AI-Trader Market Intel
HKUDS/AI-Trader
Reads AI-Trader's read-only market snapshots, grouped financial news and events board through its market-intel endpoints, for context before trading or posting.
Tracks institutional money through US ETF creations and redemptions, sector breadth and style flows to read risk appetite and sector rotation.
Install US ETF Flow and Sector Breadth
$ npx skills add HKUDS/Vibe-Trading --skill us-etf-flow -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install HKUDS/Vibe-Trading us-etf-flow --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/HKUDS/Vibe-Trading.git skills-src && mkdir -p .claude/skills && cp -r skills-src/agent/src/skills/us-etf-flow .claude/skills/us-etf-flow && rm -rf skills-srcUse ~/.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/
Install the "us-etf-flow" agent skill from https://github.com/HKUDS/Vibe-Trading/tree/main/agent/src/skills/us-etf-flow into .claude/skills/us-etf-flow/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "us-etf-flow", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/HKUDS/Vibe-Trading/tree/main/agent/src/skills/us-etf-flowType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add HKUDS/Vibe-Trading --skill us-etf-flow -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install HKUDS/Vibe-Trading us-etf-flow --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/HKUDS/Vibe-Trading.git skills-src && mkdir -p .agents/skills && cp -r skills-src/agent/src/skills/us-etf-flow .agents/skills/us-etf-flow && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "us-etf-flow" agent skill from https://github.com/HKUDS/Vibe-Trading/tree/main/agent/src/skills/us-etf-flow into .agents/skills/us-etf-flow/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "us-etf-flow", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add HKUDS/Vibe-Trading --skill us-etf-flow -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install HKUDS/Vibe-Trading us-etf-flow --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/HKUDS/Vibe-Trading.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/agent/src/skills/us-etf-flow .cursor/skills/us-etf-flow && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "us-etf-flow" agent skill from https://github.com/HKUDS/Vibe-Trading/tree/main/agent/src/skills/us-etf-flow into .cursor/skills/us-etf-flow/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "us-etf-flow", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/HKUDS/Vibe-Trading.git --path agent/src/skills/us-etf-flow--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add HKUDS/Vibe-Trading --skill us-etf-flow -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install HKUDS/Vibe-Trading us-etf-flow --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/HKUDS/Vibe-Trading.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/agent/src/skills/us-etf-flow .gemini/skills/us-etf-flow && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "us-etf-flow" agent skill from https://github.com/HKUDS/Vibe-Trading/tree/main/agent/src/skills/us-etf-flow into .gemini/skills/us-etf-flow/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "us-etf-flow", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install HKUDS/Vibe-Trading us-etf-flowInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add HKUDS/Vibe-Trading --skill us-etf-flow -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/HKUDS/Vibe-Trading.git skills-src && mkdir -p .github/skills && cp -r skills-src/agent/src/skills/us-etf-flow .github/skills/us-etf-flow && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "us-etf-flow" agent skill from https://github.com/HKUDS/Vibe-Trading/tree/main/agent/src/skills/us-etf-flow into .github/skills/us-etf-flow/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "us-etf-flow", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add HKUDS/Vibe-Trading --skill us-etf-flow -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install HKUDS/Vibe-Trading us-etf-flow --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/HKUDS/Vibe-Trading.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/agent/src/skills/us-etf-flow .opencode/skills/us-etf-flow && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "us-etf-flow" agent skill from https://github.com/HKUDS/Vibe-Trading/tree/main/agent/src/skills/us-etf-flow into .opencode/skills/us-etf-flow/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "us-etf-flow", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
us-etf-flow- GitHub stars
- 35k
- Token cost
- ~2.6k tokens
- SKILL.md length
- 688 words
- Files
- 1
- Skills in repo
- 89
- Repo updated
- First seen
- Licence
- MIT
At a glance
Tracks institutional money through US ETF creations and redemptions, sector breadth and style flows to read risk appetite and sector rotation.
