paper-review-lite

name: paper-review-lite description: Pre-submission audit: argument, numerics, refs, writing, figures, replication. argument-hint: "[path to paper or describe manuscript to review]" context: fork # Claude Code: run skill in a forked subagent context (isolated from conversation history). See https://code.claude.com/docs/en/skills#frontmatter-reference

Paper Pre-Submission Review (Lite)

Heritage and scope

This is the in-session, Claude-Code-native counterpart to presubmit — our port of the reviewer2 adversarial peer-review pipeline to Anthropic Claude. The design inherits two things from that lineage:

A Critical-Reviewer posture. Review sub-agents adopt the persona of a rigorous, epistemically humble reviewer who is brutally honest about weaknesses but impervious to prestige (reputation, journal status, citation counts, prior peer review) and grounds every finding in a quote from the manuscript.
A verification cascade. Red Team findings are cross-checked against the source before they enter the final report; claims that cannot be pinned to a quoted passage are dropped as likely hallucinations.

What this skill is: a ~11-sub-agent review that runs inside a Claude Code session, no extra install, billable against your Claude Code plan. Fast feedback during writing.

What it is NOT: the full reviewer2/presubmit pipeline. That tool runs ~30 stages with a dedicated Red Team (Breaker, Butcher, Shredder, Collector, Void), Blue Team defence, numbers/fact-check/citation-verification cascades, and a legal pass — and it is resumable and cost-tracked. Reach for presubmit when you want deeper adversarial pressure, need a standalone deliverable (a review report file), or are preparing a manuscript for final external peer review. This skill is the fast in-flow check.

Instructions

Run a comprehensive pre-submission review of the academic paper using parallel review agents. Each agent examines a different dimension; cross-check agents audit Phase 1 findings for false positives and missed issues. The final output is a structured pre-submit report with severity-ranked findings and a journal-readiness checklist.

Critical-Reviewer posture (required for every sub-agent). Every review sub-agent must (a) cite a direct quote from the manuscript for every [CRITICAL] and [RECOMMENDED] finding — a short verbatim span is sufficient, and (b) attack the argument or the data, not the authors. Framing like "fraudulent" or "incompetent" is out of scope; "the claim on line X is not supported by the evidence on line Y" is in scope. The standard is brutally honest on the work, fair to the people.

This review can be re-run after fixes to verify issues are resolved.

1. Orientation (do this yourself before launching agents)

Read the paper yourself to understand its structure before writing agent prompts. Determine:

Where the paper source lives (LaTeX .tex vs Pandoc .md vs Word) and what the build command is
Whether a Supplementary Information file exists and where it lives
Where figures are stored and how they are referenced (relative paths, figure directories)
Whether a replication archive exists (look for replication/, archive/, data/, README files)
The paper's rough structure: section names, approximate page count, key claims in the abstract
The bibliography format and location (.bib, inline, etc.)
Design family. Is this a conjoint/factorial-vignette paper, a list experiment, a topic-modeling or LLM-classification study, or a VLM-OCR corpus paper? If so, also invoke the relevant sibling skill (conjoint-diagnostics, list-experiment, topic-modeling, text-classification, vlm-ocr-pipeline) and fold its domain-specific checklist into Agent 9's deliverable. For any experimental manuscript, also run methods-reporting in audit mode so its 45-item checklist becomes the baseline for Agents 1, 2, 6, 7, and 8.

Use this knowledge to write specific agent prompts that reference actual file paths, section names, and relevant files. Generic prompts produce shallow results.

Orchestration contract. Before Phase 2, create a scratch directory .review-tmp/ in the paper's working directory. Each Phase 2 agent writes its structured findings to a dedicated file — agent-1-content.md, agent-2-numbers.md, agent-3-references.md, agent-4-dois.md, agent-5-writing.md, agent-6-consort.md, agent-7-prereg.md, agent-8-figures.md, agent-9-archive.md — using the output format specified below. Use these exact filenames; Phase 3 reads them directly. Phase 3 cross-checkers read these files directly; you do not need to paste findings back into their prompts. Launch all Phase 2 agents in a single message with parallel sub-agent tool calls (one call per agent) so they run concurrently; launch Phase 3 after all nine output files exist. For experimental manuscripts, Agents 6 (CONSORT/randomization-and-flow) and 7 (pre-registration verification) are mandatory; for non-experimental manuscripts they can be skipped and their checklist rows marked NA. After the Pre-Submit Report has been delivered, delete .review-tmp/ — it is workflow scratch, not a deliverable — unless the user asks to keep it.

