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Usfiscaldata

K-DenseCommunityCreated by K-Dense Inc.

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From the author

Queries the U.S. Treasury Fiscal Data REST API for federal financial data. No API key required. Use for national debt (Debt to the Penny), Daily Treasury Statements, Monthly Treasury Statements, Treasury securities auctions, interest rates, foreign exchange rates, savings bonds, or U.S. government revenue and spending statistics.
— the description by K-Dense Inc.

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The usfiscaldata skill provides a programmatic interface to the U.S. Department of the Treasury Fiscal Data REST API. It allows users to retrieve a wide range of federal financial information, including national debt statistics, daily and monthly treasury statements, interest rates, foreign exchange rates, and securities auction data. The API is open, requires no authentication or API keys, and returns data in JSON format, which can be easily parsed using standard tools like Python's requests and pandas libraries.

What it does

  • Queries federal financial datasets including national debt and treasury statements.
  • Supports filtering, sorting, and field selection via URL parameters.
  • Provides access to historical debt data dating back to 1790.
  • Enables retrieval of interest rates, foreign exchange rates, and savings bond information.
  • Handles pagination for large datasets through metadata links.
  • Offers structured data suitable for integration into data analysis workflows.

When to use it

  • When you need to incorporate U.S. government financial statistics into research or analysis.
  • When building applications that track national debt or treasury securities auctions.
  • When performing historical analysis on U.S. fiscal policy and government spending.
  • When you require official government reporting rates for foreign currency exchange.

Advantages

  • No API key or registration required for access.
  • Direct access to authoritative U.S. Treasury data.
  • Flexible query parameters for precise data extraction.
  • Compatible with standard data science tools like pandas and R.

Usage examples

“Get the latest total public debt outstanding.”
The agent queries the /v2/accounting/od/debt_to_penny endpoint and returns the most recent total public debt amount.
“Find all treasury exchange rates for 2024.”
The agent filters the /v1/accounting/od/rates_of_exchange endpoint for records from 2024-01-01 onwards and returns the requested data.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/k-dense-ai/usfiscaldata/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip usfiscaldata.zip -d .agents/skills

Documentation by K-Dense Inc.

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

Browse the current dataset catalog via the dataset search. Verify endpoint paths on each dataset's API Quick Guide — paths change over time.

Installation

uv pip install requests pandas

Quick Start

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
}, timeout=30)
resp.raise_for_status()
data = resp.json()["data"][0]
print(f"Total public debt as of {data['record_date']}: ${float(data['tot_pub_debt_out_amt']):,.0f}")
# Preview Treasury exchange-rate rows for recent quarters (first page only)
resp = requests.get(f"{BASE_URL}/v1/accounting/od/rates_of_exchange", params={
    "fields": "country_currency_desc,exchange_rate,record_date,effective_date",
    "filter": "record_date:gte:2024-01-01",
    "sort": "-record_date",
    "page[size]": 100
}, timeout=30)
resp.raise_for_status()
df = pd.DataFrame(resp.json()["data"])

Authentication

None required. The API is fully open and free.

Core Parameters

ParameterExampleDescription
fields=fields=record_date,tot_pub_debt_out_amtSelect specific columns
filter=filter=record_date:gte:2024-01-01Filter records
sort=sort=-record_dateSort (prefix - for descending)
format=format=jsonOutput format: json, csv, xml
page[size]=page[size]=100Records per page (default 100)
page[number]=page[number]=2Page index (starts at 1)

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

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

Key Datasets & Endpoints

Debt
DatasetEndpointFrequency
Debt to the Penny/v2/accounting/od/debt_to_pennyDaily
Historical Debt Outstanding/v2/accounting/od/debt_outstandingAnnual
Schedules of Federal Debt/v1/accounting/od/schedules_fed_debtMonthly
Daily & Monthly Statements
DatasetEndpointFrequency
DTS Operating Cash Balance/v1/accounting/dts/operating_cash_balanceDaily
DTS Deposits & Withdrawals/v1/accounting/dts/deposits_withdrawals_operating_cashDaily
Monthly Treasury Statement (MTS)/v1/accounting/mts/mts_table_1 (18 tables — see datasets-fiscal.md)Monthly
Interest Rates & Exchange
DatasetEndpointFrequency
Average Interest Rates on Treasury Securities/v2/accounting/od/avg_interest_ratesMonthly
Treasury Reporting Rates of Exchange/v1/accounting/od/rates_of_exchangeQuarterly
Interest Expense on Public Debt/v2/accounting/od/interest_expenseMonthly

Exchange-rate interpretation: Treasury Reporting Rates are foreign-currency units per USD, so divide a foreign-currency amount by the rate to obtain USD (and multiply USD to obtain foreign currency). These are government reporting rates, not live trading quotes. Preserve both record_date and effective_date, and check amendments before applying a rate to a reporting period.

