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Peer Review Assistant

Guides an authorized reviewer through evidence-bounded, confidential peer-review drafting for manuscripts, protocols, preprints, and proposals.

EducationAdvanced★ 33,030⑂ 3,248AI score 9/10Last updated: Aug 9, 2026

What it does

  • Enforces an intake gate that documents authorization, confidentiality, conflicts, venue AI policy, and retention plans before any unpublished text is inspected.
  • Selects the right reporting guideline (CONSORT, PRISMA, ARRIVE, etc.) and runs a non-scoring coverage audit locally.
  • Builds a claim–evidence matrix, audits statistics and reproducibility, and checks citation-key consistency plus figure/table integrity.
  • Generates a scaffold that keeps author comments separate from confidential editor notes, then lints for placeholders, abusive tone, and decision language that belongs to the editor.
  • All bundled CLIs are deterministic, Python-stdlib, local-only — no network, model, or image calls.

Who it's for

  • Researchers and editorial board members handling assigned reviews
  • Program officers or PIs internally appraising protocols and grant proposals
  • Authors who want a rigorous self-review before submission

Examples

  1. Reviewing an RCT manuscript: pass intake validation → check CONSORT coverage → map central claims to results → draft prioritized major/minor comments with location, evidence, and requested action.
  2. Preprint reproducibility pass: audit data/code availability, package versions, seeds and run instructions, then write proportionate requests instead of demanding new experiments.
  3. Pre-submission self-check: run audit_citations.py against your Markdown and references CSV, then lint_review.py to strip placeholders and unsupported criticism.

· · · Install guide · · ·

Try it now, no install

Paste this into Claude to use the skill without installing anything.

Read the instructions in this file and follow them to help me:
https://raw.githubusercontent.com/K-Dense-AI/scientific-agent-skills/HEAD/skills/peer-review/SKILL.md

What I want: (describe your task here)

If Claude can't open the link, open it yourself and paste the contents instead.

↓ If it works for you, download the ZIP below and install it. Then it runs on its own — no pasting each time.

Install in the Claude app (no terminal)
  1. Download the ZIP with the button below.
  2. In Claude, open Settings → Capabilities and turn on 'Code execution and file creation'. (one time)
  3. Go to Customize → Skills → + → 'Upload a skill' and upload the ZIP.
↓ Download ZIP
Install in Claude Code

Let Claude do it — paste this into Claude Code

Install the skill I found on Claude Skill Mart.
Copy the skills/peer-review folder from the GitHub repo K-Dense-AI/scientific-agent-skills into my ~/.claude/skills/peer-review/.
When it's done, tell me in one line what this skill can do.

Install with a command instead

git clone https://github.com/K-Dense-AI/scientific-agent-skills.git && mkdir -p ~/.claude/skills && cp -r scientific-agent-skills/skills/peer-review ~/.claude/skills/

⚠ This is a third-party skill. Check the source repository before installing.

  1. Open a terminal and confirm Python: python3 --version (3.11+ recommended).
  2. Clone the repo: git clone https://github.com/K-Dense-AI/scientific-agent-skills.git
  3. Create the skills folder: mkdir -p ~/.claude/skills
  4. Copy the skill in: cp -r scientific-agent-skills/skills/peer-review ~/.claude/skills/
  5. Restart Claude Code and ask something like "help me prepare a peer-review draft for this authorized manuscript".
  6. Start by copying assets/review_intake_template.json, filling it out, and running python3 scripts/validate_review_intake.py completed-intake.json until you get READY_FOR_LOCAL_REVIEW.
View source on GitHub ↗License: MIT