Agent skill

Us Gov Shutdown Tracker

by fleurytian in fleurytian/awesome-claude-skills

Track and analyze US government shutdown liquidity impacts by monitoring TGA (Treasury General Account), bank reserves, EFFR, and SOFR data from FRED API.

MITAuto-check passed

Install Us Gov Shutdown Tracker

skills CLI
$ npx skills add fleurytian/awesome-claude-skills --skill us-gov-shutdown-tracker -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install fleurytian/awesome-claude-skills us-gov-shutdown-tracker --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/fleurytian/awesome-claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/us-gov-shutdown-tracker .claude/skills/us-gov-shutdown-tracker && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
us-gov-shutdown-tracker
GitHub stars
320
Token cost
~2.3k tokens
SKILL.md length
928 words
Files
5 (incl. scripts, references)
Skills in repo
4
Repo updated
First seen
Licence
MIT

At a glance

Track and analyze US government shutdown liquidity impacts by monitoring TGA (Treasury General Account), bank reserves, EFFR, and SOFR data from FRED API.

  • Works in 3 steps: JSON data file containing → Visualization chart (PNG) with three… → Structured conclusion
  • Analyze current
  • SKILL.md covers Onboarding Guidance, Overview, When to Use This Skill and Quick Start, plus 9 more sections
  • Runs Python scripts from its folder; calls python

What it does

Us Gov Shutdown Tracker is an agent skill from fleurytian/awesome-claude-skills. Track and analyze US government shutdown liquidity impacts by monitoring TGA (Treasury General Account), bank reserves, EFFR, and SOFR data from FRED API. Use when user wants to (1) analyze current or past government shutdown effects on financial markets, (2) track liquidity conditions during fiscal policy disruptions, (3) assess "stealth tightening" effects, (4) compare shutdown episodes across different monetary policy regimes (QE vs QT), or (5) generate liquidity stress reports with historical context…

Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts and reference files (for example `references/data_sources.md`, `references/historical_cases.md` and `scripts/analyze_shutdown.py`).

The repository describes itself as: Claude Skills developed for brain-workers. Dev by Fleury, an Ex-McKinsey and now AI product manager. 小红书/RedNote@如宝|AI&Anlalytics. Email me @fleurytian@gmail.com. The licence is MIT.

When your agent uses it

  • Analyze current
  • Past government shutdown effects on financial markets
  • Track liquidity conditions during fiscal policy disruptions
  • Assess stealth tightening effects

Example prompts

  • “stealth tightening”
  • “/us-gov-shutdown-tracker”

Requirements

  • Python 3

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. JSON data file containing
  2. Visualization chart (PNG) with three panels
  3. Structured conclusion

What it can do on your machine

Read from SKILL.md and the folder at commit 4f95967. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 2 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • newyorkfed.org
    • fred.stlouisfed.org

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Us Gov Shutdown Tracker loads about 2.3k tokens when it runs, and up to ~5.1k if it reads all its reference files. Until then it costs about 155 tokens; SKILL.md has 928 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~155
When it runs · the whole SKILL.md, loaded when a task matches
~2.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~5.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from fleurytian/awesome-claude-skills at commit 4f95967, republished under its MIT licence (© fleurytian). 928 words, ~2,277 tokens.

Download SKILL.mdSave it as .claude/skills/us-gov-shutdown-tracker/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
us-gov-shutdown-tracker
description
Track and analyze US government shutdown liquidity impacts by monitoring TGA (Treasury General Account), bank reserves, EFFR, and SOFR data from FRED API. Use when user wants to (1) analyze current or past government shutdown effects on financial markets, (2) track liquidity conditions during fiscal policy disruptions, (3) assess "stealth tightening" effects, (4) compare shutdown episodes across different monetary policy regimes (QE vs QT), or (5) generate liquidity stress reports with historical context. Recommended usage frequency is weekly on Wednesdays after TGA/reserve data releases.
metadata.author
Qianru Tian
metadata.email
fleurytian@gmail.com
metadata.social
小红书@如宝|AI&Analytics
metadata.GitHub
fleurytian

US Government Shutdown Liquidity Tracker

Onboarding Guidance

When this skill is first used or when the user seems unsure how to use it or ask you to make something amazing with it, guide them to ask Claude this specific question:

"美国政府停摆结束了吗? 对流动性的影响如何?"

