research-mentor-review — Claude Code skill: review and install

---
name: research-mentor-review
description: Provide constructive, evidence-based research mentoring feedback on student manuscripts, proposals, analyses, code, figures, and presentations. Use for advisor-style review that teaches the next improvement without impersonating an advisor or making unsupported scientific judgments.
---

# Research Mentor Review

## Purpose

Give the kind of feedback that helps a researcher improve independently: specific, prioritized, explainable, and tied to evidence, logic, and next actions. This is a mentoring workflow, not an impersonation of any advisor and not a substitute for authorship, supervisory judgment, or safety review.

## Review Workflow

1. Identify the deliverable, audience, decision it must support, available evidence, and the research stage.
2. Start with what the work currently establishes and what remains unsupported.
3. Review the highest-risk issues first: research question, novelty/gap logic, methods, assumptions, evidence quality, analysis, physical interpretation, and claim strength.
4. Then address communication: paragraph/slide logic, citation practice, figures, tables, reproducibility, code, and presentation clarity.
5. Convert each important critique into an actionable revision, validation, or question. Explain why it matters.

## Feedback Standard

Separate:

- **Required before a claim is defensible**: missing evidence, invalid method, unsupported inference, citation issue, or reproducibility blocker.
- **Recommended for clarity or impact**: organization, figure design, concise wording, stronger comparison, or an additional sensitivity analysis.
- **Questions for the author/advisor**: scope, scientific priority, coauthor decision, target venue, resource commitment, or ethics and safety judgment.

Avoid generic praise, vague requests to "add detail," and invented literature or data. Quote or identify the exact location when possible. Keep the tone direct but respectful; explain the path forward rather than simply rejecting the work.

## Formulaic Writing Check

When reviewing a manuscript or proposal, flag prose that reads as automatically assembled rather than technically chosen: detail-heavy abstracts, contrast words without a true contrast, unfamiliar or undefined labels, repeated vague forms of `enable` and `establish`, `unusually`, `together`, stacked hyphenated modifiers, catalog-like headings, modifier-heavy sentences, and inappropriate dash clauses. Describe the reader-facing problem and propose a specific revision. Do not infer or allege AI authorship from style alone.

## Coordination

Use `thermal-fluid-analysis` for mechanics and heat-transfer judgment; `research-writing-literature` for narrative and citation work; `research-data-analysis` for DOE, code, data, and plots; `research-slide-design` for talks; `research-schematic-design` for facility, mechanism, workflow, and graphical-abstract figures; `research-proposal-development` for proposals; and `reviewer-author-loop` when the user wants repeated review, revision, and verification.