevant
uncovered work is a MAJOR finding ("missed X, Author et al.,
Year"). Compare on difference axes; a similar title alone proves
nothing.
- Citation completeness: retrieve the field's recent
representative works and its canonical ones, and compare against
the reference list; a missing canonical baseline, founding paper,
or recent survey is MAJOR.
Retrieval results support metadata-level judgments only; never quote
numbers or method details from search snippets. Without any retrieval
capability, skip these two checks and say so in the summary.
Step 2: Dimension 2 Writing details review
See: references/logic-and-structure.md for paragraph-level rules.
Check:
- Every paragraph has a topic sentence.
- Paragraphs transition smoothly; no orphan paragraphs.
- Paragraphs are not over 10 lines; split if so.
- No repeated or redundant passages.
- Abstract covers problem, method, result.
Step 3: Dimension 3 English grammar review
See: references/grammar-rules.md for the canonical list of errors
common to non-native English authors, with corrections and
examples.
Check the usual suspects:
- Article use (a, an, the).
- Subject-verb agreement (third-person singular).
- Tense consistency (Related Work past, method present).
- Passive-voice overuse.
- Which versus that.
- Sentence length; split long sentences at "Specifically,".
- Chinglish patterns.
Step 4: Dimension 4 LaTeX format review
See: references/latex-rules.md for the canonical list of LaTeX-
specific issues.
Check:
- Equation numbering contiguous; every numbered equation
referenced.
- Figures and tables have captions; captions are detailed.
- Citations use the correct command and the non-breaking tilde
(for example,
ResNet~\cite{X}, never ResNet\cite{X}).
- Labels use underscores, not spaces or hyphens.
- Vector figure format; no raster.
- Page-limit compliance.
Step 5: Dimension 5 Figure quality review
See: references/forbidden-patterns.md for chartjunk patterns and
the full figure-quality checklist.
For each figure:
- Vector format.
- Font size large enough post-scaling.
- Colour-blind-safe palette; dual encoding.
- Self-contained caption with a finding in the first sentence.
- No chartjunk.
- Motivated example is concrete and failure-revealing.
- Solution overview has labels matching section titles.
Step 6: Banned-vocabulary and em-dash scan
See: references/forbidden-patterns.md for the banned-word list.
Scan the full paper for:
- Em-dashes used as sentence connectors (banned; project rule).
- AI-tone words: innovative, pioneering, revolutionary paradigm,
transformative framework, superior, surpass, excel, remarkable,
unprecedented, breakthrough performance, general-purpose, is
capable of, notably, yet, yielding, at its essence, encompass,
differentiate, reveal, underscore, pave the way for, highlight
the potential of, profound challenges, stems from, rigid,
impede.
Flag each occurrence with a severity tag. Em-dashes are MAJOR by
default; banned AI-tone words are MAJOR if they appear three or
more times.
Step 7: Section-by-section review
See: references/section-guides.md for the per-section writing
guides for Abstract, Introduction, Problem Formulation, Framework
or Method, Experiments, Related Work, and Conclusion.
For each section, check that the section's content matches the
guide's canonical structure (for example, Abstract's five-sentence
formula: what, why, challenges, how, results).
Step 8: Integrity gate
Run the checks in the Integrity gate section below.
Step 9: Output
Emit the review in the Output format below.
Severity taxonomy
- CRITICAL: blocks submission. Example: contributions do not
map to sections; introduction flowchart broken; no real-world
running example; raster figure in final draft; missing key
baseline; page-limit violation.
- MAJOR: reviewers will flag in first round. Example:
topic-sentence absent from 3+ paragraphs; em-dash in 5+ places;
banned AI-tone word in 3+ places; Table 1 comparison missing;
chart type mismatched with data.
- MINOR: polish. Example: two long sentences that could be
split; default Matplotlib styling; single article error.
Severity honesty cuts both ways. A review that lists a dozen MINOR
items while missing the one rejection-level flaw sends the author to
submission with false confidence; a review that inflates taste issues
into CRITICAL destroys trust. The overall recommendation must match
the findings: any unresolved CRITICAL forbids "ready to submit", and
a near-ready verdict requires zero CRITICAL and at most two MAJOR.
Integrity gate
Each bullet is tagged [inspection] (LLM verifies from the paper
text) or [attestation] (LLM runs the procedure and states it has
done so; user remains responsible for confirming completeness).
Before emitting the review:
- [inspection] Every finding quotes specific text (sentence,
phrase, figure name); no "the Introduction is unclear" without
a quoted line.
- [inspection] Every CRITICAL finding has a concrete fix
suggestion, not "rewrite entirely".
- [inspection] No fabricated quotes: only text actually
present in the submitted material.
- [inspection] Severity assignments follow the taxonomy;
nothing is marked CRITICAL for taste reasons.
- [inspection] Dimension 3 (grammar) findings cite the
specific grammar rule from
references/grammar-rules.md.
- [attestation] Dimension 6 banned-vocabulary scan is run in
full on the entire paper, not sampled. The skill attests the
full scan; if the paper is extremely long, the skill states it
chunked the input and describes the chunking strategy.
- [inspection] Final score matches the CRITICAL + MAJOR
count; a score of 9 or 10 requires zero CRITICAL and at most
two MAJOR items.
If any [inspection] check fails, mark the output as "needs user
attention". For [attestation] bullets, the skill states the scope
of its scan and the user confirms completeness.
Run the gate silently. Do not print a per-gate pass or fail report;
a failure surfaces as a concrete finding in the affected dimension,
and the delivered review stays free of internal checking rituals.
Output format
Summary
- CRITICAL:
- MAJOR:
- MINOR:
- Top three fixes first: ...
Dimension 1: Macro logic
| # | Finding | Severity | Suggested fix |
|---|
| 1 | | CRITICAL or MAJOR or MINOR | |
Dimension 2: Writing details
Dimension 3: English grammar
<same table shape, citing grammar-rule ID>
Dimension 4: LaTeX format
Dimension 5: Figure quality
Banned-vocabulary and em-dash scan
Final score (1-10)
Submission recommendation
- <Ready to submit | Needs 1-2 days more work | Needs major revision before submission>