Securities & Auctions
DatasetEndpointFrequency
Treasury Securities Auctions Data/v1/accounting/od/auctions_queryAs Needed
Treasury Securities Upcoming Auctions/v1/accounting/od/upcoming_auctionsAs Needed
Treasury Securities Buybacks/v1/accounting/od/buybacks_operationsAs Needed
Savings Bonds
DatasetEndpointFrequency
I Bonds Interest Rates/v1/accounting/od/i_bonds_interest_ratesSemi-Annual
Savings Bonds Issues, Redemptions & Maturities/v1/accounting/od/savings_bonds_reportMonthly

Response Structure

{
  "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: Data-row values are returned as strings; metadata counts are JSON numbers. Convert as needed (e.g., float(), pd.to_datetime()). Null values appear as the string "null".

Common Patterns

Load all pages into a DataFrame

Use the bounded fetch_all() helper in parameters.md. For small result sets, a single request with page[size]=10000 may suffice when meta.total-pages is 1.

# Single-page fetch when total-pages == 1
params = {"sort": "-record_date", "page[size]": 10000}
resp = requests.get(f"{BASE_URL}/v2/accounting/od/debt_outstanding", params=params, timeout=30)
resp.raise_for_status()
result = resp.json()
if result["meta"]["total-pages"] > 1:
    raise ValueError("Use fetch_all() from parameters.md for multi-page results")
df = pd.DataFrame(result["data"])
Aggregation (automatic sum)

Selecting fewer fields can aggregate non-unique rows. It can also sum balances or rates that should not be added, and combine statement totals with their components. Inspect the full row grain first:

# Preview full DTS rows, preserving account and category dimensions
resp = requests.get(f"{BASE_URL}/v1/accounting/dts/deposits_withdrawals_operating_cash", params={
    "filter": "record_date:eq:2024-01-16", "page[size]": 1000
}, timeout=30)
resp.raise_for_status()

Interpretation checks

  • DTS amounts are in millions. Since April 18, 2022, find the Treasury General Account (TGA) Closing Balance row and read open_today_bal; close_today_bal is null.

  • MTS tables have different amount fields and row hierarchies. The compact monthly summary uses mil_amt (millions); do not assign that scale to every MTS field.

  • Interest expense uses month_expense_amt and fytd_expense_amt. Never sum FYTD values across months.

  • Auctions use auction_date for event timing; record_date is publication date. I Bond rates require the bond's issue_year_month as well as earning period.

Reviewed against the official API guide, dataset data dictionaries, and unauthenticated live GET responses on 2026-09-30. See references for table-specific caveats.

Reference Files

Citing Scientific Agent Skills

This skill is part of Scientific Agent Skills by K-Dense. If it materially contributed to a manuscript, report, presentation, or code release, add the paper to the references or software section and tell the user you did so:

Kassis, T., Agarwal, V., He, Y., Patel, D., & Brueckner, A. M. (2026). Scientific Agent Skills: A Library of Procedural Knowledge for Research Agents. arXiv:2609.00065. https://doi.org/10.48550/arXiv.2609.00065

Always cite the current version. The DOI and https://arxiv.org/abs/2609.00065 resolve to the latest arXiv version, so never append a version suffix such as v1. When network access is available, fetch https://arxiv.org/abs/2609.00065 (or http://export.arxiv.org/api/query?id_list=2609.00065) before writing the reference and take the author list, year, and version from that record. If the record lists a journal reference or publisher DOI, cite the published version instead.

Files

references/datasets-securities.md

Securities & Savings Bonds Datasets — U.S. Treasury Fiscal Data

Treasury Securities Auctions Data

Endpoint: /v1/accounting/od/auctions_query
Frequency: As Needed
Date Range: November 1979 to present

Historical data on Treasury securities auctions including bills, notes, bonds, TIPS, and FRNs.

