novelty-check

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Original

English

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Translation

Chinese

Novelty Check Skill

Check whether a proposed method/idea has already been done in the literature: $ARGUMENTS

检查所提出的方法/想法是否已在现有文献中被研究过：$ARGUMENTS

Constants

常量定义

REVIEWER_MODEL =
```
gpt-5.4
```
— Model used via Codex MCP. Must be an OpenAI model (e.g.,
```
gpt-5.4
```
,
```
o3
```
,
```
gpt-4o
```
)

REVIEWER_MODEL =
```
gpt-5.4
```
— 通过Codex MCP调用的模型。必须是OpenAI的模型（例如：
```
gpt-5.4
```
、
```
o3
```
、
```
gpt-4o
```
）

Instructions

操作步骤

Given a method description, systematically verify its novelty:

给定方法描述后，系统地验证其新颖性：

Phase A: Extract Key Claims

阶段A：提取核心论点

Read the user's method description
Identify 3-5 core technical claims that would need to be novel:
- What is the method?
- What problem does it solve?
- What is the mechanism?
- What makes it different from obvious baselines?

阅读用户提供的方法描述
识别3-5个需要具备新颖性的核心技术论点：
- 该方法具体是什么？
- 它解决了什么问题？
- 其作用机制是什么？
- 与常规基线方法相比，它的独特之处在哪里？

Phase B: Multi-Source Literature Search

阶段B：多来源文献检索

For EACH core claim, search using ALL available sources:

Web Search (via
```
WebSearch
```
):
- Search arXiv, Google Scholar, Semantic Scholar
- Use specific technical terms from the claim
- Try at least 3 different query formulations per claim
- Include year filters for 2024-2026
Known paper databases: Check against:
- ICLR 2025/2026, NeurIPS 2025, ICML 2025/2026
- Recent arXiv preprints (2025-2026)
Read abstracts: For each potentially overlapping paper, WebFetch its abstract and related work section

针对每个核心论点，使用所有可用来源进行检索：

网络检索（通过
```
WebSearch
```
工具）：
- 检索arXiv、Google Scholar、Semantic Scholar数据库
- 使用论点中的特定技术术语作为关键词
- 每个论点至少尝试3种不同的查询表述
- 应用年份筛选（2024-2026年）
知名论文数据库：检查以下数据库：
- ICLR 2025/2026、NeurIPS 2025、ICML 2025/2026
- arXiv近期预印本（2025-2026年）
阅读摘要：对于每篇可能存在重叠的论文，通过WebFetch获取其摘要及相关工作章节

Phase C: Cross-Model Verification

阶段C：跨模型验证

Call REVIEWER_MODEL via Codex MCP (

mcp__codex__codex

) with xhigh reasoning:

config: {"model_reasoning_effort": "xhigh"}

Prompt should include:

The proposed method description
All papers found in Phase B
Ask: "Is this method novel? What is the closest prior work? What is the delta?"

通过Codex MCP（

mcp__codex__codex

）调用REVIEWER_MODEL，并设置超高推理强度：

config: {"model_reasoning_effort": "xhigh"}

提示词应包含：

所提出的方法描述
阶段B中找到的所有论文
提问：“该方法是否新颖？最接近的已有研究是什么？二者的差异在哪里？”

Phase D: Novelty Report

阶段D：新颖性报告

Output a structured report:

markdown

undefined

输出结构化报告：

markdown

undefined

Novelty Check Report

新颖性验证报告

Proposed Method

所提出的方法

[1-2 sentence description]

[1-2句话描述]

Core Claims

核心论点

[Claim 1] — Novelty: HIGH/MEDIUM/LOW — Closest: [paper]
[Claim 2] — Novelty: HIGH/MEDIUM/LOW — Closest: [paper] ...

[论点1] — 新颖性：高/中/低 — 最接近的研究：[论文]
[论点2] — 新颖性：高/中/低 — 最接近的研究：[论文] ...

Closest Prior Work

最接近的已有研究

Paper	Year	Venue	Overlap	Key Difference

论文	年份	会议/期刊	重叠部分	核心差异

Overall Novelty Assessment

整体新颖性评估

Score: X/10
Recommendation: PROCEED / PROCEED WITH CAUTION / ABANDON
Key differentiator: [what makes this unique, if anything]
Risk: [what a reviewer would cite as prior work]

评分：X/10
建议：继续开展/谨慎开展/放弃
核心差异化点：（若存在，说明该方法的独特之处）
风险：（审稿人可能引用的已有研究）

Suggested Positioning

建议的定位方式

[How to frame the contribution to maximize novelty perception]

undefined

[如何呈现研究贡献以最大化新颖性感知]

undefined

Important Rules

重要规则

Be BRUTALLY honest — false novelty claims waste months of research time
"Applying X to Y" is NOT novel unless the application reveals surprising insights
Check both the method AND the experimental setting for novelty
If the method is not novel but the FINDING would be, say so explicitly
Always check the most recent 6 months of arXiv — the field moves fast

务必绝对诚实——虚假的新颖性声明会浪费数月的研究时间
“将X应用于Y”并不具有新颖性，除非该应用能带来令人惊讶的新见解
同时检查方法和实验设置的新颖性
若方法不新颖但研究发现具有新颖性，需明确说明
务必检查arXiv平台过去6个月的最新文献——领域发展速度极快