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actualizar-macrodata-espana

Updates a Spanish macroeconomic indicators dashboard by editing a single data.json file.

Updated Apr 18, 2018
Search Tags:#dashboard#json#economic indicators#macroeconomics#data update#spain#eurostat
One-click install
npx skills add https://github.com/Emirodgar/w-emirodgar-es --skill actualizar-macrodata-espana-emirodgar
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: actualizar-macrodata-espana
Source: https://github.com/Emirodgar/w-emirodgar-es/tree/main/.claude/skills/actualizar-macrodata-espana
Command: npx skills add https://github.com/Emirodgar/w-emirodgar-es --skill actualizar-macrodata-espana-emirodgar

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Keeping a public macroeconomic dashboard for Spain current requires manually checking many official sources (INE, Banco de España, BCE, Eurostat, Federal Reserve) and carefully editing a structured JSON dataset without breaking the schema. This Skill guides the full update workflow so the panel, home widget, recession-risk gauge, and FAQ section stay synchronized with the latest published figures. ## Core Features & Use Cases - Official data sourcing: Fetches the latest published figures for IPC, risk premium, ECB rate, Euríbor, Fed rate, GDP, and EPA unemployment from official sources via web search, never inventing numbers. - Schema-safe data.json editing: Updates indicators, historicalData, and the Spain vs. eurozone comparison while respecting fixed ids, quarterly repetition rules, and year-over-year change conventions. - Derived content regeneration: Rewrites the executive summary and regenerates the static sparkline SVG from the last 6 months of historical data using a provided Python script. - Use Case: A site maintainer says "actualiza MacroData" and the assistant checks each official source, appends new monthly entries, refreshes the Eurostat comparison, regenerates the sparkline, and reports which figures changed. ## Quick Start Ask the assistant to update the MacroData España panel with the latest official economic figures.

Frequently Asked Questions about actualizar-macrodata-espana

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I update a macroeconomic dashboard with official Spanish data?▼

Fetch the latest published figures from official sources like INE, Banco de España, ECB, and Eurostat, then edit the single data.json file the dashboard consumes. The panel, home widget, recession gauge, and FAQ all render dynamically from that file, so no HTML or JavaScript changes are needed.

What data sources are used for Spanish economic indicators?▼

IPC and unemployment come from INE press releases, the ECB rate from monetary policy decisions, Euríbor from Banco de España monthly averages, GDP from quarterly national accounts, and the eurozone comparison from Eurostat harmonized series. The Fed funds rate uses the midpoint of the FOMC target range.

How is the recession risk gauge calculated?▼

The gauge is a 0-100 index computed in the page's JavaScript from five indicator fields: GDP growth weighted 35%, unemployment momentum 25%, inflation distance from the 2% target 15%, and financial conditions 25% combining the ECB rate and risk premium. It is not stored in data.json and recalculates on every page load.

Why do EPA unemployment and Eurostat harmonized unemployment differ?▼

They are intentionally distinct series with different methodologies: the EPA rate is a quarterly INE survey, while the Eurostat harmonized rate is monthly with a publication lag. Both coexist in the panel by design and should never be forced to match.

What happens when no new data has been published for an indicator?▼

Quarterly indicators like GDP and EPA unemployment repeat the last known value for months within the same quarter, and policy rates stay unchanged until the next ECB or FOMC meeting. Figures are never invented; only the most recent officially published data is used.

How is the home page sparkline SVG regenerated?▼

A provided Python script reads the last 6 months of historicalData from data.json, normalizes the general and core IPC values into a 320x110 viewBox, and writes a self-contained SVG with area fill, solid and dashed lines, and month points back into the sparklineSvg field.

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