Agent skill

usfiscaldata

Query the U.S. Treasury Fiscal Data API for federal financial data including national debt, government spending, revenue, interest rates, exchange rates, and savings bonds. Access 54 datasets and 182 data tables with no API key required. Use when working with U.S. federal fiscal data, national debt tracking (Debt to the Penny), Daily Treasury Statements, Monthly Treasury Statements, Treasury securities auctions, interest rates on Treasury securities, foreign exchange rates, savings bonds, or any U.S. government financial statistics.

View SKILL.md on GitHub Repository
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Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/other/usfiscaldata-k-dense-ai-scientific-agent-ski

Metadata

Additional technical details for this skill

skill author
K-Dense Inc.

SKILL.md

U.S. Treasury Fiscal Data API

Free, open REST API from the U.S. Department of the Treasury for federal financial data. No API key or registration required.

Base URL: https://api.fiscaldata.treasury.gov/services/api/fiscal_service

Quick Start

python
import requests
import pandas as pd

BASE_URL = "https://api.fiscaldata.treasury.gov/services/api/fiscal_service"

# Get the current national debt (Debt to the Penny)
resp = requests.get(f"{BASE_URL}/v2/accounting/od/debt_to_penny", params={
    "sort": "-record_date",
    "page[size]": 1
})
data = resp.json()["data"][0]
print(f"Total public debt as of {data['record_date']}: ${float(data['tot_pub_debt_out_amt']):,.0f}")
python
# Get Treasury exchange rates for recent quarters
resp = requests.get(f"{BASE_URL}/v1/accounting/od/rates_of_exchange", params={
    "fields": "country_currency_desc,exchange_rate,record_date",
    "filter": "record_date:gte:2024-01-01",
    "sort": "-record_date",
    "page[size]": 100
})
df = pd.DataFrame(resp.json()["data"])

Authentication

None required. The API is fully open and free.

Core Parameters

Parameter Example Description
fields= fields=record_date,tot_pub_debt_out_amt Select specific columns
filter= filter=record_date:gte:2024-01-01 Filter records
sort= sort=-record_date Sort (prefix - for descending)
format= format=json Output format: json, csv, xml
page[size]= page[size]=100 Records per page (default 100)
page[number]= page[number]=2 Page index (starts at 1)

Filter operators: lt, lte, gt, gte, eq, in

python
# Multiple filters separated by comma
"filter=country_currency_desc:in:(Canada-Dollar,Mexico-Peso),record_date:gte:2024-01-01"

Key Datasets & Endpoints

Debt

Dataset Endpoint Frequency
Debt to the Penny /v2/accounting/od/debt_to_penny Daily
Historical Debt Outstanding /v2/accounting/od/historical_debt_outstanding Annual
Schedules of Federal Debt /v1/accounting/od/schedules_fed_debt Monthly

Daily & Monthly Statements

Dataset Endpoint Frequency
DTS Operating Cash Balance /v1/accounting/dts/operating_cash_balance Daily
DTS Deposits & Withdrawals /v1/accounting/dts/deposits_withdrawals_operating_cash Daily
Monthly Treasury Statement (MTS) /v1/accounting/mts/mts_table_1 (16 tables) Monthly

Interest Rates & Exchange

Dataset Endpoint Frequency
Average Interest Rates on Treasury Securities /v2/accounting/od/avg_interest_rates Monthly
Treasury Reporting Rates of Exchange /v1/accounting/od/rates_of_exchange Quarterly
Interest Expense on Public Debt /v2/accounting/od/interest_expense Monthly

Securities & Auctions

Dataset Endpoint Frequency
Treasury Securities Auctions Data /v1/accounting/od/auctions_query As Needed
Treasury Securities Upcoming Auctions /v1/accounting/od/upcoming_auctions As Needed
Average Interest Rates /v2/accounting/od/avg_interest_rates Monthly

Savings Bonds

Dataset Endpoint Frequency
I Bonds Interest Rates /v2/accounting/od/i_bond_interest_rates Semi-Annual
U.S. Treasury Savings Bonds: Issues, Redemptions & Maturities /v1/accounting/od/sb_issues_redemptions Monthly

Response Structure

json
{
  "data": [...],
  "meta": {
    "count": 100,
    "total-count": 3790,
    "total-pages": 38,
    "labels": {"field_name": "Human Readable Label"},
    "dataTypes": {"field_name": "STRING|NUMBER|DATE|CURRENCY"},
    "dataFormats": {"field_name": "String|10.2|YYYY-MM-DD"}
  },
  "links": {"self": "...", "first": "...", "prev": null, "next": "...", "last": "..."}
}

Note: All values are returned as strings. Convert as needed (e.g., float(), pd.to_datetime()). Null values appear as the string "null".

Common Patterns

Load all pages into a DataFrame

python
def fetch_all_pages(endpoint, params=None):
    params = params or {}
    params["page[size]"] = 10000  # max size to minimize requests
    resp = requests.get(f"{BASE_URL}{endpoint}", params=params)
    result = resp.json()
    df = pd.DataFrame(result["data"])
    return df

Aggregation (automatic sum)

Omitting grouping fields triggers automatic aggregation:

python
# Sum all deposits/withdrawals by record_date and transaction type
resp = requests.get(f"{BASE_URL}/v1/accounting/dts/deposits_withdrawals_operating_cash", params={
    "fields": "record_date,transaction_type,transaction_today_amt"
})

Reference Files

  • api-basics.md — URL structure, HTTP methods, versioning, data types
  • parameters.md — All parameters with detailed examples and edge cases
  • datasets-debt.md — Debt datasets: Debt to the Penny, Historical Debt, Schedules of Federal Debt, TROR
  • datasets-fiscal.md — Daily Treasury Statement, Monthly Treasury Statement, revenue, spending
  • datasets-interest-rates.md — Average interest rates, exchange rates, TIPS/CPI, certified interest rates
  • datasets-securities.md — Treasury auctions, savings bonds, SLGS, buybacks
  • response-format.md — Response objects, error handling, pagination, response codes
  • examples.md — Python, R, and pandas code examples for common use cases

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