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Agent Skill · 研究检索

economic-calendar-fetcher(经济日历获取器)

economic-calendar-fetcher 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

economic-calendar-fetcher 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 19,196。

总安装 5,717周安装 241GitHub Stars 1,137下载 1,889核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:economic-calendar-fetcher(经济日历获取器)
来源仓库:https://github.com/tradermonty/claude-trading-skills
仓库路径:skills/economic-calendar-fetcher
安装命令:
npx skills add https://github.com/tradermonty/claude-trading-skills --skill economic-calendar-fetcher
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/tradermonty/claude-trading-skills --skill economic-calendar-fetcher

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于查找、检索和筛选与宏观经济事件相关的日历信息。适合在交易策略制定、市场情绪分析或事件驱动研究中快速定位关键节点。通过关键词匹配帮助用户聚焦特定国家、指标或发布时间范围。使用前应确认是否依赖外部 API,注意调用频率与数据版权限制。建议结合原始文档了解支持的指标列表和输出格式。

economic-calendar-fetcher 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/economic-calendar-fetcher

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/tradermonty/claude-trading-skills --skill econ…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

economic-calendar-fetcher 怎么安装?

在终端执行 npx skills add https://github.com/tradermonty/claude-trading-skills --skill economic-calen…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

economic-calendar-fetcher 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

economic-calendar-fetcher 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

economic-calendar-fetcher 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

economic-calendar-fetcher 用的人多吗?

公开数据是累计安装 5,717 次,近一周安装 241 次,下载 1,889 次,GitHub 1,137 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

economic-calendar-fetcher 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 来源仓库有 1,137 星,维护活跃度相对可查。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
economic-calendar-fetcher

经济日历获取器 · 本页

5,7171,137接触敏感数据未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Economic Calendar Fetcher

Overview

Retrieve upcoming economic events and data releases from the Financial Modeling Prep (FMP) Economic Calendar API. This skill fetches scheduled economic indicators including central bank monetary policy decisions, employment reports, inflation data (CPI/PPI), GDP releases, retail sales, manufacturing data, and other market-moving events that impact financial markets.

The skill uses a Python script to query the FMP API and returns raw JSON or text output. The assistant then filters events, assesses market impact, and generates a chronological Markdown report for each scheduled event. No files are generated automatically.

Key Capabilities:

  • Fetch economic events for specified date ranges (max 90 days)
  • Support flexible API key provision (environment variable or CLI argument)
  • Filter by impact level, country, or event type (filtering performed by the assistant)
  • Present filtered results as structured Markdown reports with impact analysis (assistant-generated, not script-generated)
  • Default to next 7 days for quick market outlook

Data Source:

  • FMP Economic Calendar API: https://financialmodelingprep.com/api/v3/economic_calendar
  • Covers major economies: US, EU, UK, Japan, China, Canada, Australia
  • Event types: Central bank decisions, employment, inflation, GDP, trade, housing, surveys

When to Use This Skill

Use this skill when the user requests:

  1. Economic Calendar Queries:

- "What economic events are coming up this week?" - "Show me the economic calendar for the next two weeks" - "When is the next FOMC meeting?" - "What major economic data is being released next month?"

  1. Market Event Planning:

- "What should I watch for in the markets this week?" - "Are there any high-impact economic releases coming?" - "When is the next jobs report / CPI release / GDP report?"

  1. Specific Date Range Requests:

- "Get economic events from January 1 to January 31" - "What's on the economic calendar for Q1 2025?"

  1. Country-Specific Queries:

- "Show me US economic data releases next week" - "What ECB events are scheduled?" - "When is Japan releasing their inflation data?"

DO NOT use this skill for:

  • Past economic events (use market-news-analyst for historical analysis)
  • Corporate earnings calendars (this skill excludes earnings)
  • Real-time market data or live quotes
  • Technical analysis or chart interpretation

Prerequisites

  • FMP API Key (required): Sign up at https://financialmodelingprep.com for a free key (250 requests/day). Set via FMP_API_KEY environment variable or pass --api-key to the script.
  • Python 3.10+: Required to run skills/economic-calendar-fetcher/scripts/get_economic_calendar.py.
  • No third-party packages: The script uses only the Python standard library.

Workflow

Follow these steps to fetch and analyze the economic calendar:

Step 1: Obtain FMP API Key

Check for API key availability (in priority order):

  1. Recommended: Check if FMP_API_KEY environment variable is set — this keeps the key out of session logs
  2. Acceptable: Use --api-key CLI argument for one-off runs
  3. Not recommended: Asking the user to paste the key into chat — session logs may retain it
  4. If user doesn't have an API key, provide instructions:

- Visit https://financialmodelingprep.com - Sign up for free account (250 requests/day limit) - Navigate to API dashboard to obtain key

Example user interaction:

User: "Show me economic events for next week"
Assistant: "I'll fetch the economic calendar. I'll use the FMP_API_KEY environment variable if it's set. Otherwise, please pass the key via --api-key when running the script."