- Works in 5 steps: ETF Flow Mechanics → Major ETF Flow Categories → Sector Rotation Signals → …
- Reading institutional risk appetite from ETF inflows and outflows
- SKILL.md covers Overview, Core Concepts, Data Access and Output Format, plus 1 more section
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
This skill explains how US ETF flows reveal institutional positioning. It describes the creation and redemption process, in which authorized participants swap baskets of securities for new ETF shares when an ETF trades at a premium to net asset value and do the reverse at a discount, and it stresses that flows measure how much money moves rather than where price goes. Daily flow data is presented as faster than 13F filings, which lag by 45 days.
Reference tables cover broad market ETFs such as SPY, IVV, VOO, QQQ, IWM and DIA with the appetite each one reflects, plus a rule that reads simultaneous large-cap and small-cap inflows as risk-on. The SPDR Select Sector ETFs, from XLK to XLB, are mapped to economic sensitivity and cycle phase. The excerpt stops after the sector table, before the breadth, style-factor and thematic momentum material that the description mentions.
When your agent uses it
- Reading institutional risk appetite from ETF inflows and outflows
- Judging sector rotation from sector ETF flows and breadth
- Matching sector ETFs to a stage of the economic cycle
- Separating real capital flows from price momentum in an ETF
Example prompts
- “Are SPY and IWM both seeing inflows this month, and does that make the market risk-on?”
- “Which SPDR sector ETFs fit an early recovery, and how do their flows look?”
- “Explain why an ETF trading at a premium to NAV leads to creations.”
Workflow steps
5 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit e532650. 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
No scripts in the folder and no shell commands in SKILL.md (its code samples are python).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
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 ETF Flow and Sector Breadth loads about 2.6k tokens when it runs. Until then it costs about 50 tokens; SKILL.md has 688 words of instructions outside code blocks.
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); files beside SKILL.md are not scanned.
SKILL.md
The full file from HKUDS/Vibe-Trading at commit e532650, republished under its MIT licence (© HKUDS). 688 words, ~2,560 tokens.
Download SKILL.mdSave it as
.claude/skills/us-etf-flow/SKILL.md (or your agent's skills folder).- name
- us-etf-flow
- description
- US ETF fund flow analysis, sector rotation breadth, and style factor flows — track institutional capital movement via ETF creation/redemption, sector breadth signals, and thematic momentum.
- category
- flow
US ETF Flow & Sector Breadth Analysis
Overview
Track capital flows through US ETFs to identify institutional positioning, sector rotation trends, and risk appetite shifts. ETF flows are a real-time proxy for institutional capital allocation — unlike 13F filings (45-day lag), ETF creation/redemption data is available daily.
Core Concepts
1. ETF Flow Mechanics
Creation / Redemption process:
- Inflows (creation): Authorized Participants (APs) deliver baskets of underlying securities to the ETF issuer → receive new ETF shares → sell on exchange. This happens when ETF trades at a premium to NAV.
- Outflows (redemption): APs buy ETF shares on exchange → redeem with issuer for underlying securities → sell securities. This happens when ETF trades at a discount to NAV.
- Signal interpretation: sustained large inflows = institutional demand; sustained large outflows = institutional liquidation.
Key distinction:
- ETF price movement ≠ ETF flow. Price can rise on low volume (momentum). Flows require actual capital commitment.
- Flows are a quantity signal (how much money is moving), not a price signal.
