fin-generate-idea

fin-generate-idea is a skill for Claude Code from csmar432/finai-research. It costs 53 tokens per session (4,699 once invoked), scanned A, original, MIT.

A workflow for generating and ranking possible economics and finance research ideas. It uses existing literature to find unfinished questions, then checks whether each idea can be tested with available data.

In plain words
What is it for?
Use it when you have a research topic and want 8–12 possible studies. It helps analyze the field, identify gaps, check data sources, mark ideas that need restricted or simulated data, and produce a research-idea report.
Why use it?
It helps filter out ideas with no practical data path before they consume research time. It also gives a ranked shortlist based on novelty, data feasibility, and publication potential.

Skill for Claude Code

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

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is python scripts/research_framework/pipeline.py \.

Good fit Use it when you have a research topic and want 8–12 possible studies. It helps analyze the field, identify gaps, check data sources, mark ideas that need restricted or simulated data, and produce a research-idea report.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/csmar432/finai-research
agentmods
npx agentmods add skills/csmar432/finai-research/fin-generate-idea

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-generate-idea

README.md
[![agentmods](https://agentmods.dev/badge/skills/csmar432/finai-research/fin-generate-idea/github.svg)](https://agentmods.dev/skills/csmar432/finai-research/fin-generate-idea)
Your own site
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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-generate-idea

Your own site · 80×15
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Per session 53 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,699 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 warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Tool Misuse · line 537
    Tool defaults are unsafe or overly permissive (e.g. disabled TLS verification, no authentication, world-writable permissions). Unsafe defaults widen the attack surface.
    Fix: Override unsafe defaults with secure settings (verify=True, auth required, restrictive permissions). Review and harden all tool configurations.
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 $0.00053 $0.04699
Opus 5 $0.00026 $0.02350
Sonnet 5 $0.00011 $0.00940
Haiku 4.5 $0.00005 $0.00470

Measured 12d ago against content hash ea3d5327c530, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

fin-generate-idea 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-generate-idea/SKILL.md · 543 lines

How it starts

The opening of the file, as written. The whole thing — 543 lines — stays where its author put it; the contents beside it link to each section on GitHub.

经济金融研究想法生成器

针对研究方向 $ARGUMENTS 生成 8-12 个排序研究想法,经过数据可行性筛选后输出推荐名单。

流程概览

研究方向输入
     ↓
阶段1: 研究领域解析 + 约束提取
     ↓
阶段2: 文献提取 — 使用 MCP 获取高影响力论文
     ↓
阶段3: 缺口分析 — 识别领域内"未完成"的工作
     ↓
阶段4: 想法生成 — 基于文献生成 8-12 个想法
     ↓
阶段5: 【强制】数据可行性筛选 — 对每个想法运行数据源检查
     ↓
阶段6: 过滤标记 — 无数据路径的想法标记"需授权模拟"
     ↓
阶段7: 综合排序 — noverlty × 0.4 + data × 0.3 + publish × 0.3
     ↓
输出: IDEA_REPORT.md

触发条件

当用户明确要求生成具体研究想法时触发,例如:

  • "有什么关于[领域]的研究想法"
  • "生成[领域]的研究idea"
  • "帮我找[领域]的研究方向"
  • "我想研究[主题],有什么新想法"

输出文件

output/fin-ideas/
├── IDEA_REPORT.md         ← 完整想法报告(8-12个想法,含评分)
├── IDEA_DATA_CHECK.md     ← 数据可行性检查结果
└── IDEA_CANDIDATES.md     ← 精简版(TOP 3-5)

阶段详解

阶段1: 研究领域解析

1.1 解析研究领域

识别研究方向所属的宏观领域:

领域 核心关键词 典型研究问题
绿色金融 ESG、碳排放、绿色债券、气候风险、绿色信贷 绿色政策效果、环境信息披露
数字金融 Fintech、数字支付、互联网金融、API银行 数字普惠、金融科技赋能
碳经济学 碳交易、碳配额、碳关税、减排激励 碳市场效率、政策有效性
宏观金融 货币政策传导、金融周期、系统性风险 政策传导机制、金融稳定
公司金融 融资约束、资本结构、公司治理、并购 融资决策优化、公司价值
资产定价 因子模型、异常收益、机构投资者 定价因子、收益预测
行为金融 投资者情绪、散户行为、羊群效应 行为偏差、市场效率
金融科技 区块链、数字货币、开放银行 新技术应用、模式创新
1.2 提取约束

从用户输入中提取约束条件:

constraints = {
    "target_journal": "JF/JFE/RFS/经济研究/金融研究/...",
    "method_preference": "DID/IV/RDD/机器学习/...",
    "data_preference": "A股/美股/宏观/...",
    "time_range": "2010-2024/特定事件窗口/...",
    "sample_restriction": "创业板/国有企业/...",
}

阶段2: 文献提取

2.1 MCP 多源检索

必须按以下顺序执行检索

# 第1步:NBER 工作论文(优先)
CallMcpTool: user-nber-wp -> search_nber_papers
  query: "[研究领域] + China + empirical"
  year_from: 2023

# 第2步:OpenAlex(250M+论文)
CallMcpTool: user-openalex -> get_openalex_works
  query: "[研究领域] + [核心机制] + China"
  per_page: 30

# 第3步:中文顶刊(A股必查)
CallMcpTool: user-brave-search -> brave_web_search
  query: "经济研究 金融研究 管理世界 [核心关键词]"
  num_results: 15

# 第4步:ArXiv(方法论文)
CallMcpTool: user-arxiv -> semantic_search
  query: "[研究领域] + empirical methods China"
  max_results: 15
2.2 高影响力论文筛选

从检索结果中筛选高影响力论文:

Read the full file on GitHub · 543 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 · 543 lines · 53 tokens per session scan A ea3d5327c530

Subscribe to this mod's changes

fin-generate-idea is a skill published in the GitHub repository csmar432/finai-research (100 stars, last pushed 3d ago), licensed MIT. It adds 53 tokens to every session and 4,699 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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