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Arrays Data Api Macro And Economics

skill-arraysdata-arrays-skills-arrays-data-api-macro-and-economics · by ArraysData

Guides the agent to call Arrays REST APIs for macro and economics data (treasury rates, economic indicators, CPI, GDP, unemployment, inflation, consumer sentiment, macro index/forex/commodity, VIX). Use when the user asks about macroeconomic indicators, CPI release dates, economic data announcements, interest rates, forex, commodity prices (gold GCUSD, silver SILUSD, oil CLUSD), market index data…

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Install

$ agentstack add skill-arraysdata-arrays-skills-arrays-data-api-macro-and-economics

Open-source listing — not yet scanned by AgentStack. Follow the source repository for install instructions.

Security review

⚠ Flagged

1 finding(s); flagged for manual review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures
  • high Reads credentials/environment and may exfiltrate them.

What it can access

  • Network access Used
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets Used
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

Arrays Data API — Macro and Economics

Domain: macro_and_economics_data. Treasury rates, economic indicators, macro index/forex/commodity historical and real-time data, and VIX.

Base URL and auth

  • Base: ARRAYS_API_BASE_URL env var (default https://data-tools.prd.space.id)
  • Auth: Send X-API-Key: header on every request. Read the key from env ARRAYS_API_KEY or .env file.

Response envelope

All endpoints return a unified JSON envelope:

{ "success": true, "request_id": "...", "data": [ ... ] }
  • data is always an array (even for single-object results).
  • Access data in Python: body["data"]
  • Always check body["success"] before accessing data.

Endpoints

  • Prefix: /api/v1/macro/

| Method | Path | File | Description | |--------|------|------|-------------| | GET | economic-indicators | economic-indicators | Economic indicators (CPI, GDP, unemployment, etc.) | | GET | index/historical | macro-index-historical | Index historical data | | GET | forex/historical | macro-forex-historical | Forex historical data | | GET | commodity/historical | macro-commodity-historical | Commodity historical data | | GET | index/real-time | macro-index-real-time | Index real-time data | | GET | forex/real-time | macro-forex-real-time | Forex real-time data | | GET | commodity/real-time | macro-commodity-real-time | Commodity real-time data | | GET | forex/symbols | macro-forex-symbol-list | Available forex symbols | | GET | commodity/symbols | macro-commodity-symbol-list | Available commodity symbols | | GET | treasury-rates | rates | US treasury yield rates |

> For detailed parameters, response fields, and examples for a specific endpoint, read references/.md in this skill directory.

Example

import requests, os
base = os.environ["ARRAYS_API_BASE_URL"]
key = os.environ["ARRAYS_API_KEY"]

# Economic indicators — get US CPI
resp = requests.get(f"{base}/api/v1/macro/economic-indicators",
    params={"indicator_type": "CPI", "time_type": "CALENDAR_START_DATE",
            "start_time": 1719792000, "end_time": 1722470400},
    headers={"X-API-Key": key})
body = resp.json()
obs = body["data"][0]["observations"]  # data is array, take first element
print(obs[0]["date"], obs[0]["value"])

# Commodity historical — get gold price
resp = requests.get(f"{base}/api/v1/macro/commodity/historical",
    params={"symbol": "GCUSD", "start_time": 1746057600, "end_time": 1746057600},
    headers={"X-API-Key": key})
body = resp.json()
bars = body["data"]  # array of OHLCV bars
print(bars[0]["close"])

# Treasury rates
resp = requests.get(f"{base}/api/v1/macro/treasury-rates",
    params={"start_time": to_ts(2025, 1, 1), "end_time": to_ts(2025, 3, 1)},
    headers={"X-API-Key": key})
body = resp.json()
rates = body["data"][0]["rates"]  # nested: body["data"][0] has {"rates": [...]}
print(rates[0]["year10"])

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.