hotspot-qa
Provides information extraction and structured analysis for fund-related hot-topic questions.
Install
mkdir -p .claude/skills/hotspot-qa && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/16340" && unzip -o skill.zip -d .claude/skills/hotspot-qa && rm skill.zipInstalls to .claude/skills/hotspot-qa
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
面向基金品牌与内容领域的热点问答任务Skill，围绕「热点问答助手」场景提供信息抽取、结构化分析与结果输出。Key capabilities
- →Extract information from financial documents (fund announcements, reports, prospectuses)
- →Analyze net value, income time series, holdings, and asset allocation disclosures
- →Process sales/service records, customer feedback, and Q&A materials
- →Incorporate compliance standards and brand content guidelines
- →Output structured content drafts and key selling points
- →Organize question lists and standard answers based on input materials
How it works
The skill processes various financial documents and data, extracts key information, and applies brand and compliance guidelines to generate structured content drafts, question lists, and standard answers for hot topic Q&A tasks in the fund industry.
Inputs & outputs
When to use hotspot-qa
- →Generating fund content
- →Structuring market research data
- →Creating compliance-reviewed Q&A
About this skill
热点问答助手 Skill
数据来源
1. 输入类型
- 基金公告/定期报告/招募说明书/产品说明材料
- 净值与收益时间序列、持仓与资产配置披露
- 销售/服务记录、客户反馈与问答素材(如适用)
- 合规口径与品牌内容规范(如适用)
2. 主要数据要素
- 品牌调性与内容规范
- 热点事件与市场数据
- 产品亮点与关键图表素材
- 受众画像与传播渠道反馈
- 合规审校规则与对外口径
3. 质量要求
- 输入信息尽量完整，包含时间区间、基金代码与核心指标
- 若来自 OCR/截图，请尽量校对错字与断行
- 对于未披露的数据需明确标注“缺失/待补充”
核心能力
- 围绕目标人群输出结构化内容草稿与关键卖点
- 控制语气风格与风险提示，形成可直接使用的内容模板
- 基于输入资料组织问题清单与标准回答
- 提供引用来源与口径一致性说明
输出结构
1. 基础字段
- skill
- domain
- scene
- input_summary
- key_findings
- data_quality
- limitations
2. 场景扩展模块(按需输出)
- content
- draft
- key_points
- compliance_notes
- qa
- questions
- answers
- citations
使用示例
1. 安装依赖
pip install -r requirements.txt
2. 运行脚本
python scripts/main.py --input sample.txt --output-json result.json --output-md report.md
3. 输出示例
{
"skill": "热点问答助手",
"domain": "品牌与内容",
"scene": "热点问答",
"input_summary": {
"fund_code": "000000",
"fund_name": "示例基金",
"period": "2024Q4",
"data_coverage": "净值/持仓/披露/市场"
},
"key_findings": [
"关键结论1",
"关键结论2"
],
"data_quality": {
"has_text": true,
"text_length": 1200
},
"limitations": [
"仅基于输入信息形成初步判断"
]
}
注意事项与限制
- 仅对输入文本进行结构化与初步判断，不替代人工投研或合规结论
- 若缺少关键数据(持仓、基准、时间区间)，结果需明确提示不完整
- 输出建议应结合实际业务口径与监管要求复核
适用场景
- 业务条线: 品牌与内容
- 场景/能力: 热点问答
- 典型用户: 研究员、产品经理、渠道与客服、合规审查或内容运营人员
License
- 代码部分遵循 MIT License
- 数据来源与披露口径需遵循对应数据供应商与监管要求
When not to use it
- →When the user wants to replace manual investment research or compliance conclusions
- →When critical data (holdings, benchmarks, time ranges) is missing
- →When the output suggestions do not need to be reviewed against actual business standards and regulatory requirements
Limitations
- →Only performs structuring and preliminary judgment on input text, not a substitute for manual investment research or compliance conclusions
- →If critical data is missing, the results will explicitly prompt incompleteness
- →Output suggestions should be reviewed against actual business standards and regulatory requirements
How it compares
This skill specifically targets hot topic Q&A tasks in the fund brand and content domain, providing structured information extraction and analysis tailored to financial documents and compliance, unlike general content generation tools.
Compared to similar skills
hotspot-qa side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| hotspot-qa (this skill) | 0 | 5mo | Review | Intermediate |
| mm-report-writer | 0 | 2mo | No flags | Advanced |
| quant-analyst | 103 | 3mo | No flags | Advanced |
| stock-analyzer | 71 | 2mo | Review | Beginner |
Try saying
Example prompts that trigger this skill in your AI assistant.
More by aifinlab
View all by aifinlab →You might also like
mm-report-writer
ShinyGua
Generates daily or weekly research report from evidence cards, quant summary, thesis map, and company profile
quant-analyst
zenobi-us
Expert quantitative analyst specializing in financial modeling, algorithmic trading, and risk analytics. Masters statistical methods, derivatives pricing, and high-frequency trading with focus on mathematical rigor, performance optimization, and profitable strategy development.
stock-analyzer
FrancyJGLisboa
Provides comprehensive technical analysis for stocks and ETFs using RSI, MACD, Bollinger Bands, and other indicators. Activates when user requests stock analysis, technical indicators, trading signals, or market data for specific ticker symbols.
creating-financial-models
anthropics
This skill provides an advanced financial modeling suite with DCF analysis, sensitivity testing, Monte Carlo simulations, and scenario planning for investment decisions
reconciliation
anthropics
Reconcile accounts by comparing GL balances to subledgers, bank statements, or third-party data. Use when performing bank reconciliations, GL-to-subledger recs, intercompany reconciliations, or identifying and categorizing reconciling items.
analyzing-financial-statements
anthropics
This skill calculates key financial ratios and metrics from financial statement data for investment analysis