2. Major ETF Flow Categories
Broad Market ETFs
| ETF | Tracking Index | AUM | Flow Signal |
|---|---|---|---|
| SPY | S&P 500 | ~$500B | Broadest equity risk appetite |
| IVV | S&P 500 | ~$400B | Long-term institutional allocation |
| VOO | S&P 500 | ~$400B | Retail + advisor allocation |
| QQQ | Nasdaq 100 | ~$250B | Tech / growth appetite |
| IWM | Russell 2000 | ~$60B | Small-cap risk appetite |
| DIA | Dow Jones 30 | ~$30B | Value / blue-chip sentiment |
Interpretation rules:
# Broad market flow signals
if spy_flow > 0 and iwm_flow > 0:
signal = "risk_on" # Both large and small cap getting inflows
elif spy_flow > 0 and iwm_flow < 0:
signal = "quality_flight" # Money rotating to large-cap safety
elif spy_flow < 0 and iwm_flow < 0:
signal = "risk_off" # Broad equity outflows
elif spy_flow < 0 and iwm_flow > 0:
signal = "risk_seeking" # Rotation from large to small (rare, usually early cycle)Sector ETFs (SPDR Select Sector)
| ETF | Sector | Economic Sensitivity | Cycle Phase |
|---|---|---|---|
| XLK | Technology | Growth / late cycle | Expansion |
| XLF | Financials | Rate sensitive | Early recovery |
| XLE | Energy | Commodity linked | Late cycle / inflation |
| XLV | Healthcare | Defensive | Recession |
| XLY | Consumer Discretionary | Cyclical | Recovery |
| XLP | Consumer Staples | Defensive | Recession |
| XLI | Industrials | Cyclical | Early expansion |
| XLU | Utilities | Defensive / rate sensitive | Late cycle / recession |
| XLB | Materials | Commodity linked | Early cycle |
| XLRE | Real Estate | Rate sensitive | Rate-cut cycle |
| XLC | Communication Services | Growth (META, GOOGL) | Expansion |
Style & Factor ETFs
| ETF | Factor | Signal |
|---|---|---|
| IVW / SPYG | S&P 500 Growth | Growth appetite |
| IVE / SPYV | S&P 500 Value | Value rotation |
| MTUM | MSCI USA Momentum | Trend following |
| QUAL | MSCI USA Quality | Quality flight |
| USMV / SPLV | Min Volatility | Defensive positioning |
| SIZE | MSCI USA Size | Small-cap factor |
Fixed Income ETFs
| ETF | Segment | Signal |
|---|---|---|
| TLT | 20+ Year Treasury | Duration / rate expectations |
| IEF | 7-10 Year Treasury | Intermediate rate view |
| SHY | 1-3 Year Treasury | Cash proxy / safe haven |
| LQD | Investment Grade Corp | Credit appetite |
| HYG / JNK | High Yield Corp | Risk appetite / credit cycle |
| TIP | TIPS | Inflation expectations |
| EMB | EM Sovereign Debt | EM risk appetite |
3. Sector Rotation Signals
Sector breadth analysis:
# Sector breadth = number of sectors with positive flows / total sectors
sector_flows = {
"XLK": +500, # $500M inflow
"XLF": +200,
"XLE": -100,
"XLV": +50,
"XLY": -300,
"XLP": +100,
"XLI": +150,
"XLU": -50,
"XLB": +80,
"XLRE": -200,
"XLC": +300,
}
positive_sectors = sum(1 for v in sector_flows.values() if v > 0)
breadth = positive_sectors / len(sector_flows)
# Interpretation
# breadth > 0.7: broad-based inflows → healthy bull market
# breadth 0.4-0.7: selective rotation → stock/sector picker's market
# breadth < 0.4: broad outflows → risk-off environmentCyclical vs Defensive ratio:
cyclical = ["XLK", "XLY", "XLI", "XLF", "XLB"]
defensive = ["XLV", "XLP", "XLU", "XLRE"]
cyclical_flow = sum(sector_flows[s] for s in cyclical)
defensive_flow = sum(sector_flows[s] for s in defensive)
ratio = cyclical_flow / (cyclical_flow + defensive_flow + 1e-10)
# ratio > 0.65: strong risk-on, cyclical leadership
# ratio 0.4-0.65: balanced
# ratio < 0.4: defensive rotation, risk-offShow full SKILL.md (286 more words)Show less
4. Thematic ETF Flows
Growth / innovation themes:
| Theme | Key ETFs | What It Tracks |
|---|---|---|
| AI / Semiconductors | SMH, SOXX, BOTZ | AI capex cycle |
| Clean Energy | ICLN, TAN, QCLN | Energy transition spend |
| Biotech | XBI, IBB | Pharma pipeline / M&A cycle |
| Cybersecurity | CIBR, HACK | Security spending cycle |
| China Internet | KWEB, FXI | China tech sentiment |
| India | INDA, SMIN | India growth allocation |
| Emerging Markets | EEM, VWO | EM risk appetite |
| Gold Miners | GDX, GDXJ | Gold price leverage play |
| Bitcoin | IBIT, FBTC | Crypto institutional adoption |
Thematic flow interpretation:
- Sustained 4-week+ inflows into a theme = institutional conviction, not just hot money
- Sudden large outflows from a theme that was trending = crowded trade unwind risk
- Divergence between thematic ETF flow and underlying asset price = potential inflection
5. Flow-Based Trading Signals
Signal construction:
def etf_flow_signal(ticker, lookback_days=20):
"""
Generate trading signal from ETF flow data.