Step 2: Determine Date Range

Set appropriate date range based on user request:

Default (no specific dates): Today + 7 days User specifies period: Use exact dates (validate format: YYYY-MM-DD) Maximum range: 90 days (FMP API limitation)

Examples:

  • "Next week" → Today to +7 days
  • "Next two weeks" → Today to +14 days
  • "January 2025" → 2025-01-01 to 2025-01-31
  • "Q1 2025" → 2025-01-01 to 2025-03-31

Validate date range:

  • Ensure start date ≤ end date
  • Ensure range ≤ 90 days
  • Warn if querying past dates

Step 3: Execute API Fetch Script

Run the get_economic_calendar.py script with appropriate parameters:

Basic usage (default 7 days):

python3 skills/economic-calendar-fetcher/scripts/get_economic_calendar.py --api-key YOUR_KEY

With specific date range:

python3 skills/economic-calendar-fetcher/scripts/get_economic_calendar.py \
  --from 2025-01-01 \
  --to 2025-01-31 \
  --api-key YOUR_KEY \
  --format json

Using environment variable (no --api-key needed):

export FMP_API_KEY=your_key_here
python3 skills/economic-calendar-fetcher/scripts/get_economic_calendar.py \
  --from 2025-01-01 \
  --to 2025-01-07

Script parameters:

  • --from: Start date (YYYY-MM-DD) - default: today
  • --to: End date (YYYY-MM-DD) - default: today + 7 days
  • --api-key: FMP API key (optional if FMP_API_KEY env var set)
  • --format: Output format (json or text) - default: json
  • --output: Output file path (optional, default: stdout)

Handle errors:

  • Invalid API key → Ask user to verify key
  • Rate limit exceeded (429) → Suggest waiting or upgrading FMP tier
  • Network errors → Check your connection and re-run the script
  • Invalid date format → Provide correct format example

Step 4: Parse and Filter Events

Process the JSON response from the script:

  1. Parse event data: Extract all events from API response
  2. Apply user filters if specified:

- Impact level: "High", "Medium", "Low" - Country: "US", "EU", "JP", "CN", etc. - Event type: FOMC, CPI, Employment, GDP, etc. - Currency: USD, EUR, JPY, etc.

Filter examples:

  • "Show only high-impact events" → Filter impact == "High"
  • "US events only" → Filter country == "US"
  • "Central bank decisions" → Search event name for "Rate", "Policy", "FOMC", "ECB", "BOJ"

Event data structure:

{
  "date": "2025-01-15 14:30:00",
  "country": "US",
  "event": "Consumer Price Index (CPI) YoY",
  "currency": "USD",
  "previous": 2.6,
  "estimate": 2.7,
  "actual": null,
  "change": null,
  "impact": "High",
  "changePercentage": null
}

Step 5: Assess Market Impact

Evaluate the market significance of each event:

Impact Level Classification (from FMP):

  • High Impact: Major market-moving events

- FOMC rate decisions, ECB/BOJ policy meetings - Non-Farm Payrolls (NFP), CPI, GDP - Market typically shows 0.5-2%+ intraday volatility

  • Medium Impact: Significant but less volatile

- Retail Sales, Industrial Production - PMI surveys, Consumer Confidence - Housing data, Durable Goods Orders

  • Low Impact: Minor indicators

- Weekly jobless claims (unless extreme) - Regional manufacturing surveys - Minor auction results

Additional Context Factors:

  1. Current Market Sensitivity:

- High inflation environment → CPI/PPI elevated importance - Recession fears → Employment data more critical - Rate cut speculation → Central bank meetings crucial

  1. Surprise Potential:

- Compare estimate vs. previous reading - Large expected changes = higher attention - Consensus uncertainty = higher impact potential

  1. Event Clustering:

- Multiple related events same day = amplified impact - Example: CPI + Retail Sales + Fed speech = Very High impact day

  1. Forward Significance:

- Does this event influence upcoming central bank decisions? - Is this a preliminary or final reading? - Will this data be revised?

Step 6: Generate Output Report

Responsibility: The script outputs raw JSON or text. This step is performed by the assistant using the script's output. No Markdown files are generated automatically; results are displayed in chat and can be saved to reports/ on request.