Key fields:

FieldTypeDescription
record_dateDATEPublication date; do not use as auction date
auction_dateDATEDate auction was held
security_typeSTRINGBasic security type; inspect inflation_index_security and floating_rate flags for TIPS/FRNs
security_termSTRINGe.g., "4-Week", "2-Year", "10-Year"
cusipSTRINGCUSIP identifier
offering_amtCURRENCY0Amount offered
high_yieldNUMBERHigh accepted yield (notes/bonds/TIPS; bills use high_discnt_rate)
int_rateNUMBERCoupon/interest rate of the security
bid_to_cover_ratioNUMBERBid-to-cover ratio
total_acceptedNUMBERTotal accepted amount (USD)
indirect_bidder_acceptedNUMBERIndirect bidder amount accepted (USD)
issue_dateDATEIssue/settlement date
maturity_dateDATEMaturity date
# Get recent 10-year Treasury note auctions
resp = requests.get(
    "https://api.fiscaldata.treasury.gov/services/api/fiscal_service/v1/accounting/od/auctions_query",
    params={
        "filter": "security_type:eq:Note,original_security_term:eq:10-Year,inflation_index_security:eq:No,floating_rate:eq:No",
        "sort": "-auction_date",
        "page[size]": 10
    },
    timeout=30,
)
resp.raise_for_status()
df = pd.DataFrame(resp.json()["data"])

# Get all auctions in 2024
resp = requests.get(
    "https://api.fiscaldata.treasury.gov/services/api/fiscal_service/v1/accounting/od/auctions_query",
    params={
        "filter": "auction_date:gte:2024-01-01,auction_date:lte:2024-12-31",
        "sort": "-auction_date",
        "page[size]": 10000
    },
    timeout=30,
)
resp.raise_for_status()
assert resp.json()["meta"]["total-pages"] <= 1, "Use fetch_all for more pages"

Treasury Securities Upcoming Auctions

Endpoint: /v1/accounting/od/upcoming_auctions
Frequency: As Needed
Date Range: March 2024 to present

Schedule data can include historical rows. Filter auction_date:gte:<today> for future auction dates, or issue_date for settlement timing. Do not assume an unfiltered response contains only upcoming events.

Key fields:

FieldTypeDescription
auction_dateDATEScheduled auction date
security_typeSTRINGSecurity type
security_termSTRINGMaturity term
offering_amtCURRENCY0Announced offering amount
# Get upcoming auctions
from datetime import date
resp = requests.get(
    "https://api.fiscaldata.treasury.gov/services/api/fiscal_service/v1/accounting/od/upcoming_auctions",
    params={"filter": f"auction_date:gte:{date.today().isoformat()}", "sort": "auction_date", "page[size]": 1000},
    timeout=30,
)
resp.raise_for_status()
assert resp.json()["meta"]["total-pages"] <= 1, "Use fetch_all for more pages"
upcoming = pd.DataFrame(resp.json()["data"])
if upcoming.empty:
    print("No upcoming rows returned for the requested date range")
else:
    print(upcoming[["auction_date", "security_type", "security_term", "offering_amt"]])

Record-Setting Treasury Securities Auction Data

Frequency: As Needed

Tracks auction records (largest, highest rate, lowest rate, etc.) for each security type and term.

Treasury Securities Buybacks

Frequency: As Needed (2 data tables)
Date Range: March 2000 to present

Data on Treasury's secondary market buyback (repurchase) operations. Active since the program's relaunch in 2024.

TableEndpointDescription
Buybacks Operations/v1/accounting/od/buybacks_operationsAnnouncements and results per operation
Security Details/v1/accounting/od/buybacks_security_detailsSecurity details per operation
# Recent buyback operations
resp = requests.get(
    "https://api.fiscaldata.treasury.gov/services/api/fiscal_service/v1/accounting/od/buybacks_operations",
    params={"sort": "-operation_date", "page[size]": 10},
    timeout=30,
)
resp.raise_for_status()
df = pd.DataFrame(resp.json()["data"])
print(df[["operation_date", "settlement_date"]].head())

I Bonds Interest Rates

Endpoint: /v1/accounting/od/i_bonds_interest_rates
Frequency: Semi-Annual (May and November)
Date Range: September 1998 to present

Composite interest rates for Series I Savings Bonds, including fixed rate and inflation rate components.

