What problem does it solve?
Authors submitting to Nature and other high-impact journals lack an objective, evidence-grounded way to stress-test their manuscripts before peer review, often discovering weaknesses in novelty, rigor, or claim-evidence alignment only after rejection.
Core Features & Use Cases
- Three-lens review structure: Evaluates manuscripts through conceptual significance, technical integrity, and evidence-and-communication lenses, then merges findings into a cross-review synthesis with P0/P1/P2 severity ranking.
- Traceable issue tracking: Assigns every concern a stable Issue key, unique Concern ID, claim pointer, evidence pointer, and a verifiable resolution test so findings are auditable rather than vague.
- Automated consistency checking: Ships a Python script that validates concern identifiers, required fields, severity values, and consensus rules in the generated Markdown report.
- Use Case: A researcher pastes a draft manuscript and asks for a simulated Nature-style review; the skill produces a structured reviewer report flagging a P0 causality gap in Figure 2 with a concrete resolution test, then validates the report with the consistency script.
Quick Start
Use qinyan-nature-review to conduct a traceable pre-submission review of my attached manuscript and produce a severity-ranked reviewer report.
