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Pre-submission audit: argument, numerics, refs, writing, figures, replication.
Passed 15 of 19 test cases with the skill, and 10 of 19 without it.
and 4 more in the full report
6 fixed11 passed either way4 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 6 test cases the skill fixed. Same model, same prompt, with and without the skill.
When orchestrating a multi-agent paper review, where should Phase 2 sub-agents write their structured findings so that Phase 3 cross-checkers can access them directly without clogging the context window?
| Checked | Without skill | With skill |
|---|---|---|
| The response specifies creating a dedicated temporary scratch directory named .review-tmp for intermediate agent files. | Missed | Passed |
The instructions your model reads when the skill loads.
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:
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.
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.
Read the paper yourself to understand its structure before writing agent prompts. Determine:
.tex vs Pandoc .md vs Word) and what the build command isreplication/, archive/, data/, README files).bib, inline, etc.)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-9-archive.md) using the output format specified below. 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.
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.
test cases passed, vs 10 / 19 without
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