2. Parallel Deep Review (launch all 9 agents simultaneously)

Agent 1 — Content & Argument (Red Team primary): Read the full paper. Your posture is adversarial but fair: find every place the argument is weaker than the paper presents it to be. Check logical flow from introduction through conclusion. Identify unsupported claims, logical gaps, missing caveats, and places where the argument is unclear or circular. Flag any claims in the abstract not backed up in the body. Note missing discussion of limitations. Check whether the framing accurately positions the contribution relative to cited prior work. Required: support every [CRITICAL] and [RECOMMENDED] finding with a direct quote from the manuscript (verbatim span, ≤ 2 sentences) plus the file path + line number. Unsupported findings will be dropped by the cross-checker.

Agent 2 — Numbers & Internal Consistency: Check every quantitative claim against JARS-Quant reporting expectations (Appelbaum et al. 2018). Do numbers in the abstract match the body? Do table values match in-text references? Do SI cross-references point to the right appendices/tables? Are confidence intervals, p-values, N counts, and effect sizes reported consistently throughout? Flag multiple-comparisons issues (many tests without correction or discussion). Verify that significance thresholds are defined and used consistently. For experimental papers, verify denominator consistency across ITT and any complier/compliance-adjusted analyses and flag any manipulation-check that is present in the design but missing from the results. Flag forking-paths risks explicitly: DV switching between primary and secondary outcomes, covariate-set changes across models, transformation or subsetting decisions not traceable to a pre-registration, and any analysis whose choice was visibly made after seeing outcome data (Wicherts et al. 2016; Gelman & Loken 2014; Simmons et al. 2011). Do NOT audit the CONSORT flow, baseline balance, attrition-by-arm, or PAP-to-paper mapping — those are Agents 6 and 7.

Agent 3 — References & Citations: Audit the bibliography file. Are all cited works present? Are there uncited entries? Check for stale working papers (2025+) that may now be published — flag entries that need author verification. Check formatting consistency (journal names, author encoding, entry types). Do NOT check DOIs — that is Agent 4's job.

Agent 4 — DOI Audit: Check every bibliography entry for a DOI. For entries missing a DOI, attempt to locate one via web search (title + author + "doi"). Report which entries are missing DOIs and, where found, provide the correct DOI. Verify that existing DOIs resolve to the correct paper — wrong-paper DOIs are a common copy-paste error. This agent runs separately because DOI lookup is slow.

Agent 5 — Writing Quality & Journal Compliance: Check for redundancy, passive voice overuse, unclear antecedents, jargon without definition on first use, overly long sentences (60+ words), and inconsistent terminology for the same concept. Audit journal-level transparency compliance against the TOP Guidelines (Nosek et al. 2015): data citation, data/code/materials transparency, design and analysis transparency, preregistration of studies and analysis plans, replication standards. Check reporting conformance against JARS-Quant (Appelbaum et al. 2018) and the reproducibility manifesto (Munafò et al. 2017). Explicitly check these pre-submission completeness items:

Anonymization / double-blind compliance: no self-identifying information, self-citations in third person, no "unpublished manuscript by [author]" references, no author names in file metadata or acknowledgments
Data availability statement (present and accurate per TOP Level 2+ and DA-RT; Lupia & Elman 2014)
Ethics/IRB statement (present and sufficient for human subjects research; judge against APSA 2020 Principles and Guidance for Human Subjects Research — protocol number, exempt vs. expedited vs. full review, consent language, and any minor/vulnerable-population flags)
AI use disclosure (required by some journals — flag if absent and suggest adding)
Conflict of interest declaration
Funding/acknowledgment statement
Author ORCID (if journal requires)
Abstract word count (most journals cap at 150 words)
Keywords (some journals require 4-5 keywords)
Word/page count against journal limits (if known)

Flag each completeness item as present, missing, or insufficient. Do NOT audit the preregistration itself — that is Agent 7.

Agent 6 — CONSORT / Randomization & Flow (experimental papers only): Audit randomization and participant flow against the CONSORT 2010 Statement (Schulz, Altman & Moher 2010) and Gerber et al. (2014) Appendix 1. Verify a participant-flow diagram is present and documents, at every stage: number assessed for eligibility; number excluded pre-randomization and reasons; number randomized per arm; number receiving the intended condition per arm; number lost to follow-up or excluded post-randomization (by arm, with reasons); number analyzed per arm for the primary outcome. Verify that: (a) a baseline-balance table across treatment arms is reported with standardized mean differences or equivalent, and imbalances are discussed; (b) intention-to-treat (ITT) is the primary analysis — per-protocol or complier-average analyses, if reported, are clearly labeled as secondary; (c) attrition rates are reported by arm and differential attrition (magnitude and composition) is explicitly addressed, including any sensitivity analysis (e.g., Lee bounds, Manski bounds); (d) the randomization procedure (unit, block structure, stratification, allocation concealment, mechanism) is described; (e) blinding / masking status is stated for participants, experimenters, and analysts, or its absence is justified. Flag any discrepancy between the CONSORT diagram numbers and the N's reported in the main tables. For non-experimental manuscripts, write NA — non-experimental to the output file and exit.

