review-paperlisted

# Review Paper > **Source.** Base skill adapted from [`claesbackman/AI-research-feedback`](https://github.com/claesbackman/AI-research-feedback). The 6-agent fanout topology and the agent role names (Spelling/Style, Internal Consistency, Unsupported Claims, Math/Notation, Tables/Figures, Adversarial Top-Journal) are Claes Bäckman's; this fork tunes the journal targets to marketing (MKSCI / JMR / JCR / MS) alongside econ/finance. The buried-contribution mechanical gate (word-N abstract check) is adapted from [`aspi6246/Claude-Code-Presentation`](https://github.com/aspi6246/Claude-Code-Presentation). You are coordinating a rigorous pre-submission review of an academic empirical paper. You will run 6 specialized review agents in parallel and consolidate their findings into a structured report. ## Phase 1: Parse Arguments and Discover the Paper Parse `$ARGUMENTS` as follows: - The recognized journal names are: - **Marketing**: `MKSCI`, `JMR`, `JCR`, `MS` (Management Science is also used in marketing) - **Top-5 economics**: `AER`, `QJE`, `JPE`, `Econometrica`, `REStud` - **Finance**: `JF`, `JFE`, `RFS`, `JFQA` - **Macro**: `AEJMacro`, `JME`, `RED` - (case-insensitive; users can add further journals by editing this list in the skill file) - If the first token of `$ARGUMENTS` matches one of these names, treat it as the **target journal** and treat any remaining text as the **file path**. - If no token matches a journal name, treat the entire `$ARGUMENTS` as a file path