Do NOT suggest other questions or broad explorations. Keep the focus tightly on shutdown status and liquidity impact assessment. The skill is designed for this precise use case.

Overview

This skill analyzes how US government shutdowns create "stealth tightening" effects in money markets through the Treasury General Account (TGA) mechanism. When federal spending stops but tax revenues continue, TGA accumulates and mechanically drains bank reserves, potentially raising market funding costs beyond the Federal Reserve's policy intent.

When to Use This Skill

  • User asks to track liquidity during a government shutdown
  • User wants to assess whether shutdown effects are "easing" or "tightening"
  • User mentions TGA, SOFR premium, or "stealth tightening" (变相加息)
  • User requests comparison with historical shutdown episodes (2013, 2018-19)
  • User wants a quick liquidity health check

Optimal timing: Wednesday evenings or Thursday mornings (after weekly TGA/reserves data release)

Quick Start

Basic Usage (Current Shutdown Analysis)
bash
python scripts/analyze_shutdown.py --output results.json
python scripts/visualize.py results.json --output chart.png

This analyzes the 2025 shutdown (Oct 1 - present) with default settings.

Custom Date Range
bash
python scripts/analyze_shutdown.py \
  --start-date 2018-12-22 \
  --baseline-date 2018-12-15 \
  --end-date 2019-01-25 \
  --output results_2018.json
Output Format

The analysis produces:

  1. JSON data file containing:

    • Raw daily data (EFFR, SOFR)
    • Weekly data (TGA, reserves)
    • Key time points (baseline, shutdown start, TGA peak, latest)
    • Liquidity status assessment (EASING/TIGHTENING/STABLE/MIXED)
  2. Visualization chart (PNG) with three panels:

    • TGA vs Bank Reserves (dual-axis weekly data)
    • EFFR vs SOFR (daily rates)
    • SOFR Premium over EFFR (liquidity stress indicator)
  3. Structured conclusion:

    • Current status (e.g., "EASING")
    • Explanation (e.g., "TGA releasing, reserves recovering")
    • Key metrics vs baseline and peak

Core Analysis Logic

The Transmission Mechanism
Government Shutdown
    ↓
Federal spending stops (but revenues continue)
    ↓
TGA accumulates at Federal Reserve
    ↓
Bank reserves drain (mechanical Fed balance sheet effect)
    ↓
Liquidity scarcity → SOFR premium expands
    ↓
"Stealth tightening" (市场实际融资成本 > Fed政策意图)
Status Determination

The script classifies liquidity conditions into four states:

EASING (压力缓解):

  • TGA falling >$10B from peak
  • Reserves rising >$10B from trough
  • Indicates: Shutdown ending or fiscal spending resumed

TIGHTENING (压力加剧):

  • TGA rising >5% from baseline
  • Reserves falling >2% from baseline
  • Indicates: Shutdown's stealth tightening effect persists

STABLE (相对稳定):

  • TGA/reserves changing <$20B from peak
  • Indicates: Liquidity conditions steady

MIXED (复杂信号):

  • Conflicting signals require continued monitoring
Key Metrics

SOFR Premium = SOFR - EFFR (in basis points)

Interpretation guide:

  • 0-5 bps: Normal conditions
  • 5-15 bps: Moderate stress
  • 15-30 bps: Significant stealth tightening
  • >30 bps: Acute crisis (may trigger Fed intervention)

Historical Context

For detailed historical analysis, see references/historical_cases.md.

