dashboard-brief
# dashboard-brief The dashboard-brief skill converts a business question into a structured, implementation-ready dashboard specification for data engineers and BI developers. Use this skill when asked to design a dashboard, create a dashboard brief or specification, plan a BI report, or define what metrics and charts a dashboard should contain. It produces a detailed specification including KPI metrics, chart types and dimensions, filters, data sources, and layout guidance without requiring follow-up meetings.
git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills /tmp/dashboard-brief && cp -r /tmp/dashboard-brief/plugins/pm-data/skills/dashboard-brief ~/.claude/skills/dashboard-briefSKILL.md
# 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. | Metric | Definition | Data Source | Comparison | |---|---|---|---| | [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: | Filter | Type | Default | Options | |---|---|---|---| | Date range | Date picker | Last 30 days | Custom | | [Segment filter] | Dropdown | All | [List relevant values] | | [Other filter] | Multi-select | All | [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 Field | Logic | Source 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"
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