pre-submission-reviewer

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):

1. 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.
2. 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:

1. [inspection] Every finding quotes specific text (sentence, phrase, figure name); no "the Introduction is unclear" without a quoted line.
2. [inspection] Every CRITICAL finding has a concrete fix suggestion, not "rewrite entirely".
3. [inspection] No fabricated quotes: only text actually present in the submitted material.
4. [inspection] Severity assignments follow the taxonomy; nothing is marked CRITICAL for taste reasons.
5. [inspection] Dimension 3 (grammar) findings cite the specific grammar rule from references/grammar-rules.md.
6. [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.
7. [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>