paper-review

name	paper-review
description	Use when a paper is complete or near-complete and a holistic pre-submission audit is needed. Cross-cuts text, code, tables, figures, results, citations, and reproducibility in a single pass and produces a persistent audit report. Works standalone on papers written outside the plugin.

Paper Review

Overview

This skill runs a terminal, cross-cutting audit before submission. It is not a deep prose critic (that is paper-writing), not a statistical robustness reviewer (that is robustness-checks), not a reproducibility verifier (that is replication-driven-research). Instead, it detects the seams between those skills — numerical inconsistency across the manuscript, narrative incoherence between sections, missing literature dialogue, LaTeX overflow, script errors in data pipelines, stylistic tells of AI writing — in one pass, and writes a single consolidated report with severity-ranked findings and a go/no-go verdict.

The skill is standalone. It works on any paper folder, whether produced by the superpapers pipeline or not. When the canonical layout is absent, it asks the user for the paths it needs.

When to Use

• The paper is drafted, tables and figures are in place, and the user wants a final check before submission.
• An external collaborator delivered a manuscript and you need a structured audit.
• The execute-plan skill has finished and suggested this step.
• After a major revision cycle, before re-submitting.
• The user asks for "a full paper review", "pre-submission audit", or "audit my paper".

Do not use this skill:

• Before the paper is substantially drafted — without text there is nothing to audit. Use paper-writing instead.
• For deep prose rewriting. That is paper-writing.
• To design or run additional robustness checks. That is robustness-checks.
• To verify end-to-end reproducibility execution. That is replication-driven-research.

Mandatory Steps

1. Discover the paper structure. Locate: paper.tex (or the equivalent main TeX file), references.bib, output/tables/, output/figures/, output/logs/, the code directory, run_all.sh. Walk up from the working directory. If any essential path is missing, ask the user via AskUserQuestion with concrete options (include "Other" for custom paths). Record the paths for reuse. Do not assume CLAUDE.superpapers.md or docs/superpapers/plans/ exist — the skill must work on externally authored papers.

2. Inventory artifacts. List every file relevant to the audit by category: prose files (.tex), bibliography (.bib), table files (output/tables/*.tex), figure files (output/figures/*.pdf), code (.R, .py, .do, .jl, etc.), logs, and the data manifest. Store the inventory for reuse across subsequent steps.

3. Numerical consistency. Extract numbers from the paper prose — percentages, point estimates, standard errors, sample sizes, R², test statistics, p-values. Cross-check each against its source: the output/tables/*.tex file it came from, or the log in output/logs/ that produced it. Any discrepancy beyond a reasonable rounding tolerance (default: last reported digit of the paper figure) is a Critical finding. Report both paper location (file:line) and source location.

4. Narrative coherence and structure.

   • Coherence: abstract ↔ introduction ↔ results ↔ conclusion must agree on research question, main result with magnitude, identification strategy, and key caveats. Divergence — abstract says "12% effect", conclusion says "around 10%" — is a Major finding.
   • Literature dialogue: Results and Discussion sections must cite prior literature, comparing the paper's findings against cited papers rather than merely reporting numbers in isolation. A Discussion section with zero \cite{} is a Major finding. Fewer than one citation per page of prose in Discussion or Results is a Major gap.
   • Structural flow: flag any \section, \subsection, or \subsubsection whose body is under 80 words. Flag pages where the density of subheadings suggests over-fragmentation (roughly ≥3 subheadings in one page's worth of text). Over-fragmentation is Minor with a suggested merge; severely choppy writing — multiple short sections in a row — escalates to Major.

5. Citation integrity. Every \cite{key} must have a matching entry in .bib. Every .bib entry must be cited at least once. No duplicate keys. For malformed entries or missing required fields, delegate to citation-management.

6. Code and reproducibility hygiene. Scan scripts in the code directory for:

   • Hard-coded paths: /home/..., C:\\..., absolute URLs to local disks.
   • Non-relative working directory changes: setwd("/..."), os.chdir("/...").
   • Missing seeds: any script calling sample(), bootstrap, rnorm, np.random, random, or train/test splits must set a seed before.
   • Data loading: read_csv, read.csv, read_dta, pd.read_*, fread — the path must be relative, and the referenced file must exist in the repo.
   • Column references that do not match the data schema (df$colname / df["colname"] where colname is never assigned in the pipeline).
   • Silent NA handling: regressions called without an explicit na.action or dropna(), joins with type mismatches, filters (filter, subset, .loc, where) chained without logging N before and after.
   • run_all.sh (or equivalent) exists and lists every script in the order they must run. Scripts present on disk but not referenced by the runner are flagged as orphaned.
   • data/raw/manifest.md (or equivalent) documents sources, retrieval dates, and licenses.

   For executable end-to-end verification, delegate to replication-driven-research. Findings are Critical when they block reproducibility (hard-coded paths, missing seeds in stochastic scripts, orphaned main scripts, missing data file referenced by a script), and Major otherwise.

