pre-submission-reviewer

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.

1. 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.

1. [inspection] Every CRITICAL finding has a concrete fix

suggestion, not "rewrite entirely".

1. [inspection] No fabricated quotes: only text actually

present in the submitted material.

1. [inspection] Severity assignments follow the taxonomy;

nothing is marked CRITICAL for taste reasons.

1. [inspection] Dimension 3 (grammar) findings cite the

specific grammar rule from references/grammar-rules.md.

1. [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.

1. [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: <n>
• MAJOR: <m>
• MINOR: <k>
• Top three fixes first: ...

Dimension 1: Macro logic

| # | Finding | Severity | Suggested fix |

|---|---|---|---|

| 1 | <quoted text> | CRITICAL or MAJOR or MINOR | <fix> |

Dimension 2: Writing details

<same table shape>

Dimension 3: English grammar

<same table shape, citing grammar-rule ID>

Dimension 4: LaTeX format

<same table shape>

Dimension 5: Figure quality

<same table shape>

Banned-vocabulary and em-dash scan

<list with line references>

Final score (1-10)

<score>

Submission recommendation

• <Ready to submit | Needs 1-2 days more work | Needs major revision before submission>