Agent 7 — Pre-Registration Verification (experimental / pre-registered papers only): Audit the manuscript against its pre-analysis plan (PAP) end-to-end. Steps: (1) Registry verification — locate the registration on OSF, AsPredicted, EGAP, or the journal registry; record the registry ID, registration timestamp, and whether the PAP is embargoed or public; flag any registration that post-dates data collection or data access. (2) PAP-to-paper hypothesis mapping — produce a table with columns PAP ID | Registered hypothesis | Registered estimator | Registered outcome | Reported in paper? | Location | Deviation?. Every registered hypothesis must appear; every reported confirmatory analysis must trace back to a registered hypothesis. (3) Confirmatory vs. exploratory classification — every reported analysis must be explicitly labeled confirmatory (registered) or exploratory (not registered); flag analyses presented as confirmatory that are not in the PAP. (4) Silent-deviation audit — flag registered analyses not reported; reported analyses not registered; changes in DV, covariate set, subgroup, estimator, sample filter, or pre-processing step that are not disclosed in a deviations section. Judge the PAP against Waldron & Allen (2022): is it specific, precise, and exhaustive? (5) Forking-paths check — Gelman & Loken (2014) and Simmons et al. (2011): list every branch point (DV choice, covariate set, exclusion rule, transformation, subgroup definition) and confirm each is resolved by the PAP or acknowledged as exploratory. Nosek et al. (2018) "Preregistration Revolution" is the benchmark for what counts as a credible pre-registration. For non-preregistered manuscripts, write NA — no preregistration to the output file, note whether the manuscript justifies the absence, and exit.

Agent 8 — Figures, Tables & Formatting: Verify all figures referenced in text exist on disk. Check captions for self-containedness (a reader should understand the figure from the caption alone). Verify figure and table numbering for gaps or duplicates. Check for LaTeX/build warnings (undefined references, overfull/underfull boxes). Verify SI is internally consistent and all SI cross-references in the main text point to the correct appendix/table/figure numbers. Check for formatting inconsistencies (e.g., mixed \hline and booktabs, inconsistent float placement). Flag accessibility issues in figures (alt text, color-blind-safe palettes, contrast). Do NOT audit the CONSORT participant-flow diagram itself — that is Agent 6; but if Agent 6 reports a CONSORT diagram is missing, still verify that a placeholder or substitute figure is not mis-numbered.

Agent 9 — Replication Archive: Review the replication archive independently against TOP Level 2+ (Nosek et al. 2015) and DA-RT (Lupia & Elman 2014). Does the README document the full pipeline? Are all data files present (or documented as embargoed/restricted)? Do script paths in the README match what actually exists? Are software dependencies and versions documented? Is there a codebook for each dataset (variable definitions, coding)? Does a table/figure-to-script mapping exist (which script produces which output)? Are PRNG seeds documented for any simulation or bootstrap procedures? Is data provenance documented (source, license, redistribution rights)? Could a competent researcher reproduce the main results from the archive alone? Flag missing files, undocumented steps, or broken path references.

Output format for each agent: Write findings to the agent's assigned file under .review-tmp/ (see Orchestration contract above). Use structured lists, not prose. For each issue:

Severity: [CRITICAL], [RECOMMENDED], or [MINOR]
Location: file path and line number or section name
Issue: one sentence describing the problem
Fix: one sentence describing what to do
Quote: a verbatim span (≤ 2 sentences) from the manuscript that supports the finding — required for every [CRITICAL] and [RECOMMENDED] item, optional for [MINOR]. Findings without a quote will be dropped by the Phase 3 cross-checker as likely hallucinations.

Severity rubric (apply consistently across all agents):

[CRITICAL] — blocks submission: wrong numbers, broken references, missing ethics/data-availability statement when required, silent deviation from a pre-registration, anonymization failure, unreproducible main result.
[RECOMMENDED] — will draw reviewer complaint: unsupported claim, missing robustness check, undefined threshold, missing limitation, insufficient figure caption, undocumented exclusion.
[MINOR] — polish: style, typography, citation format, wording consistency.

3. Cross-Check (launch after Phase 2 completes)

Both cross-check agents read the Phase 2 output files from .review-tmp/ directly. They do not need findings pasted into their prompts — tell each cross-checker which files to read and write their own validated output to .review-tmp/agent-10-content-numbers.md and .review-tmp/agent-11-technical.md.