"""
# Cumulative flow over lookback period
cum_flow = sum(daily_flows[ticker][-lookback_days:])
# Flow as % of AUM (normalized)
flow_pct = cum_flow / aum[ticker]
# Flow momentum: recent 5-day vs prior 15-day
recent = sum(daily_flows[ticker][-5:])
prior = sum(daily_flows[ticker][-20:-5])
momentum = recent - prior
# Signal
if flow_pct > 0.02 and momentum > 0:
return "strong_inflow" # Sustained and accelerating
elif flow_pct > 0.01:
return "mild_inflow" # Positive but not accelerating
elif flow_pct < -0.02 and momentum < 0:
return "strong_outflow" # Sustained and accelerating outflows
elif flow_pct < -0.01:
return "mild_outflow"
else:
return "neutral"Contrarian vs momentum flow signals:
- Momentum (follow the flow): works best for broad market ETFs (SPY, QQQ) during trending markets
- Contrarian (fade extreme flows): works best for sector/thematic ETFs at extreme levels
- Rule of thumb: 3-standard-deviation flow events in sector ETFs tend to mean-revert within 2-4 weeks
Data Access
Via yfinance
import yfinance as yf
# ETF price and volume data
etf = yf.download("SPY", start="2025-01-01", end="2026-03-30", progress=False)
# ETF info (AUM, expense ratio, holdings)
spy = yf.Ticker("SPY")
info = spy.info
print(f"AUM: {info.get('totalAssets')}")
print(f"Expense ratio: {info.get('annualReportExpenseRatio')}")
# Sector weights (for sector ETFs)
# Not directly available via yfinance; use web scraping or manual inputFlow Data Sources
| Source | Access | Coverage | Latency |
|---|---|---|---|
| ETF.com | Free (web) | US ETFs | T+1 |
| Bloomberg Terminal | Paid | Global ETFs | Real-time |
| ICI (Investment Company Institute) | Free (weekly) | US mutual fund + ETF aggregate | T+7 |
| ETF Database (etfdb.com) | Free (web) | US ETFs | T+1 |
| VettaFi | Free (web) | US ETFs | T+1 |
Output Format
## ETF Flow Analysis — [Date Range]
### Broad Market Flows
- **SPY**: [+/- $X.XB over N days] — [risk-on / risk-off signal]
- **QQQ**: [+/- $X.XB] — [tech appetite]
- **IWM**: [+/- $X.XB] — [small-cap sentiment]
- **Overall**: [risk-on / selective / risk-off]
### Sector Rotation
- **Inflow leaders**: [sector1 +$XM, sector2 +$XM]
- **Outflow leaders**: [sector1 -$XM, sector2 -$XM]
- **Breadth**: X/11 sectors with positive flows
- **Cyclical/Defensive ratio**: X.XX [risk-on / balanced / defensive]
### Style Factor Flows
- **Growth vs Value**: [growth leading / value leading / balanced]
- **Momentum**: [inflow / outflow]
- **Quality/MinVol**: [inflow = defensive, outflow = risk-on]
### Fixed Income Flows
- **Duration signal**: TLT [inflow/outflow] → [rate cut expectations / rate concern]
- **Credit signal**: HYG [inflow/outflow] → [credit cycle expansion / contraction]
- **Inflation signal**: TIP [inflow/outflow] → [rising / falling inflation expectations]
### Thematic Highlights
- [Theme1 ETF]: [flow trend and implication]
- [Theme2 ETF]: [flow trend and implication]
### Composite Signal
| Dimension | Signal | Basis |
|-----------|--------|-------|
| Risk appetite | [on/off] | SPY+QQQ flows, C/D ratio |
| Sector rotation | [early/mid/late cycle] | Sector flow pattern |
| Rate expectations | [cuts/hold/hikes] | TLT + TIP flows |
### Investment Implication
- **Positioning**: [overweight equities / neutral / underweight]
- **Sector tilts**: [overweight X, underweight Y]
- **Risk level**: [high / moderate / low]Notes
- ETF flows are a proxy for institutional behavior, not a standalone signal; combine with price action and fundamentals
- Large single-day flows can be rebalancing-driven (quarter-end, index reconstitution) rather than directional
- Options-related ETF activity (hedging via SPY puts) can distort flow signals
- International ETF flows (EEM, FXI, INDA) are useful for global macro positioning
- This framework is for research purposes only and does not constitute investment advice
© HKUDS, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in agent/src/skills/us-etf-flow of HKUDS/Vibe-Trading.
