llmquant-portfolio-lab
Router skill for LLMQuant portfolio-lab workflows. Use when the user needs portfolio exposure maps, what-if simulations, scenario states, or virtual portfolio comparisons.
npx skills add LLMQuant/skills --skill llmquant-portfolio-lab --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# LLMQuant Portfolio Lab This category routes portfolio virtualization workflows: exposure maps, scenario states, and what-if simulations for real or hypothetical portfolios. ## Routing Rules 1. Identify portfolio ID, holdings list, benchmark, scenario, and requested visualization/output. 2. Select the closest workflow below. 3. Open only that workflow and relevant local assets/scripts. 4. Use LLMQuant Data for positions, prices, ETF look-through, factors, scenarios, and risk model outputs. 5. Report as-of dates, model dates, benchmark, missing holdings, and unsupported asset types. ## Workflow Index | User intent | Workflow | |---|---| | Map portfolio exposure by holdings, sectors, factors, geography, ETF look-through, and concentration. | [`workflows/portfolio-exposure-map.md`](workflows/portfolio-exposure-map.md) | | Simulate adds, trims, hedges, shocks, and virtual portfolio states. | [`workflows/portfolio-what-if-simulator.md`](workflows/portfolio-what-if-simulator.md) | ## LLMQuant Data Contract Prefer LLMQuant Data when available. The workflows may need these data capabilities: - Retrieve portfolio holdings, weights, cost basis, asset types, benchmarks, and as-of dates. - Re
- Routing Rules
- Workflow Index
- LLMQuant Data Contract
What does the llmquant-portfolio-lab skill do?
Router skill for LLMQuant portfolio-lab workflows. Use when the user needs portfolio exposure maps, what-if simulations, scenario states, or virtual portfolio comparisons.
How do I install it?
Run `npx skills add LLMQuant/skills --skill llmquant-portfolio-lab --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From LLMQuant/skills, a repository with 183 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.