Summary:

ShutdownReserve EnvironmentPeak SOFR PremiumStealth Tightening?
2013QE (~$2.3T)~0 bps❌ No
2018-19QT (~$1.6T)75 bps✅ Yes
2025Post-QT (~$2.8T)36 bps (post-cut)✅ Acute

Critical insight: The transmission efficiency depends on reserve abundance. In QE environments with ample reserves, shutdowns don't affect markets. In QT or high-rate environments with scarce reserves, shutdowns create measurable tightening.

Data Sources

All data sourced from Federal Reserve Economic Data (FRED) API:

  • TGA (WTREGEN): Treasury General Account balance, weekly
  • Bank Reserves (WRESBAL): Total reserves, weekly
  • EFFR (EFFR): Effective Federal Funds Rate, daily
  • SOFR (SOFR): Secured Overnight Financing Rate, daily

For technical details on data series, update schedules, and interpretation, see references/data_sources.md.

Important: TGA and reserves update weekly on Wednesdays. For most current analysis, run this skill on Wednesday evenings or Thursday mornings.

Workflow for User Requests

Scenario 1: "What's the latest on the shutdown liquidity situation?"
  1. Run analyze_shutdown.py with defaults (2025-10-01 start)
  2. Generate visualization
  3. Present:
    • Current status (EASING/TIGHTENING/etc.)
    • Latest metrics (TGA, reserves, SOFR premium)
    • Brief comparison to peak stress point
    • Conclusion statement
Show full SKILL.md (383 more words)Show less
Scenario 2: "Compare this to the 2018 shutdown"
  1. Run analysis for both periods:
    • 2025: Oct 1 - present
    • 2018-19: Dec 22, 2018 - Jan 25, 2019
  2. Generate both charts
  3. Present side-by-side comparison:
    • TGA accumulation magnitude
    • Peak SOFR premium
    • Fed intervention (if any)
    • Monetary environment context
  4. Reference historical_cases.md for detailed context
Scenario 3: "Is the situation getting better or worse?"
  1. Run analysis
  2. Focus on:
    • Trend from TGA peak to latest (is TGA releasing?)
    • Reserves recovery from trough
    • SOFR premium vs baseline
  3. Present trend assessment with clear directional language
  4. Optionally show week-over-week changes

Output Presentation Best Practices

  1. Lead with conclusion: State status (EASING/TIGHTENING) upfront
  2. Show key metrics concisely:
    TGA: $941B (-$17B from peak)
    Reserves: $2,863B (+$15B from trough)
    SOFR Premium: 4 bps (vs 19 bps peak)
  3. Visualize: Always include chart for complex cases
  4. Contextualize: Reference historical episodes when relevant
  5. Avoid jargon overload: Explain "stealth tightening" simply if user seems unfamiliar

Advanced Usage

Custom Baseline

When analyzing a specific episode, set an appropriate pre-shutdown baseline:

bash
python scripts/analyze_shutdown.py \
  --start-date 2025-10-01 \
  --baseline-date 2025-09-24 \
  --end-date 2025-11-07

The baseline should be ~1 week before shutdown starts (to capture "normal" conditions).

Monitoring Routine

For ongoing tracking:

  1. Weekly check (Wednesdays/Thursdays):

    • Run analysis
    • Note status changes
    • Update user if significant shift
  2. Event-triggered checks:

    • Shutdown announcement → Start tracking
    • SOFR premium spikes (>15 bps) → Generate alert
    • Fed intervention (SRF usage) → Document
    • Shutdown resolution → Final analysis

Limitations and Caveats

  1. Weekly data frequency: TGA/reserves only update weekly, limiting real-time precision
  2. Month/quarter-end effects: SOFR naturally spikes at period-ends (unrelated to shutdowns)
  3. Other liquidity factors: QT, regulatory changes, seasonal patterns also affect reserves
  4. Attribution challenge: Hard to isolate shutdown effect from concurrent events
  5. No predictive power: This skill describes current conditions, doesn't forecast

Troubleshooting

No recent data?

