Day1Global-Skills is a collection of investment-analysis skills for AI agents covering technology earnings, value investing, stock-market sentiment, macroeconomic liquidity, and Bitcoin-cycle analysis. Investors use the skills to examine companies, markets, economic conditions, and crypto indicators through structured analysis workflows. The catalogue skills are the project’s own agent workflows.
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 star23/Day1Global-Skills --skill macro-liquiditygit clone --depth 1 https://github.com/star23/Day1Global-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/star23/day1global-skills/macro-liquidity)<a href="https://agentmods.dev/skills/star23/day1global-skills/macro-liquidity"><img src="https://agentmods.dev/badge/skills/star23/day1global-skills/macro-liquidity/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/star23/day1global-skills/macro-liquidity"><img src="https://agentmods.dev/badge/skills/star23/day1global-skills/macro-liquidity.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk fail
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high System Prompt Leakage · line 211 Skill contains instructions that could directly expose system prompts, internal rules, or hidden instructions to users or external parties.Fix: Remove any instructions that reveal, print, or output system prompts or internal rules. System instructions should never be exposed to end users.
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 | $0.00175 | $0.03330 |
| Opus 5 | $0.00088 | $0.01665 |
| Sonnet 5 | $0.00035 | $0.00666 |
| Haiku 4.5 | $0.00017 | $0.00333 |
Grade A, and why
macro-liquidity scanned grade A with 0 findings 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 12d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 229 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Macro Liquidity Monitoring System
This skill helps you track the most critical "water level" in the global financial system — liquidity. Liquidity can be simply understood as how much money is flowing in the market. When there is plenty of money (ample liquidity), asset prices tend to rise; when money is scarce (tight liquidity), asset prices come under pressure. These 4 indicators cover the complete chain from the Fed's "main faucet" to the market's "end of the pipeline."
Use Cases
Use this skill when users ask the following types of questions:
- How is liquidity right now / Is the Fed injecting or draining liquidity
- What is the SOFR rate trend
- Is Treasury market volatility high
- Will the yen carry trade blow up
- Is the macro environment friendly for risk assets (stocks, crypto)
Analytical Framework
4 Core Monitoring Indicators
For each indicator, use web_search to find the latest data, then evaluate according to the criteria below.
Indicator 1: Fed Net Liquidity
What it is: This is the core formula for measuring how much money the Fed has actually injected into the market:
Net Liquidity = Fed Total Assets - TGA Balance - ON RRP Balance
Breaking down each component:
-
Fed Total Assets (Fed Balance Sheet): The total amount of Treasuries and MBS (Mortgage-Backed Securities) held by the Fed. When the Fed "prints money" to buy bonds → total assets increase → cash is injected into the market. Conversely, "quantitative tightening" (QT) means not reinvesting maturing bonds → total assets decrease → cash is drained from the market. Think of it as "the size of the total water pool."
-
TGA (Treasury General Account): The U.S. Treasury's "bank account" at the Fed. Money received from Treasury bond issuance is deposited here. TGA balance rising = money flowing from the market into the government's account (draining); TGA balance falling = the government is spending, money flowing back to the market (injecting). Think of it as "the government's reservoir — saving is draining, spending is injecting."
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.
- 12d ago First seen · 229 lines · 175 tokens per session scan A 6bc7224cd926
macro-liquidity is a skill published in the GitHub repository star23/Day1Global-Skills (1,048 stars, last pushed 25d ago), licensed MIT. It adds 175 tokens to every session and 3,330 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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