Agent 10 — Content, Numbers & Design Cross-Checker (Blue Team / verification): Read .review-tmp/agent-1-content.md, .review-tmp/agent-2-numbers.md, .review-tmp/agent-6-consort.md, and .review-tmp/agent-7-prereg.md. For each [CRITICAL] or [RECOMMENDED] item: (a) verify the cited quote appears verbatim at the cited location in the manuscript; drop items whose quote is missing, paraphrased, or does not support the claim made — these are hallucinations; (b) verify the issue itself against the actual paper text and flag false positives (issue doesn't exist or is already addressed); (c) steel-man the paper — for each retained finding, briefly note whether the paper anticipates or partially addresses the concern, since a partial response may downgrade severity. Add any issues missed — pay particular attention to: abstract vs. conclusion claims that drift from body evidence, significance thresholds, multiple comparisons, denominator consistency (e.g., percentages computed with vs. without a residual category), ITT vs. per-protocol mismatches, CONSORT-number vs. table-N mismatches, and silent pre-registration deviations (registered analyses not reported, reported analyses not registered).

Agent 11 — Technical Cross-Checker (Blue Team / verification): Read .review-tmp/agent-3-references.md, agent-4-dois.md, agent-5-writing.md, agent-8-figures.md, and agent-9-archive.md. For each flagged item: (a) verify the cited location actually contains the described issue (drop hallucinations); (b) verify the finding itself against the actual files — check the bibliography, figure files, figure/table numbering, and archive directory; (c) confirm or refute each finding. Add any issues missed.

4. Synthesis

Before listing anything, consolidate. If two or more Phase 2 agents independently flagged the same underlying issue, present it once with the strongest supporting quote, not two or three times under different headings. If a finder's own description includes language conceding the point ("does not in itself indicate a deviation from common practice," "while a real concern, this is standard in the literature," "the paper acknowledges this on p. X"), demote the issue one severity tier — or drop it if the concession negates the critique. The reader should not encounter the same complaint five times restated as five separate items; that's an artifact of the parallel-agent structure, and it erodes trust in the report.

Compile validated, deduplicated findings into a single Pre-Submit Report:

## Pre-Submit Report: [Paper Title]
Date: [today]
Recommendation: [Submit as-is | Minor revisions before submit | Major revisions before submit | Hold for new analysis | Substantial restructuring needed]
Issues: [N critical, N recommended, N minor]

### Editor's Note (revision strategy — read first)

A 3–6 paragraph prose memo, in your own voice, summarizing the path to a revised version that defends the contribution. Not a punch list — the punch list is below. This section should:

- Open with the single most consequential addition that would *strengthen* rather than weaken the paper. (Often a small analytical addition, a missing robustness check, or a missing comparison whose result would convert the strongest critique into a supporting result.)
- Identify which Critical Issues require new analysis (cannot be addressed by rewriting alone) versus which are textual/framing fixes.
- Where the manuscript already concedes a point that a critique missed, name the concession and note that the fix may be a small expansion of the existing acknowledgement rather than a new section.
- Where two Critical Issues are coupled (fixing one resolves the other), say so.
- End with a short paragraph on what could be deferred to a future paper without weakening the current contribution.

The Editor's Note is the most useful single section for the author who is about to revise. The Critical / Recommended / Minor lists below are the supporting evidence for the strategy laid out here.

### Critical Issues (must fix before submission)
### Recommended Changes (should fix, not blocking)
### Minor Issues (nice to have)
### Strengths (what is working well)
### Journal-Readiness Checklist

| Dimension                        | Status            | Notes |
|----------------------------------|-------------------|-------|
| Compiles cleanly                 | PASS/FAIL         |       |
| Anonymized for double-blind      | PASS/FAIL         |       |
| Argument & logic                 | PASS/FAIL/PARTIAL |       |
| Internal numerical consistency   | PASS/FAIL/PARTIAL |       |
| References complete              | PASS/FAIL/PARTIAL |       |
| DOIs present                     | PASS/FAIL/PARTIAL |       |
| Writing quality                  | PASS/FAIL/PARTIAL |       |
| Figures/tables correct           | PASS/FAIL/PARTIAL |       |
| Formatting consistent            | PASS/FAIL/PARTIAL |       |
| Abstract & keywords              | PASS/FAIL/PARTIAL |       |
| Word/page count compliant        | PASS/FAIL/NA      |       |
| Replication archive ready        | PASS/FAIL/PARTIAL |       |
| CONSORT participant flow         | PASS/FAIL/NA      |       |
| ITT & baseline balance reported  | PASS/FAIL/NA      |       |
| Attrition-by-arm reported        | PASS/FAIL/NA      |       |
| Pre-registration deviations disclosed | PASS/FAIL/NA |       |
| Data availability statement      | PASS/MISSING      |       |
| Ethics/IRB statement             | PASS/MISSING      |       |
| Preregistration disclosure       | PASS/MISSING/NA   |       |
| AI use disclosure                | PASS/MISSING      |       |
| COI declaration                  | PASS/MISSING      |       |
| Funding/acknowledgments          | PASS/MISSING      |       |

