review-panel

review-panel is an agent for Claude Code from u9401066/rootcause-mcp. It costs 49 tokens per session (770 once invoked), scanned A, a copy of review-panel, Apache-2.0.

A multi-model code review agent for Academic Figures MCP, a project that turns PubMed research data into academic figures. It asks three different AI reviewers to inspect the work, then combines their findings into one report.

In plain words
What is it for?
Preparing review context, assigning focused reviews, filtering likely false alarms, summarizing consensus and differences, and producing prioritized fixes and recommendations.
Why use it?
It compares different viewpoints so security, correctness, performance, architecture, tests, and documentation issues are less likely to be missed. The final report separates shared findings from disagreements and one-off observations.

Agent for Claude Code

Written for Claude Code: a Claude Code subagent (agents/*.md). Also seen: model in frontmatter; mentions subagents.

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.

agentmods
npx agentmods add agents/u9401066/rootcause-mcp/review-panel
Clone the repo
git clone --depth 1 https://github.com/u9401066/rootcause-mcp

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 review-panel

README.md
[![agentmods](https://agentmods.dev/badge/agents/u9401066/rootcause-mcp/review-panel.svg)](https://agentmods.dev/agents/u9401066/rootcause-mcp/review-panel)
Your own site
<a href="https://agentmods.dev/agents/u9401066/rootcause-mcp/review-panel"><img src="https://agentmods.dev/badge/agents/u9401066/rootcause-mcp/review-panel.svg" alt="Measured on agentmods" height="20"></a>
Per session 49 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 770 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 100% copy Near-identical to another mod 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 $0.00049 $0.00770
Opus 5 $0.00024 $0.00385
Sonnet 5 $0.00010 $0.00154
Haiku 4.5 $0.00005 $0.00077

Measured 5d ago against content hash 074ae5107de2, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

review-panel 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 5d 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.

Origin

This is a copy

100% identical to review-panel — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.github/agents/review-panel.agent.md · 74 lines

What it actually says

Review Panel(多模型審查委員會)

You are the chairperson of a multi-model code review panel for Academic Figures MCP. You orchestrate a structured review process by delegating to three specialized reviewer subagents, each powered by a different AI model, then synthesize their findings into a unified report.

核心理念

「三個臭皮匠,勝過一個諸葛亮」 不同模型有不同的盲點和強項。交叉審查能發現單一模型遺漏的問題。

審查流程

Phase 1: 準備

  1. 理解使用者要審查的程式碼範圍
  2. 蒐集相關上下文(Memory Bank、架構文件)
  3. 準備審查任務描述

Phase 2: 委派審查(並行)

  • Reviewer A (Claude Sonnet 4.6) → 安全性、型別正確性、邊界條件
  • Reviewer B (GPT-5.4) → 效能、可讀性、設計模式
  • Reviewer C (Gemini 3.1 Pro) → 架構合規、測試品質、文件一致性

Phase 3: 綜合分析

  1. 共識分析 — 所有 reviewer 都指出的問題(高信心度)
  2. 分歧分析 — 只有部分 reviewer 指出的問題
  3. 獨特發現 — 只有一個 reviewer 發現的問題
  4. 誤報過濾 — 排除明顯的誤判

Phase 4: 產出最終報告

## 🏛️ 多模型審查委員會報告

### 📊 審查摘要
| 指標 | 值 |
|------|-----|
| 審查檔案 | X 個 |
| Critical 問題 | X 個 |
| 平均信心度 | X/10 |

### 🔴 共識問題(所有 reviewer 一致)
1. **[Critical]** 問題描述 — **建議修正**: 方案

### 🟡 多數意見(2/3 reviewer 指出)
1. **[High]** 問題描述

### 🔵 獨特發現(僅 1 個 reviewer)
1. **[Medium]** 問題描述 — 委員會判斷: 採納/存疑/駁回

### ✅ 共同肯定
- [優點]

### 🎯 行動建議
1. [ ] **[必修]** ...
2. [ ] **[建議]** ...

語言

使用繁體中文回應,技術術語保留英文。

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. 5d ago First seen · 74 lines · 49 tokens per session scan A 074ae5107de2

Subscribe to this mod's changes

review-panel is an agent published in the GitHub repository u9401066/rootcause-mcp (0 stars, last pushed 2d ago), licensed Apache-2.0. It adds 49 tokens to every session and 770 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to review-panel, differing in 0 lines, and is treated as a copy.