llmquant-macro
Router skill for LLMQuant macro workflows. Use when the user needs macro dashboards, Fed or central-bank previews, inflation and growth context, liquidity, or macro-to-portfolio impact analysis.
npx skills add LLMQuant/skills --skill llmquant-macro --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 Macro This category routes macroeconomic research workflows for regime dashboards, policy previews, and portfolio impact mapping. ## Routing Rules 1. Identify geography, indicators, policy body, asset universe, horizon, and requested deliverable. 2. Select the closest workflow below. 3. Open only that workflow and any referenced local resources. 4. Use LLMQuant Data for macro observations, release dates, rates, FX, commodities, credit, equity indices, and research context. 5. Report observation dates, release dates, revisions, frequencies, stale notices, and missing inputs. ## Workflow Index | User intent | Workflow | |---|---| | Build a cross-indicator macro dashboard and regime view. | [`workflows/global-macro-dashboard.md`](workflows/global-macro-dashboard.md) | | Prepare a Fed or central-bank policy meeting preview. | [`workflows/fed-policy-preview.md`](workflows/fed-policy-preview.md) | | Translate macro data into equity, rates, credit, FX, commodity, and portfolio implications. | [`workflows/macro-to-portfolio-impact.md`](workflows/macro-to-portfolio-impact.md) | ## LLMQuant Data Contract Prefer LLMQuant Data when available. The workflows may need these data capabi
- Routing Rules
- Workflow Index
- LLMQuant Data Contract
What does the llmquant-macro skill do?
Router skill for LLMQuant macro workflows. Use when the user needs macro dashboards, Fed or central-bank previews, inflation and growth context, liquidity, or macro-to-portfolio impact analysis.
How do I install it?
Run `npx skills add LLMQuant/skills --skill llmquant-macro --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.