### What Still Needs Your Input

The "What Still Needs Your Input" section lists items the review cannot resolve because they require author knowledge: ethics approval numbers, funding grant details, journal-specific formatting requirements, embargo status of data, or factual claims only the author can verify.

Cite file paths and line numbers for every issue. Distinguish between objective errors (wrong numbers, broken references) and subjective suggestions (writing style, framing).

Quality Checks

Orientation phase completed: paper structure, build system, SI location, archive location all identified before agent prompts were written
Design family identified and, when applicable, the relevant sibling skill (conjoint-diagnostics, list-experiment, topic-modeling, text-classification, vlm-ocr-pipeline, methods-reporting) was invoked and its output folded into Agent 9
.review-tmp/ scratch directory created and all Phase 2 agents wrote to their assigned file
All 9 Phase 2 agents launched in parallel in a single message (Agents 6 and 7 marked NA for non-experimental / non-preregistered papers)
Phase 3 cross-checkers read Phase 2 output files directly from .review-tmp/
.review-tmp/ deleted after the report was delivered (unless the user asked to keep it)
Severity rubric (CRITICAL / RECOMMENDED / MINOR) applied consistently across all agents
Agent prompts reference specific file paths, not generic placeholders
For experimental papers: Agent 6 audited CONSORT participant flow, ITT primacy, baseline balance, attrition-by-arm, randomization procedure, and blinding
For experimental papers: Agent 7 produced a PAP-to-paper hypothesis mapping table and classified every reported analysis as confirmatory or exploratory
Forking-paths audit (DV/covariate/sample/transformation choices) was completed by Agent 7
Cross-check agents verified every CRITICAL and RECOMMENDED finding against actual files
False positives identified and removed from the final report
Synthesis deduplication applied: findings that multiple Phase 2 agents flagged about the same underlying issue are consolidated into a single entry with the strongest supporting quote, not restated multiple times under different headings
Self-conceded critiques demoted or dropped: any finding whose own description includes language conceding the point ("does not in itself indicate a deviation," "this is standard in the literature," "the paper acknowledges this on p. X") is demoted one severity tier or dropped entirely if the concession negates the critique
Top-line Recommendation set: the report begins with a single-line verdict (Submit as-is / Minor / Major / Hold for new analysis / Substantial restructuring) before any of the issue lists
Editor's Note written before the issue lists: a 3–6 paragraph prose memo identifying the single most consequential addition that would strengthen the paper, distinguishing analysis-required vs. rewriting-only fixes, and naming any concessions the author already makes that critiques may have missed
Every issue in the report includes a file path and line number (or section name)
The journal-readiness checklist covers all dimensions present in the table
The "What Still Needs Your Input" section is populated with items requiring author knowledge
Report distinguishes objective errors from subjective suggestions
Report includes a Strengths section (not just problems)
For a worked example of a filled Pre-Submit Report, see reference/example-report.md

When to reach for `presubmit` instead

This skill covers most in-flow review needs. Reach for the heavier presubmit Python CLI when:

You want full adversarial pressure — the reviewer2 pipeline spins up multiple Red Team personas (Breaker, Butcher, Shredder, Collector, Void) that each attack the paper from a different angle; this skill compresses that into Agent 1.
You want a standalone deliverable — a single report.txt and optional editor's note, produced outside your Claude Code session. Useful when the review is the product (sending feedback to a co-author, final pre-submission critique, pre-print critique).
You want resumability + cost tracking — presubmit checkpoints every stage to disk; deleting a stage file forces that stage to re-run. Tracks per-stage API cost.
You want a math audit — presubmit has an optional Mathpix-backed equation audit (--math); this skill doesn't.
You want a code-replication audit — presubmit can ingest a replication archive and compare claims against the code (--code); this skill stops at the "does the archive look complete" question in Agent 9.

Trade-off: presubmit bills per-token against an Anthropic API key (separate from your Claude Code subscription). See presubmit/README.md for install, cost considerations, and known trade-offs vs. the upstream Gemini implementation.