Open the folder on GitHubat commit e532650
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Questions about US ETF Flow and Sector Breadth
What does US ETF Flow and Sector Breadth do?
Tracks institutional money through US ETF creations and redemptions, sector breadth and style flows to read risk appetite and sector rotation. This skill explains how US ETF flows reveal institutional positioning. It describes the creation and redemption process, in which authorized participants swap baskets of securities for new ETF shares when an ETF trades at a premium to net asset value and do the reverse at a discount, and it stresses that flows measure how much money moves rather than where price goes.
When should I use US ETF Flow and Sector Breadth?
US ETF Flow and Sector Breadth fits situations like: reading institutional risk appetite from ETF inflows and outflows; judging sector rotation from sector ETF flows and breadth; matching sector ETFs to a stage of the economic cycle; separating real capital flows from price momentum in an ETF.
How do I install US ETF Flow and Sector Breadth in Claude Code?
Run `npx skills add HKUDS/Vibe-Trading --skill us-etf-flow -a claude-code`. Or copy the skill folder (agent/src/skills/us-etf-flow in HKUDS/Vibe-Trading) into .claude/skills/us-etf-flow in your project. Claude Code loads it when a task matches its description.
How do I install US ETF Flow and Sector Breadth in Codex?
Run `npx skills add HKUDS/Vibe-Trading --skill us-etf-flow -a codex`. Or copy the skill folder (agent/src/skills/us-etf-flow in HKUDS/Vibe-Trading) into .agents/skills/us-etf-flow in your project. Codex loads it when a task matches its description.
Can I use US ETF Flow and Sector Breadth 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 HKUDS/Vibe-Trading --skill us-etf-flow -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-etf-flow, .gemini/skills/us-etf-flow, .github/skills/us-etf-flow and .opencode/skills/us-etf-flow in your project.
What does US ETF Flow and Sector Breadth need to run?
SKILL.md names no scripts, command-line tools or credentials: US ETF Flow and Sector Breadth is instructions for the agent only.
Does US ETF Flow and Sector Breadth access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is US ETF Flow and Sector Breadth 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. Review the folder before installing.
What licence does US ETF Flow and Sector Breadth use?
US ETF Flow and Sector Breadth 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 ETF Flow and Sector Breadth use?
About 2.6k tokens (SKILL.md is roughly 10k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to US ETF Flow and Sector Breadth?
Skills that share tags, products or a category with US ETF Flow and Sector Breadth: AI-Trader Market Intel (HKUDS/AI-Trader, 23k stars), Stock Deep Analysis Workflow (wbh604/UZI-Skill, 7.1k stars), Zhengxi Fund Manager Views Library (lyra81604/zhengxi-views, 1.8k stars) and Supply Chain Bottleneck Hunter (xbtlin/ai-berkshire, 17k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains US ETF Flow and Sector Breadth?
HKUDS (a GitHub organization) maintains it in HKUDS/Vibe-Trading, which has 35,043 GitHub stars. The repository holds 89 skills in this directory. The repository was last updated on October 8, 2026.
Source: HKUDS/Vibe-Trading on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.