/peer-review-engine

name: peer-review-engine
description: >
  Activate when the user wants to simulate a double-blind peer review of their
  paper before submission or before sharing with co-authors. Reads the current
  draft (draft.md or paper.tex), generates 2 independent reviewer reports in the
  style of top IS/CS conferences (ICIS, ECIS, MISQ level), and saves the output
  as simulated_reviews.md. The output is formatted to serve as direct input for
  /respond-reviewers (review-engine feedback loop).

> **Orchestration Log**: When this skill is activated, append a log entry to `outputs/orchestration_log.md`: > ``` > ### Skill Activation: Peer Review Engine > **Timestamp:** [current date/time] > **Actor:** AI Agent (peer-review-engine) > **Input:** [paper source: draft.md / paper.tex, word count, number of sections] > **Output:** 2 simulated reviewer reports saved to simulated_reviews.md > **Recommendation distribution:** [R1: recommendation, R2: recommendation] > ```

Peer Review Engine

Core Principle

The best time to discover weaknesses is before reviewers do. This engine generates two independent, simulated double-blind peer reviews that mimic the rigor, tone, and structure of top-tier IS/CS conference reviews (ICIS, ECIS, HICSS) and journal reviews (MISQ, ISR, EJIS, BISE). Each reviewer has a distinct persona and evaluation focus, producing complementary perspectives on the manuscript.

The reviews are **actionable, not performative**. Every weakness includes a concrete suggestion for improvement. Every strength is specific enough to preserve during revision. The output format is designed to feed directly into `/respond-reviewers`, creating a pre-submission quality loop: write -> self-review -> revise -> submit.

When to Activate

• User says "review my paper", "simulate a peer review", "give me reviewer feedback"
• User says "review paper", "pre-submission check", "what would reviewers say?"
• After Phase 6 (LaTeX export) when the user wants quality assurance before sharing
• Before sending a draft to co-authors
• When the user wants to identify weaknesses before formal submission
• User runs `/review-paper`

Prerequisites

• `draft.md` or `latex/paper.tex` exists (at least one)
• Paper has identifiable sections (Introduction, Background, Method, Results/Findings, Discussion)
• If paper.tex exists and is more recent than draft.md, prefer paper.tex

---

Step 1: LOCATE & READ the Paper

Find the Manuscript

Check for paper sources in this order of preference:

1. **`latex/paper.tex`** — if it exists and compiles, this is the most complete version 2. **`draft.md`** — the markdown draft from the production phase 3. **User-specified path** — if the user provides a specific file path

If both exist, compare timestamps. Use the more recent one, but note which version was reviewed.

Extract Paper Metadata

Read the full paper and extract:

1. **Title** (from `\title{}` or first `# ` heading) 2. **Abstract** (from `\begin{abstract}` or the abstract section) 3. **Section structure** — list all sections and subsections with approximate word counts 4. **Research questions** — extract explicit RQs (look for "RQ1:", "Research Question", etc.) 5. **Method** — what methodology is described (SLR, case study, DSR, survey, experiment, etc.) 6. **Theoretical lens** — which theories/frameworks are applied 7. **Key contribution claims** — what does the paper claim to contribute 8. **Number of references** — count `\citep`/`\citet` or `(Author, Year)` patterns 9. **Figures and tables** — count and list captions 10. **Total word count** — approximate

Identify Target Venue

If the paper mentions a target venue (in metadata, framing.md, or paper_structure.md), use that venue's specific review criteria. Otherwise, default to ICIS/ECIS-level expectations for IS papers, or top-tier CS conference standards for CS papers.

---

Step 2: ASSESS Against Review Dimensions

Before writing individual reviews, perform a systematic assessment across all evaluation dimensions. This ensures both reviewers draw from a consistent quality analysis while emphasizing different aspects.

Evaluation Dimensions

| Dimension | Weight | What to Check | |-----------|--------|---------------| | **1. Contribution** | High | Is the contribution clearly stated? Is it novel? Does it advance theory or practice? Is the gap well-motivated? | | **2. Theoretical Foundation** | High | Is the theory well-chosen? Is it properly applied (not just cited)? Are constructs operationalized? | | **3. Research Design & Rigor** | High | Is the method appropriate for the RQs? Are threats to validity discussed? Is the approach replicable? | | **4. Literature Coverage** | Medium | Is the related work comprehensive? Are key papers cited? Is the positioning accurate? | | **5. Argumentation & Logic** | Medium | Does the paper flow logically? Are claims supported by evidence? Are there logical gaps? | | **6. Writing Quality** | Medium | Is the paper clearly written? Is it within page limits? Are figures/tables well-designed? | | **7. Practical Relevance** | Low-Med | Are practical implications specific and actionable? Would practitioners find this useful? |

Quality Signals to Detect

**Positive signals:**

• Clear gap-to-contribution alignment
• Theory used as an analytical lens (not just background decoration)
• Method follows established protocols (e.g., Kitchenholz & Charters for SLR, Hevner for DSR)
• Discussion goes beyond restating results
• Limitations are honest and specific

**Red flags:**

• Gap is asserted without evidence ("surprisingly, no study has...")
• Theory is mentioned but not applied in analysis
• Method lacks detail (sampling unclear, coding process vague)
• Results section is purely descriptive without interpretation
• Discussion is generic ("future research should explore...")
• [CITE], [DATA], [TODO] placeholders remain
• Contribution claims are too broad for the evidence presented
• Mismatch between RQs a