fin-novelty-check

fin-novelty-check is a skill for Claude Code from csmar432/finai-research. It costs 52 tokens per session (3,060 once invoked), scanned A, original, MIT.

A literature search for checking whether an economics or finance research idea is new. It compares the idea with recent papers from major journals, working-paper databases, and arXiv across similarity, methods, samples, and mechanisms.

In plain words
What is it for?
Use it to break an idea into testable claims, search for closely related studies, assess how the sample or method differs, rate the level of novelty, and develop a clearer research position.
Why use it?
It helps reveal whether a proposed study has already been done and where its genuine difference might lie. It also identifies ways to position the contribution and risks that could make the idea look less original.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter. Also seen: installed under .agents/ (shared by several agents).

Good fit Use it to break an idea into testable claims, search for closely related studies, assess how the sample or method differs, rate the level of novelty, and develop a clearer research position.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/csmar432/finai-research/fin-novelty-check
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 csmar432/finai-research --skill fin-novelty-check
Clone the repo
git clone --depth 1 https://github.com/csmar432/finai-research

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 fin-novelty-check

README.md
[![agentmods](https://agentmods.dev/badge/skills/csmar432/finai-research/fin-novelty-check/github.svg)](https://agentmods.dev/skills/csmar432/finai-research/fin-novelty-check)
Your own site
<a href="https://agentmods.dev/skills/csmar432/finai-research/fin-novelty-check"><img src="https://agentmods.dev/badge/skills/csmar432/finai-research/fin-novelty-check/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 fin-novelty-check

Your own site · 80×15
<a href="https://agentmods.dev/skills/csmar432/finai-research/fin-novelty-check"><img src="https://agentmods.dev/badge/skills/csmar432/finai-research/fin-novelty-check.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 52 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,060 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 pass 7 Sept 2026
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 $0.00052 $0.03060
Opus 5 $0.00026 $0.01530
Sonnet 5 $0.00010 $0.00612
Haiku 4.5 $0.00005 $0.00306

Measured 12d ago against content hash eabf480a58b3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

fin-novelty-check 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.

.agents/skills/fin-novelty-check/SKILL.md · 351 lines

How it starts

The opening of the file, as written. The whole thing — 351 lines — stays where its author put it; the contents beside it link to each section on GitHub.

研究想法新颖性验证

在顶刊数据库中系统性检索,评估研究想法的原创性,输出定位策略。

核心功能

  • 四维评估:相似度 / 方法差异 / 样本独特性 / 机制新颖性
  • 顶刊检索:JF / JFE / RFS / JME / arXiv / NBER
  • 中文顶刊:经济研究 / 金融研究 / 管理世界
  • 综合评分:HIGH (≥8) / MEDIUM (6-8) / LOW (<6)
  • 定位策略:差异化路径 + 潜在风险规避

工作流程

Step 1: 想法解析

将研究想法拆解为 3-5 个可检验的核心主张(Claims):

原始想法: "数字金融对中小企业创新的影响"

核心主张:
1. 数字金融能显著提升中小企业创新投入
2. 融资约束是主要作用机制
3. 东部地区效果强于西部地区
4. 对民营企业效果强于国有企业

每个 Claim 需包含:

  • 变量关系:[X] → [Y]
  • 假设方向:[正向/负向/倒U型]
  • 适用情境:[样本范围]

Step 2: 多源并行检索

对每个 Claim 分别检索,使用以下模板:

JF/JFE/RFS(英文顶刊)
server: user-brave-search
tool: brave_web_search
params: {
    "query": "site:jf.com digital finance SME innovation empirical"
}
# 替换: site:jfe.oxfordjournals.org, site:rfs.org
arXiv(近3年预印本)
server: user-arxiv
tool: semantic_search
params: {
    "query": "digital finance AND (SME OR \"small business\") AND (innovation OR R&D) AND (2023 OR 2024 OR 2025)"
}
NBER(工作论文)
server: user-nber-wp
tool: get_nber_papers
params: {
    "category": "corporate finance OR financial economics",
    "year_from": 2023
}
中文顶刊
server: user-brave-search
tool: brave_web_search
params: {
    "query": "site:er.cngp.org.cn OR site:jr.cass.org.cn 数字金融 中小企业 创新 实证"
}
# 经济研究: site:er.cngp.org.cn
# 金融研究: site:jr.cass.org.cn
# 管理世界: site:管理与世界.ajcass.com
补充检索(更宽泛)
server: user-openalex
tool: get_openalex_works
params: {
    "query": "digital finance innovation SMEs empirical",
    "per_page": 30
}

Step 3: 四维评估

对每个 Claim 逐一评估:

维度 评估问题 评分 (1-10)
相似度 (S) 已有多少研究做了一样的 X→Y? 1=完全相同, 10=从未做过
方法差异 (M) 你的方法与已有研究有何不同? 1=方法相同, 10=全新方法
样本独特性 (U) 数据/样本是否独特? 1=常用数据, 10=独有数据
机制新颖性 (N) 机制解释是否新颖? 1=常见机制, 10=全新机制

评估标准详解

相似度 (S)

  • 1-3:完全相同的 X→Y 已有多个顶刊研究
  • 4-6:相近主题(如数字金融→创新),但 X/Y 定义不同
  • 7-10:X→Y 组合从未被研究过

方法差异 (M)

  • 1-3:直接复用已有研究方法(如标准DID)
  • 4-6:有改进(如异质性DID、动态DID)
  • 7-10:引入全新方法或组合(如合成DID + 机器学习)

Read the full file on GitHub · 351 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. 12d ago First seen · 351 lines · 52 tokens per session scan A eabf480a58b3

Subscribe to this mod's changes

fin-novelty-check is a skill published in the GitHub repository csmar432/finai-research (100 stars, last pushed 4d ago), licensed MIT. It adds 52 tokens to every session and 3,060 once invoked, about $0.0003 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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