7. Tables and figures quality.

   • Tables in output/tables/*.tex use booktabs (\toprule, \midrule, \bottomrule). Table notes use threeparttable when present.
   • Figures in output/figures/ are vector (.pdf, .eps, .svg). Raster images (.png, .jpg) are a Major finding unless the figure is inherently raster (maps with imagery).
   • Captions must be self-contained — a reader should understand the table or figure from the caption alone.
   • Margin overflow. If a compilation log exists at output/logs/paper.log or the paper directory, parse it for Overfull \hbox warnings inside table environments. If no log exists, invoke compile-latex to produce one. Each overflow is a Major finding localized to the table with suggested remediation: \resizebox{\textwidth}{!}{...}, adjustbox, landscape rotation, or column narrowing. For deeper remediation patterns, reference tables-and-figures.

8. AI-pattern surface scan.

   • Banned-word density. Count occurrences of "leverage", "delve into", "landscape" (non-literal), "multifaceted", "notably", "furthermore", "comprehensive", "pivotal", "groundbreaking", "shed light on", "pave the way", "tapestry", "intricate", "underscore", "it is important to note", "utilize". Density above 1 per 1000 words of prose is flagged with counts and locations.
   • Em-dash overuse. Count — (U+2014) per section and per 1000 words of prose. Default threshold: above 2 per 1000 words is flagged as Minor with example occurrences. Some em-dashes are legitimate; the aim is to surface overuse for the user to audit. Report per-section density so regional overuse is visible.
   • Uniform sentence length. If more than 80% of sentences in any section fall within a ±3-word band, flag as Minor.
   • For deeper prose rewriting, reference paper-writing and its review-checklist.md.

9. Language consistency. Detect the paper's main language first from CLAUDE.superpapers.md's paper_language, then heuristically (character sets, common words). Flag prose passages in a different language from the declared one. The audit report itself must be written in the same language as the paper.

10. Generate the consolidated report. Create docs/superpapers/review/ if absent. Write audit-YYYYMMDD-HHMM.md using the template at references/report-template.md. Populate every section. Each finding has: severity (Critical / Major / Minor), location (file:line), description, suggested fix. Mark any step that could not run (no compilation log and no LaTeX installed, for example) as "Inconclusive" with the reason — never silently skip.

11. Deliver the summary and offer remediation. In chat, present: finding counts by severity, report path, and go/no-go verdict. "Go" requires zero Critical findings. Offer via AskUserQuestion to remediate findings one at a time, starting with Critical. Never edit without per-finding approval. Never apply a batch fix.

Standalone vs Integrated Mode

When CLAUDE.superpapers.md is present, the skill inherits paper_language, target_journals, significance_convention, and any custom rules. When absent, the skill proceeds with defaults: paper language detected heuristically, rounding tolerance at the last reported digit, significance at 5%, em-dash threshold at 2 per 1000 words, banned-word threshold at 1 per 1000 words. The skill must function on externally authored papers, where none of the plugin's artifacts exist.

Severity Taxonomy

• Critical — blocks submission. Examples: numerical discrepancy paper ↔ source; hard-coded absolute paths in main scripts; missing seed in a stochastic script; missing raw data file referenced by the pipeline; table overflow that prevents rendering.
• Major — should fix before submission. Examples: Discussion without citations; raster figure that should be vector; narrative divergence between abstract and conclusion; Overfull \hbox in a table; orphaned .bib entries in bulk.
• Minor — nice to fix. Examples: em-dash density above threshold; a single short subsection; uniform sentence length in one section.

Anti-Patterns

• Running any mandatory step without first reading paper.tex end to end.
• Duplicating the 100-point rubric from paper-writing/references/review-checklist.md. This skill flags issues at the seams and refers deep prose critique out.
• Re-executing every robustness check listed in the paper. That is robustness-checks. Here we only verify that the checks the paper claims were executed actually exist as scripts and outputs.
• Applying fixes automatically. Every remediation requires explicit user approval per finding.
• Producing a report in a language different from the paper's declared paper_language.
• Issuing a "go" verdict while any Critical finding is unresolved.
• Silently omitting a step that could not run. Every un-runnable step must be recorded as "Inconclusive" with the reason.
• Treating absence of evidence as evidence of absence. If logs are missing and compilation was not possible, say so in the report.
• Flagging every em-dash or every long sentence. The skill surfaces density and examples so the user decides; it does not moralize.

Verification Before Completion

• docs/superpapers/review/audit-YYYYMMDD-HHMM.md exists.
• Every dimension (steps 3–9) has a populated section or an explicit "Inconclusive" with reason.
• All findings carry severity (Critical / Major / Minor) and location (file:line).
• Go/no-go verdict is explicit and consistent with findings (zero Critical ⇒ go).
• Remediation checklist exists, ordered by severity.
• User received the executive summary in chat with the report path.
• Report is written in the paper's declared language.
• No fix was applied without explicit user approval.