Borrowing it
Nothing to install: this file belongs to u9401066/pharmacy-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/u9401066/pharmacy-mcp/main/.github/agents/review-panel.agent.mdgit clone --depth 1 https://github.com/u9401066/pharmacy-mcpWrote 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.
[](https://agentmods.dev/agents/u9401066/pharmacy-mcp/review-panel)<a href="https://agentmods.dev/agents/u9401066/pharmacy-mcp/review-panel"><img src="https://agentmods.dev/badge/agents/u9401066/pharmacy-mcp/review-panel/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.
<a href="https://agentmods.dev/agents/u9401066/pharmacy-mcp/review-panel"><img src="https://agentmods.dev/badge/agents/u9401066/pharmacy-mcp/review-panel.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once 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 |
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 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- review-panel — 100% identical, 0 lines differ
- review-panel — 100% identical, 0 lines differ
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
- 理解使用者要審查的程式碼範圍
- 蒐集相關上下文（Memory Bank、架構文件）
- 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
- 共識分析 — 所有 reviewer 都指出的問題（高信心度）
- 分歧分析 — 只有部分 reviewer 指出的問題
- 獨特發現 — 只有一個 reviewer 發現的問題
- 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。
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.
- 9d ago First seen · 74 lines · 49 tokens per session scan A 074ae5107de2
review-panel is an agent published in the GitHub repository u9401066/pharmacy-mcp (3 stars, last pushed 1mo 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. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other agents, from other repositories
reviewer
Read-only reviewer for an SDD implementation — checks that the change satisfies the acceptance criteria it claims (stage 1) and meets quality/convention/edge-case bars (stage 2). Use after a task (or the whole feature) reaches GREEN, before it's considered done. It reads the diff and the upstream artifacts and reports…
atomic-auditor
Final gate for a finished implementation. Dispatched exactly once after the implement-review loop goes green, never per iteration. Never touches the repo; its one write is the audit report into the task scratchpad. Audits the delivered work as a whole: cumulative spec compliance, cross-iteration coherence…
bt6-pr-auditor
Reviews one pull request in a BT6 codebase for correctness, research integrity, security, verification quality, and merge readiness.
Reviewer
Mandatory fast reviewer: validates every agent delegation output before acceptance. Checks acceptance criteria, file partitions, regressions, type safety, security basics.
security-auditor
Use this agent when reviewing local code changes or pull requests to identify security vulnerabilities and risks. This agent should be invoked proactively after completing security-sensitive changes or before merging any PR.
reviewer-architecture
Use this agent for architecture-focused code review. Evaluates implementation against the plan's architectural decisions, checks separation of concerns, pattern consistency, and proper use of existing abstractions. Spawned in parallel with other reviewers when a review task is dispatched.