economic-calendar-fetcher

economic-calendar-fetcher is a skill for Claude Code, Codex from BaggaT236/AI-Trading-Skills. It costs 0 tokens per session (3,192 once invoked), scanned A, a copy of economic-calendar-fetcher, MIT.

A tool for fetching scheduled economic events and data releases, such as interest-rate decisions, employment reports, inflation figures, and GDP updates, from the Financial Modeling Prep service.

In plain words
What is it for?
Use it to build a chronological report of upcoming economic releases and assess which events may affect financial markets. It requires an FMP API key.
Why use it?
It removes the need to collect these market-moving dates manually and organize them into a calendar. It can return events for a chosen date range, up to 90 days.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to build a chronological report of upcoming economic releases and assess which events may affect financial markets. It requires an FMP API key.

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Install with agentmods
npx agentmods add skills/baggat236/ai-trading-skills/economic-calendar-fetcher
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 BaggaT236/AI-Trading-Skills --skill economic-calendar-fetcher
Clone the repo
git clone --depth 1 https://github.com/BaggaT236/AI-Trading-Skills

Made for: Claude Code, Codex.

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 economic-calendar-fetcher

README.md
[![agentmods](https://agentmods.dev/badge/skills/baggat236/ai-trading-skills/economic-calendar-fetcher/github.svg)](https://agentmods.dev/skills/baggat236/ai-trading-skills/economic-calendar-fetcher)
Your own site
<a href="https://agentmods.dev/skills/baggat236/ai-trading-skills/economic-calendar-fetcher"><img src="https://agentmods.dev/badge/skills/baggat236/ai-trading-skills/economic-calendar-fetcher/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 economic-calendar-fetcher

Your own site · 80×15
<a href="https://agentmods.dev/skills/baggat236/ai-trading-skills/economic-calendar-fetcher"><img src="https://agentmods.dev/badge/skills/baggat236/ai-trading-skills/economic-calendar-fetcher.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,192 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.
Origin 100% copy Near-identical to another mod 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 $0.00000 $0.03192
Opus 5 $0.00000 $0.01596
Sonnet 5 $0.00000 $0.00638
Haiku 4.5 $0.00000 $0.00319

Measured 12d ago against content hash 0deafe282462, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

economic-calendar-fetcher 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.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/get_economic_calendar.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Origin

This is a copy

100% identical to economic-calendar-fetcher — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

examples/weekly-trade-strategy/skills/economic-calendar-fetcher/SKILL.md · 362 lines

How it starts

The opening of the file, as written. The whole thing — 362 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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?"
  2. 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?"
  3. Specific Date Range Requests:

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

Read the full file on GitHub · 362 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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 · 362 lines · 0 tokens per session scan A 0deafe282462

Subscribe to this mod's changes

economic-calendar-fetcher is a skill published in the GitHub repository BaggaT236/AI-Trading-Skills (121 stars, last pushed 9d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 3,192 tokens. A static security scan graded it A with 0 findings. It is 100% identical to economic-calendar-fetcher, differing in 0 lines, and is treated as a copy.

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