Dashboard Brief

Convert a business question into a complete dashboard specification. Use when asked to design a dashboard, create a dashboard spec or brief, plan a BI report, or define what charts and metrics a dashboard should include. Produces a structured spec with metrics, dimensions, chart types, filters, and layout guidance.

Published by @Mohit Aggarwal·0 agent reads / 30d·0 saves·

Dashboard Brief Skill

This skill converts a business question or monitoring need into a complete, implementation-ready dashboard specification. The output gives a data engineer or BI developer everything they need to build without a follow-up meeting.

Required Inputs

Ask the user for these if not provided:

  • The business question this dashboard should answer (e.g. "How is our activation funnel performing this week?")
  • Primary audience (exec / product team / operations / customer success / engineering)
  • Refresh cadence (real-time / hourly / daily / weekly)
  • Data sources available (e.g. Postgres, BigQuery, Mixpanel, Salesforce, Jira)
  • BI tool being used (Looker / Metabase / Tableau / Power BI / Grafana / Custom / Unknown)

Output Structure


Dashboard Brief: [Dashboard Name]

Business Question: [The question this dashboard answers — verbatim from inputs or refined] Audience: [Who uses this] Refresh Rate: [Real-time / Hourly / Daily / Weekly] Data Sources: [List] BI Tool: [Tool or Unknown]


Section 1: Key Metrics (KPI Cards)

List the headline numbers that should appear at the top of the dashboard as KPI cards.

MetricDefinitionData SourceComparison
[Metric name][How it's calculated][Table/source][vs. last week / vs. target / MoM]

Aim for 3–6 KPI cards. More than 6 is noise.


Section 2: Charts & Visualisations

For each chart, specify:

Chart [N]: [Chart Title]

  • Chart type: [Line / Bar / Stacked bar / Pie / Funnel / Heatmap / Table / Scatter]
  • Why this chart type: [One sentence — why this type suits this data]
  • X-axis / Rows: [Dimension — e.g. Date, User segment, Product]
  • Y-axis / Values: [Metric — e.g. Count of active users, Revenue]
  • Breakdown/colour: [Optional secondary dimension — e.g. by Plan tier, by Channel]
  • Data source: [Table or source]
  • Filters: [Any default filters applied — e.g. "Exclude internal test accounts"]
  • Key insight to surface: [What pattern or signal this chart should help the viewer spot]

Section 3: Filters & Controls

Global filters available to dashboard viewers:

FilterTypeDefaultOptions
Date rangeDate pickerLast 30 daysCustom
[Segment filter]DropdownAll[List relevant values]
[Other filter]Multi-selectAll[List relevant values]

Section 4: Layout Recommendation

Describe the dashboard layout in plain terms:

[ROW 1 — KPI Cards]: [Metric 1] | [Metric 2] | [Metric 3] | [Metric 4]
[ROW 2 — Primary chart, full width]: [Chart name]
[ROW 3 — Two charts side by side]: [Chart A] | [Chart B]
[ROW 4 — Supporting table, full width]: [Table name]

Section 5: Data Requirements

List any data transformations, joins, or derived fields needed:

Derived FieldLogicSource Tables
[Field name][How it's calculated][Tables involved]

Flag any fields that may not exist in current data infrastructure.


Section 6: Access & Ownership

  • Dashboard owner: [Leave for user to fill]
  • Who can edit: [Leave for user to fill]
  • Who can view: [Leave for user to fill]
  • Review cadence: [When should this dashboard be reviewed for relevance?]

Quality Checks

  • Every chart has a stated "key insight to surface" — not just "show the data"
  • KPI cards are 3–6 (not more)
  • Chart types are justified
  • Layout follows visual hierarchy (summary → detail)
  • Data requirements section flags any missing fields
  • Filters are practical and don't require IT to configure

Anti-Patterns

  • Do not specify metrics that the available data sources cannot actually support — always validate data availability
  • Do not include more than 8–10 primary metrics on a single dashboard — more creates noise, not insight
  • Do not skip the primary business question — a dashboard without a north-star question becomes a vanity metrics display
  • Do not choose chart types for aesthetic reasons — every chart type must match the data relationship it represents
  • Do not leave filter configurations vague — specify exact filter values, not just filter categories

Example Trigger Phrases

  • "Design a dashboard to track [business process]"
  • "Give me a spec for a [team] performance dashboard"
  • "What should go on a [topic] dashboard?"
  • "Write a dashboard brief for our [metric] monitoring"

Bundled with this artifact

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Reference files that ship alongside this artifact. Agents pull these in only when the task needs them.

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