Create structured markdown report with the following sections:

Report Header:

# Economic Calendar
**Period:** [Start Date] to [End Date]
**Report Generated:** [Timestamp]
**Total Events:** [Count]
**High Impact Events:** [Count]

Event Listing (Chronological):

For each event, provide:

## [Date] - [Day of Week]

### [Event Name] ([Impact Level])
- **Country:** [Country Code] ([Currency])
- **Time:** [HH:MM UTC]
- **Previous:** [Value]
- **Estimate:** [Consensus Forecast]
- **Impact Assessment:** [Your analysis]

**Market Implications:**
[2-3 sentences on why this matters, what markets watch for, typical reaction patterns]

---

Example Event Entry:

## 2025-01-15 - Wednesday

### Consumer Price Index (CPI) YoY (High Impact)
- **Country:** US (USD)
- **Time:** 14:30 UTC (8:30 AM ET)
- **Previous:** 2.6%
- **Estimate:** 2.7%
- **Impact Assessment:** Very High - Core inflation metric for Fed policy decisions

**Market Implications:**
CPI reading above estimate (>2.7%) likely strengthens hawkish Fed expectations, potentially pressuring equities and supporting USD. Reading at or below 2.7% could reinforce disinflation narrative and support risk assets. Options market pricing 1.2% S&P 500 move on release day.

---

Summary Section:

Add analytical summary at the end:

## Key Takeaways

**Highest Impact Days:**
- [Date]: [Events] - [Combined impact rationale]
- [Date]: [Events] - [Combined impact rationale]

**Central Bank Activity:**
- [Summary of any scheduled Fed/ECB/BOJ meetings or speeches]

**Major Data Releases:**
- Employment: [NFP, Unemployment Rate dates]
- Inflation: [CPI, PPI dates]
- Growth: [GDP, Retail Sales dates]

**Market Positioning Considerations:**
[2-3 bullets on how traders might position around these events]

**Risk Events:**
[Highlight any particularly high-uncertainty or surprise-potential events]

Filtering Notes:

If user requested specific filters, note at top:

**Filters Applied:**
- Impact Level: High only
- Country: US
- Events shown: [X] of [Y] total events in date range

Output:

  • Results are displayed in chat. No files are generated automatically.
  • To save raw JSON/text data: use --output reports/economic_calendar_[START]_to_[END].json when running the script.
  • To save the Markdown report: ask the assistant to write it to reports/ after generating it in chat.

Assistant-Generated Report Format

Markdown structure requirements:

  1. Chronological ordering: Events sorted by date and time (earliest first)
  2. Impact level indicators: Use (High Impact), (Medium Impact), (Low Impact) labels
  3. Time zone clarity: Always specify UTC; ET/PT conversions are performed by the assistant based on US DST calendar
  4. Data completeness: Include all available fields (previous, estimate, actual if past)
  5. Null handling: Display "N/A" or "No estimate" for null values
  6. Impact assessment: Every high/medium impact event must have market implications analysis

Table format option (for dense listings):

| Date/Time (UTC) | Event | Country | Impact | Previous | Estimate | Assessment |
|-----------------|-------|---------|--------|----------|----------|------------|
| 01-15 14:30 | CPI YoY | US | High | 2.6% | 2.7% | Core inflation metric |

Language: All reports in English

Resources

Python Script:

  • skills/economic-calendar-fetcher/scripts/get_economic_calendar.py: Main API fetch script with CLI interface

Reference Documentation:

  • references/fmp_api_documentation.md: Complete FMP Economic Calendar API reference

- Authentication and API key management - Request parameters and date formats - Response field definitions - Rate limits and error handling - Best practices for caching and efficiency

API Details:

  • Endpoint: https://financialmodelingprep.com/api/v3/economic_calendar
  • Authentication: API key required (free tier: 250 requests/day)
  • Max date range: 90 days per request
  • Response format: JSON array of event objects
  • Rate limits: 5 requests/second (free tier)

Event Coverage:

  • Major economies: US, EU, UK, Japan, China, Canada, Australia, Switzerland
  • Event categories: Monetary policy, Employment, Inflation, GDP, Trade, Housing, Surveys
  • Update frequency: Real-time (events added/updated as scheduled)
  • Historical data: Available for past events with actual values

Usage Tips:

  1. Cache results to minimize API calls (events rarely change once scheduled)
  2. Query 7-30 day ranges for optimal request efficiency
  3. Don't query >6 months in future (sparse data, speculative dates)
  4. Refresh cache daily for upcoming week to catch time changes
  5. Use smaller ranges (1-7 days) for real-time event monitoring

Error Handling:

  • API key errors: Clear user guidance for obtaining free key
  • Rate limits (429): Suggest waiting or upgrading FMP tier; re-run the script after the wait
  • Network failures: Check connection and re-run; no automatic retry or cache in the script
  • Invalid dates: Validation with helpful error messages

平台分布

Codex

33.48%
按下载量换算632

Claude

30.87%
按下载量换算583

Cursor

18.54%
按下载量换算350

Gemini CLI

9.3%
按下载量换算176

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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