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.
npx skills add crazymsn/academic-skills --skill usfiscaldatagit clone --depth 1 https://github.com/crazymsn/academic-skillsWrote 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.
[](https://agentmods.dev/skills/crazymsn/academic-skills/usfiscaldata)<a href="https://agentmods.dev/skills/crazymsn/academic-skills/usfiscaldata"><img src="https://agentmods.dev/badge/skills/crazymsn/academic-skills/usfiscaldata/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.
<a href="https://agentmods.dev/skills/crazymsn/academic-skills/usfiscaldata"><img src="https://agentmods.dev/badge/skills/crazymsn/academic-skills/usfiscaldata.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00106 | $0.01630 |
| Opus 5 | $0.00053 | $0.00815 |
| Sonnet 5 | $0.00021 | $0.00326 |
| Haiku 4.5 | $0.00011 | $0.00163 |
Grade A, and why
usfiscaldata scanned grade A with 1 finding 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 8d ago.
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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
resp = requests.get(f"{BASE_URL}/v2/accounting/od/debt_to_penny", params={ This is a copy
83% identical to usfiscaldata — 6 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.
How it starts
The opening of the file, as written. The whole thing — 158 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
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}")
# 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
# 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 |
What ships with it
8 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.
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.
- 8d ago First seen · 158 lines · 106 tokens per session scan A aa49dda75303
usfiscaldata is a skill published in the GitHub repository crazymsn/academic-skills (22 stars, last pushed 3mo ago), licensed MIT. It adds 106 tokens to every session and 1,630 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 83% identical to usfiscaldata, differing in 6 lines, and is treated as a copy.
Other skills, from other repositories
sector-rotation
An analysis framework for comparing industries in the Chinese A-share stock market, using business conditions, price momentum, valuation, and money flows. It produces rankings and higher- or lower-allocation suggestions.
strategy-pivot-designer
Detect backtest iteration stagnation and generate structurally different strategy pivot proposals when parameter tuning reaches a local optimum.
twitter-reader
Read Twitter/X for financial research using opencli (read-only). Use this skill whenever the user wants to read their Twitter feed, search for financial tweets, view bookmarks, look up user profiles, or gather market sentiment from Twitter/X. Triggers include: "check my feed", "search Twitter for", "show my…
chenhao-limit-up
A framework for judging Chinese A-share stocks that have reached the daily price-rise limit, using market mood, sector leadership, and trading momentum.
furusato
A Japanese hometown-tax donation manager for furusato nozei, a system where donations to municipalities can qualify for an income-tax or local-tax deduction. It reads donation receipts, stores donation records, and calculates deduction limits.
reading-receipt
An image-reading workflow for extracting structured information from receipts, invoices, and hometown-tax donation certificates. It can first extract text from PDFs and otherwise read their images.