Key fields:

FieldTypeDescription
issue_year_monthSTRINGBond issue month (YYYY-MM); fixes the bond vintage
earning_period_startDATEStart of published earning period
earning_period_endDATEEnd of published earning period
fixed_ratePERCENTAGEFixed rate component
semi_annual_inflation_ratePERCENTAGESemi-annual CPI-U inflation rate
combined_ratePERCENTAGECombined composite rate

Do not take the first row sorted only by earning period: many issue-month vintages share that period and have different fixed rates. Filter issue_year_month for the bond, and choose the earning period appropriate to the reporting date. The first period may be shorter than six months. The current rate for newly issued bonds is not the rate for every outstanding I Bond. See examples.md for a query that names its issue vintage.

U.S. Treasury Savings Bonds: Issues, Redemptions & Maturities

Three data tables under /v1/accounting/od/:

TableEndpointDescription
Issues, Redemptions & Maturities/v1/accounting/od/savings_bonds_reportPaper-bond counts by series
Matured Unredeemed Debt/v1/accounting/od/savings_bonds_mudMatured unredeemed debt
Piece Information by Series/v1/accounting/od/savings_bonds_pcsPiece information by series

Frequency: Monthly
Date Range: September 1998 to present

The savings_bonds_report table counts paper bonds by series; its fields are not dollar amounts. Its API coverage starts in January 2019; the other tables have different start dates. These counts should not be interpreted as all electronic and paper savings-bond sales.

Key fields (savings_bonds_report):

FieldTypeDescription
record_dateDATEMonth end date
series_cdSTRINGBond series (EE, I, HH)
bonds_issued_cntNUMBERCount of paper bonds issued
bonds_redeemed_cntNUMBERCount redeemed
bonds_matured_cntNUMBERCount matured
bonds_out_cntNUMBERCount outstanding

Savings Bonds Value Files

Frequency: Semi-Annual
Date Range: May 1992 to present

Files for calculating current redemption values of savings bonds.

Accrual Savings Bonds Redemption Tables (Discontinued)

Endpoint: /v2/accounting/od/redemption_tables
Frequency: Discontinued (last updated 2022)
Date Range: March 1999 – May 2023

Monthly redemption value tables for historical savings bonds.

Savings Bonds Securities Sold (Discontinued)

Endpoint: /v1/accounting/od/slgs_savings_bonds (despite its name, this is historical savings-bond statistics, not SLGS interest rates).

Frequency: Discontinued
Date Range: October 1998 – June 2022


State and Local Government Series (SLGS) Securities

Endpoint: /v1/accounting/od/slgs_securities Frequency: Daily
Date Range: October 1998 to present

SLGS securities outstanding data — non-marketable special purpose securities sold to state and local governments.

Monthly State and Local Government Series (SLGS) Securities Program

Endpoint: /v2/accounting/od/slgs_statistics

Frequency: Monthly
Date Range: March 2014 to present

Monthly statistics on the SLGS program.


Electronic Securities Transactions

Frequency: Monthly (8 data tables)
Date Range: January 2000 to present

Counts of sales, transfers, redemptions, outstanding securities and accounts in TreasuryDirect. These transaction tables do not provide bond values or yields; do not describe them as TRADES settlement data.


Federal Investments Program

Interest Cost by Fund

Frequency: Monthly
Date Range: October 2001 to present

Monthly interest components by Federal Investments Program account/Treasury Account Symbol, including premiums, discounts, interest payments and inflation compensation.

Principal Outstanding

Frequency: Monthly (2 tables)
Date Range: October 2017 to present

Statement of Account

Frequency: Monthly (3 tables)
Date Range: November 2011 to present


Federal Borrowings Program

Distribution and Transaction Data

Frequency: Daily (2 tables)
Date Range: September 2000 to present

Interest on Uninvested Funds

Frequency: Quarterly
Date Range: December 2016 to present

Summary General Ledger Balances Report

Frequency: Monthly (2 tables)
Date Range: October 2005 to present

Official sources

Reviewed 2026-09-30 against the current dataset dictionaries and live API responses.

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Declares allowed tools, Needs network access, Needs an API key, Needs Python

The author says: Requires Python 3.10+ with requests and pandas for Python examples; R with httr and jsonlite for R examples. Requires network access; no credentials.

Security

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Attribution and licence

Created by
K-Dense Inc.
Publisher
K-Dense (Community)
Source
K-Dense-AI/scientific-agent-skills · skills/usfiscaldata · commit a25cf9e
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE.md)
  • ATTRIBUTION.md (written by AutoGineer)
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The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download usfiscaldata.zip