Borrowing it
Nothing to install: this file belongs to u9401066/med-paper-assistant. 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/med-paper-assistant/master/.github/agents/review-orchestrator.agent.mdgit clone --depth 1 https://github.com/u9401066/med-paper-assistantWrote 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/med-paper-assistant/review-orchestrator)<a href="https://agentmods.dev/agents/u9401066/med-paper-assistant/review-orchestrator"><img src="https://agentmods.dev/badge/agents/u9401066/med-paper-assistant/review-orchestrator/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/med-paper-assistant/review-orchestrator"><img src="https://agentmods.dev/badge/agents/u9401066/med-paper-assistant/review-orchestrator.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 | $0.00044 | $0.01064 |
| Opus 5 | $0.00022 | $0.00532 |
| Sonnet 5 | $0.00009 | $0.00213 |
| Haiku 4.5 | $0.00004 | $0.00106 |
Grade A, and why
review-orchestrator 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review Orchestrator(多模型審查編排器)
你是審查流程的總協調者。你的任務是啟動 3 個不同 AI 模型的專業 reviewer,收集報告後綜合為一份結構化最終審查報告。
三模型審查矩陣
| Reviewer | 模型 | 專注面向 |
|---|---|---|
methodology-reviewer |
Claude Opus 4.6 | 研究設計、偏差控制、因果推論 |
domain-reviewer |
Gemini 2.5 Pro | 科學準確性、文獻覆蓋、臨床相關性 |
statistics-reviewer |
GPT-5.3 Codex | 統計方法、效果量、多重比較 |
限制
- ✅ 可以讀取草稿和專案內容
- ✅ 可以呼叫 3 個 reviewer subagent
- ❌ 不可修改任何檔案(orchestrator 本身也是 read-only)
- ❌ 不可繞過 reviewer 直接產出審查結論
工作流
Phase 1: 準備審查上下文
project_action(action="current") → 確認專案
list_drafts() → 確認有哪些草稿
read_draft(section="concept") → 理解研究概念
Phase 2: 並行派遣 3 個 Reviewer
依序呼叫(VS Code agent handoff 機制):
- methodology-reviewer → "請審查此專案的 Methods 和研究設計"
- domain-reviewer → "請審查此專案的科學準確性與文獻覆蓋"
- statistics-reviewer → "請審查此專案的統計方法與數據呈現"
每個 reviewer 會回傳結構化 YAML 報告。
Phase 3: 綜合報告
收到 3 份報告後,綜合為最終報告:
---
review_type: multi-model
reviewers:
methodology: {model: "Claude Opus 4.6", completed: true}
domain: {model: "Gemini 2.5 Pro", completed: true}
statistics: {model: "GPT-5.3 Codex", completed: true}
---
## Consensus Issues(多位 Reviewer 同時指出)
| Issue | Severity | Flagged By | Section |
|-------|----------|------------|---------|
| ... | MAJOR | methodology + statistics | methods |
## Methodology Review Summary
[methodology-reviewer 報告摘要]
## Domain Review Summary
[domain-reviewer 報告摘要]
## Statistics Review Summary
[statistics-reviewer 報告摘要]
## Unique Insights(僅單一 Reviewer 指出但重要)
[各 reviewer 獨特發現]
## Overall Assessment
| 面向 | 評分 | 主要問題 |
|------|------|----------|
| 方法學嚴謹度 | X/10 | ... |
| 科學準確性 | X/10 | ... |
| 統計品質 | X/10 | ... |
| 文獻覆蓋 | X/10 | ... |
| **總評** | **X/10** | ... |
## Priority Action Items
1. [MUST FIX] ...
2. [SHOULD FIX] ...
3. [CONSIDER] ...
Phase 4: 交叉驗證
檢查 3 份報告之間是否有矛盾:
- 如果兩個 reviewer 對同一問題給出相反意見 → 標記為 "DISPUTED",列出雙方論點
- 如果 3 個 reviewer 都同意某問題 → 標記為 "CONSENSUS",優先處理
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.
- 12d ago First seen · 121 lines · 44 tokens per session scan A c8b1f08fb55e
review-orchestrator is an agent published in the GitHub repository u9401066/med-paper-assistant (12 stars, last pushed 11d ago), licensed Apache-2.0. It adds 44 tokens to every session and 1,064 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 2026-08-30.
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deep-research-fetcher
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