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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
Download the skill as a ZIP:
https://autogineer.com/agent-skills/k-dense-ai/usfiscaldata/downloadUnzip 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 pandasQuick 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
| 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
# 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/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 (18 tables — see datasets-fiscal.md) | 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 |
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
| 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 |
| Treasury Securities Buybacks | /v1/accounting/od/buybacks_operations | As Needed |
Savings Bonds
| Dataset | Endpoint | Frequency |
|---|---|---|
| I Bonds Interest Rates | /v1/accounting/od/i_bonds_interest_rates | Semi-Annual |
| Savings Bonds Issues, Redemptions & Maturities | /v1/accounting/od/savings_bonds_report | Monthly |
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 Balancerow and readopen_today_bal;close_today_balis 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_amtandfytd_expense_amt. Never sum FYTD values across months.Auctions use
auction_datefor event timing;record_dateis publication date. I Bond rates require the bond'sissue_year_monthas 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
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
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
- ATTRIBUTION.mdAdded by AutoGineer922 B
- LICENSELicence file added by AutoGineer1.0 KiB
- SKILL.md9.4 KiB
- references/api-basics.md3.9 KiB
- references/datasets-debt.md6.9 KiB
- references/datasets-fiscal.md9.4 KiB
- references/datasets-interest-rates.md6.9 KiB
- references/datasets-securities.md9.9 KiB
- references/examples.md9.5 KiB
- references/parameters.md6.5 KiB
- references/response-format.md6.0 KiB
references/datasets-interest-rates.md
Interest Rates & Exchange Rate Datasets — U.S. Treasury Fiscal Data
Average Interest Rates on U.S. Treasury Securities
Endpoint: /v2/accounting/od/avg_interest_rates
Frequency: Monthly
Date Range: January 2001 to present
Average interest rates for marketable and non-marketable Treasury securities, broken down by security type.
Key fields:
| Field | Type | Description |
|---|---|---|
record_date | DATE | Month end date |
security_desc | STRING | Security description (e.g., "Treasury Bills") |
security_type_desc | STRING | "Marketable" or "Non-marketable" |
avg_interest_rate_amt | PERCENTAGE | Average interest rate (%) |
# Get average rates for all marketable securities, most recent month
resp = requests.get(
"https://api.fiscaldata.treasury.gov/services/api/fiscal_service/v2/accounting/od/avg_interest_rates",
params={
"filter": "security_type_desc:eq:Marketable",
"sort": "-record_date",
"page[size]": 50
},
timeout=30,
)
resp.raise_for_status()
df = pd.DataFrame(resp.json()["data"])
latest = df[df["record_date"] == df["record_date"].max()]
print(latest[["security_desc", "avg_interest_rate_amt"]])
# First-page preview of historical rates for a specific security type
resp = requests.get(
"https://api.fiscaldata.treasury.gov/services/api/fiscal_service/v2/accounting/od/avg_interest_rates",
params={
"fields": "record_date,avg_interest_rate_amt",
"filter": "security_desc:eq:Treasury Notes,record_date:gte:2010-01-01",
"sort": "-record_date"
},
timeout=30,
)
resp.raise_for_status()Common security descriptions:
Treasury BillsTreasury NotesTreasury BondsTreasury Inflation-Protected Securities (TIPS)Treasury Floating Rate Notes (FRN)Federal Financing BankUnited States Savings SecuritiesGovernment Account SeriesTotal MarketableTotal Non-marketableTotal Interest-bearing Debt
Treasury Reporting Rates of Exchange
Endpoint: /v1/accounting/od/rates_of_exchange
Frequency: Quarterly
Date Range: March 2001 to present
Official Treasury exchange rates for foreign currencies used by federal agencies for reporting purposes. Updated quarterly (March 31, June 30, September 30, December 31).
Key fields:
| Field | Type | Description |
|---|---|---|
record_date | DATE | Quarter end date |
country | STRING | Country name |
currency | STRING | Currency name |
country_currency_desc | STRING | Combined "Country-Currency" (e.g., "Canada-Dollar") |
exchange_rate | NUMBER | Units of foreign currency per 1 USD |
effective_date | DATE | Date rate became effective |
Fetch the latest record_date first, then fetch all pages for that date with
all columns retained. A fixed page of 200 rows can omit currencies/amendments.
Use country_currency_desc:eq:Euro Zone-Euro for euro history, preserving both
record_date and effective_date. See examples.md.
Amendments are separate rows with later effective dates; a rate amended at month end applies to the remaining months of the quarter described in the official notes. Do not silently deduplicate a currency without choosing a reporting period. Multiply USD by the rate for foreign currency; divide foreign currency by the rate for USD. These are reporting rates, not daily market quotes.
TIPS and CPI Data
Two data tables under /v1/accounting/od/:
| Table | Endpoint | Description |
|---|---|---|
| Summary | /v1/accounting/od/tips_cpi_data_summary | Reference CPI numbers and daily index ratios (summary) |
| Detail | /v1/accounting/od/tips_cpi_data_detail | Reference CPI numbers and daily index ratios (detail) |
Frequency: Monthly
Date Range: April 1998 to present
Treasury Inflation-Protected Securities (TIPS) reference CPI data and index ratios used to calculate TIPS values.
The summary table describes securities; daily observations live in detail. Neither table uses record_date.
Key fields:
| Field | Type | Description |
|---|---|---|
cusip | STRING | Security identifier in both tables |
index_date | DATE | Daily observation date in the detail table |
index_ratio | NUMBER | Detail table index ratio |
ref_cpi | NUMBER | Detail table reference CPI |
ref_cpi_on_dated_date | NUMBER | Base CPI in the summary table |
FRN Daily Indexes
Endpoint: /v1/accounting/od/frn_daily_indexes
Frequency: Monthly release (daily index rows per CUSIP)
Date Range: October 2024 onward (current API coverage)
Daily index values for Treasury Floating Rate Notes (FRNs). The rate is based on the 13-week Treasury bill auction rate. Data is published monthly with daily index rows for each CUSIP.
Treasury Certified Interest Rates
Four certification periods, each with their own endpoint set:
Annual Certification
Frequency: Annual
Date Range: October 2006 to present (9 data tables)
Monthly Certification
Frequency: Monthly
Date Range: October 2006 to present (6 data tables)
Quarterly Certification
Frequency: Quarterly
Date Range: October 2006 to present (4 data tables)
Semi-Annual Certification
Frequency: Semi-Annual
Date Range: January 2008 to present (1 data table)
These certified interest rates are used for federal loans, financing programs, and other purposes requiring official Treasury-certified rates.
Federal Credit Similar Maturity Rates
Endpoint: /v1/accounting/od/federal_maturity_rates
Frequency: Annual
Date Range: September 1992 to present
Interest rates used for valuing federal credit programs (loans and loan guarantees) under the Federal Credit Reform Act.
Historical Qualified Tax Credit Bond Interest Rates
Frequency: Daily (Discontinued)
Date Range: March 2009 – January 2018
Historical interest rates for Qualified Tax Credit Bonds (QTCB). No longer updated.
State and Local Government Series (SLGS) Daily Rate Table
Endpoints: /v1/accounting/od/slgs_demand_deposit_rates and
/v1/accounting/od/slgs_time_deposit_rates
Frequency: Daily
Date Range: June 1992 to present
Daily interest rates for State and Local Government Series securities, used by state and local issuers to comply with federal tax law arbitrage restrictions.
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)
- Synced
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