Agent skill · data analytics · borghei
business-intelligence
Business intelligence across dashboard design, visualization, and reporting automation. Use when designing dashboards, building KPI frameworks, automating reports, creating data stories, or optimizing BI tool performance.
Why this skill is useful
Provides specific templates and workflows for KPI definitions and dashboard design that the AI wouldn't reliably generate on its own.
What it needs
About 7k tokens when loaded. Last updated 2026-07-21. 462 stars on the source repository.
What this skill does
Business Intelligence The agent operates as a senior BI specialist, designing dashboards, defining KPI frameworks, automating reporting pipelines, and translating data into executive-ready narratives. Clarify First Before designing the dashboard, confirm these inputs. If any is unknown or vague, ASK — do not assume: [ ] Audience — executive, operational, or self-service (sets the layout, altitude, and metric count per page) [ ] Key questions + refresh cadence — what decisions the dashboard drives and how fresh the data must be (scopes the metrics and the live-vs-extract choice) [ ] KPI definitions — formula, data source, owner, and RAG thresholds per metric (these are the exact fields the KPI template and metricvalidator.py require) Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact. Workflow 1. Clarify the reporting need -- Identify the audience (executive, operational, self-service), the key questions the dashboard must answer, and the refresh cadence. Validate that required data sources exist and are accessible. 2. Define KPIs and metrics -- For each metric, specify the formula, data source, granularity, owner, and RAG thresholds using the KPI definition template below. 3. Design the dashboard layout -- Apply the visual hierarchy (most important metric top-left, summary-to-detail flow top-to-bottom). Select chart types using the chart selection matrix. Limit to 5-8 visualizations per page. 4. Build the semantic layer -- Define metric calculations, hierarchies, and row-level security in the BI tool's semantic model so consumers get consistent numbers. 5. Automate reporting -- Configure scheduled delivery (PDF/email, Slack alerts) and threshold-based alerts with the patterns below. 6. Validate and iterate -- Confirm KPI values match source-of-truth queries. Check dashboard load time (<5 s target). Gather stakeholder feedback and refine. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills borghei/business-intelligence