academic-paper-reviewer

academic-paper-reviewer is a skill for Claude Code from GGbond-bo/MemOmics-Agent. It costs 0 tokens per session (8,393 once invoked), scanned A, original, MIT.

A multi-perspective academic paper review workflow that simulates several independent reviewers and combines their findings into an editorial decision and revision roadmap. It can also check whether requested revisions were addressed.

In plain words
What is it for?
It reviews journal fit, methods, field knowledge, cross-disciplinary relevance, logical challenges, and revision progress.
Why use it?
It helps authors understand a paper's strengths, weaknesses, and next improvements before or after journal review.

Skill for Claude Code

Written for Claude Code: when-to-use in frontmatter. Also seen: mentions CLAUDE.md.

Good fit It reviews journal fit, methods, field knowledge, cross-disciplinary relevance, logical challenges, and revision progress.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ggbond-bo/memomics-agent/academic-paper-reviewer
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add GGbond-bo/MemOmics-Agent --skill academic-paper-reviewer
Clone the repo
git clone --depth 1 https://github.com/GGbond-bo/MemOmics-Agent

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for academic-paper-reviewer

README.md
[![agentmods](https://agentmods.dev/badge/skills/ggbond-bo/memomics-agent/academic-paper-reviewer/github.svg)](https://agentmods.dev/skills/ggbond-bo/memomics-agent/academic-paper-reviewer)
Your own site
<a href="https://agentmods.dev/skills/ggbond-bo/memomics-agent/academic-paper-reviewer"><img src="https://agentmods.dev/badge/skills/ggbond-bo/memomics-agent/academic-paper-reviewer/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for academic-paper-reviewer

Your own site · 80×15
<a href="https://agentmods.dev/skills/ggbond-bo/memomics-agent/academic-paper-reviewer"><img src="https://agentmods.dev/badge/skills/ggbond-bo/memomics-agent/academic-paper-reviewer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 8,393 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Excessive Agency · line 428
    Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.
    Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00000 $0.08393
Opus 5 $0.00000 $0.04196
Sonnet 5 $0.00000 $0.01679
Haiku 4.5 $0.00000 $0.00839

Measured 9d ago against content hash 36c01671d5d8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

academic-paper-reviewer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

hermes_home/skills/bioinformatics/academic-paper-reviewer/SKILL.md · 505 lines

How it starts

The opening of the file, as written. The whole thing — 505 lines — stays where its author put it; the contents beside it link to each section on GitHub.

规则N: 运行记录只是参考,不能跳过审查

  • skill_evolution(action="query_logs") 返回的历史运行日志仅供参数参考
  • 即使有 quality_score=9.0 的历史日志,仍必须执行 rail_review(pre)、debate_analysis、rail_review(post)
  • 禁止因"之前跑过"而跳过任何审查步骤
  • 禁止直接用历史日志里的脚本运行而不经本次审查
  • 运行日志是"参考"不是"免审凭证"

Academic Paper Reviewer v1.10.0 — Multi-Perspective Academic Paper Review Agent Team

Simulates a complete international journal peer review process: automatically identifies the paper's field, dynamically configures 5 reviewers (Journal-Fit Reviewer + 3 peer reviewers + Devil's Advocate) who review from five non-overlapping perspectives — journal fit, methodology, domain expertise, cross-disciplinary viewpoints, and core argument challenges — then uses a separate editorial synthesizer to produce a structured Editorial Decision and Revision Roadmap.

v1.1 Improvements:

  1. Added Devil's Advocate Reviewer — specifically challenges core arguments, detects logical fallacies, and identifies the strongest counter-arguments
  2. Added re-review mode — verification review, focused on checking whether revisions address the review comments
  3. Expanded review team from 4 to 5 members

Routing discipline (v3.9.2): see .claude/CLAUDE.md "Routing Discipline (v3.9.2)" + shared/references/intent_clarification_protocol.md for cross-skill routing rules. This skill assumes routing has already settled — ambiguous cross-phase materials should have been clarified upstream.


Quick Start

Simplest command:

Review this paper: [paste paper or provide file]

Output:

  1. Automatically identifies the paper's field and methodology type
  2. Dynamically configures the specific identities and expertise of 5 reviewers
  3. 5 independent review reports (each from a different perspective)
  4. 1 Editorial Decision Letter + Revision Roadmap

Trigger Conditions

Trigger Keywords

English: review paper, peer review, manuscript review, referee report, review my paper, critique paper, simulate review, editorial review, calibrate reviewer, reviewer calibration, measure reviewer accuracy

Read the full file on GitHub · 505 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 505 lines · 0 tokens per session scan A 36c01671d5d8

Subscribe to this mod's changes

academic-paper-reviewer is a skill published in the GitHub repository GGbond-bo/MemOmics-Agent (19 stars, last pushed 2d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 8,393 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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