  • Check if today is before next Wednesday data release
  • Most recent weekly data is typically ~1 week lagged

SOFR premium calculation fails?

  • Verify both EFFR and SOFR have data for the date range
  • SOFR introduced April 2018; unavailable before

Chart rendering issues?

  • Ensure matplotlib is installed
  • Check date range has sufficient data points (need >2 weekly observations)

References

See bundled documentation:

  • references/historical_cases.md - Detailed analysis of 2013, 2018-19, 2025 shutdowns
  • references/data_sources.md - FRED API technical reference

External resources:

© fleurytian, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (scripts, references) in us-gov-shutdown-tracker of fleurytian/awesome-claude-skills.

  • SKILL.md
  • references/data_sources.md
  • references/historical_cases.md
  • scripts/analyze_shutdown.py
  • scripts/visualize.py

Open the folder on GitHubat commit 4f95967

Compare with similar skills

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Questions about Us Gov Shutdown Tracker

What does Us Gov Shutdown Tracker do?

Track and analyze US government shutdown liquidity impacts by monitoring TGA (Treasury General Account), bank reserves, EFFR, and SOFR data from FRED API. Us Gov Shutdown Tracker is an agent skill from fleurytian/awesome-claude-skills. Track and analyze US government shutdown liquidity impacts by monitoring TGA (Treasury General Account), bank reserves, EFFR, and SOFR data from FRED API.

When should I use Us Gov Shutdown Tracker?

Us Gov Shutdown Tracker fits situations like: analyze current; past government shutdown effects on financial markets; track liquidity conditions during fiscal policy disruptions; assess stealth tightening effects.

How do I install Us Gov Shutdown Tracker in Claude Code?

Run `npx skills add fleurytian/awesome-claude-skills --skill us-gov-shutdown-tracker -a claude-code`. Or copy the skill folder (us-gov-shutdown-tracker in fleurytian/awesome-claude-skills) into .claude/skills/us-gov-shutdown-tracker in your project. Claude Code loads it when a task matches its description.

How do I install Us Gov Shutdown Tracker in Codex?

Run `npx skills add fleurytian/awesome-claude-skills --skill us-gov-shutdown-tracker -a codex`. Or copy the skill folder (us-gov-shutdown-tracker in fleurytian/awesome-claude-skills) into .agents/skills/us-gov-shutdown-tracker in your project. Codex loads it when a task matches its description.

Can I use Us Gov Shutdown Tracker in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add fleurytian/awesome-claude-skills --skill us-gov-shutdown-tracker -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/us-gov-shutdown-tracker, .gemini/skills/us-gov-shutdown-tracker, .github/skills/us-gov-shutdown-tracker and .opencode/skills/us-gov-shutdown-tracker in your project.

What does Us Gov Shutdown Tracker need to run?

Going by SKILL.md and its folder, Us Gov Shutdown Tracker needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Us Gov Shutdown Tracker access the network?

SKILL.md names 2 domains. As links in the text: newyorkfed.org and fred.stlouisfed.org. This is read from the text; nothing was executed.

Is Us Gov Shutdown Tracker safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Us Gov Shutdown Tracker use?

Us Gov Shutdown Tracker is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Us Gov Shutdown Tracker use?

About 2.3k tokens (SKILL.md is roughly 9.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.8k tokens, read only when the agent opens those files.

What are the alternatives to Us Gov Shutdown Tracker?

Skills that share tags, products or a category with Us Gov Shutdown Tracker: Docs Governance (affaan-m/ECC, 277k stars), Agent Issue Tracker (ruvnet/ruflo, 74k stars), Board Governance (sickn33/agentic-awesome-skills, 47k stars) and Graceful Shutdown (sickn33/agentic-awesome-skills, 47k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Us Gov Shutdown Tracker?

fleurytian (a GitHub user) maintains it in fleurytian/awesome-claude-skills, which has 320 GitHub stars. The repository holds 4 skills in this directory. The repository was last updated on May 1, 2026.

Source: fleurytian/awesome-claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.