LLMQuant ETFs

SkillDev tools

Router skill for LLMQuant ETFs workflows. Use when the user needs ETF holdings, overlap, concentration, issuer snapshot, or theme exposure analysis.

Available today. Use it from your connected AI after setup.

No other account needed.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the LLMQuant ETFs skill

What this skill tells your AI

The instructions your AI receives, as published by llmquant/skills in skills/llmquant-etfs/SKILL.md and read by ahel’s review.

This category routes ETF analysis tasks to holdings and exposure workflows.

Identify the ETF tickers, comparison universe, as-of date, and required output.
Select the closest workflow below.
Open only the selected workflow and required local resources.
Use LLMQuant Data for holdings, fund metadata, prices, and coverage notices.
Report holdings as_of_date, source, stale flags, unsupported tickers, and missing fields.

User intent	Workflow
Compare ETF holdings, overlap, concentration, and exposure.	`workflows/etf-overlap-report.md`

Prefer LLMQuant Data when available. The workflows may need these data capabilities:

Look up ETF identity, issuer, category, expense ratio, market price, NAV, and coverage status.
Retrieve ETF holdings with weights, identifiers, sectors, countries, source, and holdings as-of date.
Compare ETF holdings overlap, top-name concentration, and exposure breakdowns.
Retrieve price history, fund-flow history, and sector exposure history when available.

Fallback:

If holdings coverage is unsupported, report the unsupported ticker and the ETF identifiers needed.
If LLMQuant Data or a compatible data MCP is unavailable, ask the user for issuer holdings files or holdings tables.
Do not approximate holdings from memory.

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