Dashboard Brief Skill
Convert a business question into a complete dashboard specification.
How to use it
Claude Code
- Run the line below. It pulls the whole folder into
~/.claude/skills/dashboard-brief. - Describe your job in plain words. Claude Code follows the skill from there.
npx degit mohitagw15856/pm-claude-skills/skills/dashboard-brief#main ~/.claude/skills/dashboard-briefFor one project only, change the path to .claude/skills/dashboard-brief.
Claude (web or desktop app)
- On this page open ⋯ → Download .md.
- Save it as SKILL.md in a folder, zip the folder, then Customize → Skills → + → Create skill → Upload a skill.
- Pick the file and Save. Claude shows the name and description and runs a security scan.
- Check the skill is switched on.
- Start a new chat and describe your job in plain words. The AI follows the skill from there.
ChatGPT or another app
- ChatGPT: make a Project and paste it into Instructions.
- Neither? Paste it at the top of a new chat — it works for that chat.
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- Check which app you pasted it into — the steps above name the right one.
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Paste into Claude, ChatGPT or Cursor.
Source of Dashboard Brief Skill
Show the full text131 lines
| name | description |
|---|---|
| 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. |
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"
| 1 | |
| 2 | name dashboard-brief |
| 3 | description "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." |
| 4 | |
| 5 | |
| 6 | # Dashboard Brief Skill |
| 7 | |
| 8 | 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. |
| 9 | |
| 10 | ## Required Inputs |
| 11 | |
| 12 | Ask the user for these if not provided: |
| 13 | **The business question this dashboard should answer** (e.g. "How is our activation funnel performing this week?") |
| 14 | **Primary audience** (exec / product team / operations / customer success / engineering) |
| 15 | **Refresh cadence** (real-time / hourly / daily / weekly) |
| 16 | **Data sources available** (e.g. Postgres, BigQuery, Mixpanel, Salesforce, Jira) |
| 17 | **BI tool being used** (Looker / Metabase / Tableau / Power BI / Grafana / Custom / Unknown) |
| 18 | |
| 19 | ## Output Structure |
| 20 | |
| 21 | |
| 22 | |
| 23 | # Dashboard Brief: [Dashboard Name] |
| 24 | |
| 25 | **Business Question:** [The question this dashboard answers — verbatim from inputs or refined] |
| 26 | **Audience:** [Who uses this] |
| 27 | **Refresh Rate:** [Real-time / Hourly / Daily / Weekly] |
| 28 | **Data Sources:** [List] |
| 29 | **BI Tool:** [Tool or Unknown] |
| 30 | |
| 31 | |
| 32 | |
| 33 | ## Section 1: Key Metrics (KPI Cards) |
| 34 | |
| 35 | List the headline numbers that should appear at the top of the dashboard as KPI cards. |
| 36 | |
| 37 | | Metric | Definition | Data Source | Comparison | |
| 38 | |---|---|---|---| |
| 39 | | [Metric name] | [How it's calculated] | [Table/source] | [vs. last week / vs. target / MoM] | |
| 40 | |
| 41 | Aim for 3–6 KPI cards. More than 6 is noise. |
| 42 | |
| 43 | |
| 44 | |
| 45 | ## Section 2: Charts & Visualisations |
| 46 | |
| 47 | For each chart, specify: |
| 48 | |
| 49 | ### Chart [N]: [Chart Title] |
| 50 | |
| 51 | **Chart type:** [Line / Bar / Stacked bar / Pie / Funnel / Heatmap / Table / Scatter] |
| 52 | **Why this chart type:** [One sentence — why this type suits this data] |
| 53 | **X-axis / Rows:** [Dimension — e.g. Date, User segment, Product] |
| 54 | **Y-axis / Values:** [Metric — e.g. Count of active users, Revenue] |
| 55 | **Breakdown/colour:** [Optional secondary dimension — e.g. by Plan tier, by Channel] |
| 56 | **Data source:** [Table or source] |
| 57 | **Filters:** [Any default filters applied — e.g. "Exclude internal test accounts"] |
| 58 | **Key insight to surface:** [What pattern or signal this chart should help the viewer spot] |
| 59 | |
| 60 | |
| 61 | |
| 62 | ## Section 3: Filters & Controls |
| 63 | |
| 64 | Global filters available to dashboard viewers: |
| 65 | |
| 66 | | Filter | Type | Default | Options | |
| 67 | |---|---|---|---| |
| 68 | | Date range | Date picker | Last 30 days | Custom | |
| 69 | | [Segment filter] | Dropdown | All | [List relevant values] | |
| 70 | | [Other filter] | Multi-select | All | [List relevant values] | |
| 71 | |
| 72 | |
| 73 | |
| 74 | ## Section 4: Layout Recommendation |
| 75 | |
| 76 | Describe the dashboard layout in plain terms: |
| 77 | |
| 78 | |
| 79 | [ROW 1 — KPI Cards]: [Metric 1] | [Metric 2] | [Metric 3] | [Metric 4] |
| 80 | [ROW 2 — Primary chart, full width]: [Chart name] |
| 81 | [ROW 3 — Two charts side by side]: [Chart A] | [Chart B] |
| 82 | [ROW 4 — Supporting table, full width]: [Table name] |
| 83 | |
| 84 | |
| 85 | |
| 86 | |
| 87 | ## Section 5: Data Requirements |
| 88 | |
| 89 | List any data transformations, joins, or derived fields needed: |
| 90 | |
| 91 | | Derived Field | Logic | Source Tables | |
| 92 | |---|---|---| |
| 93 | | [Field name] | [How it's calculated] | [Tables involved] | |
| 94 | |
| 95 | Flag any fields that may not exist in current data infrastructure. |
| 96 | |
| 97 | |
| 98 | |
| 99 | ## Section 6: Access & Ownership |
| 100 | |
| 101 | **Dashboard owner:** [Leave for user to fill] |
| 102 | **Who can edit:** [Leave for user to fill] |
| 103 | **Who can view:** [Leave for user to fill] |
| 104 | **Review cadence:** [When should this dashboard be reviewed for relevance?] |
| 105 | |
| 106 | |
| 107 | |
| 108 | ## Quality Checks |
| 109 | |
| 110 | [ ] Every chart has a stated "key insight to surface" — not just "show the data" |
| 111 | [ ] KPI cards are 3–6 (not more) |
| 112 | [ ] Chart types are justified |
| 113 | [ ] Layout follows visual hierarchy (summary → detail) |
| 114 | [ ] Data requirements section flags any missing fields |
| 115 | [ ] Filters are practical and don't require IT to configure |
| 116 | |
| 117 | ## Anti-Patterns |
| 118 | |
| 119 | [ ] Do not specify metrics that the available data sources cannot actually support — always validate data availability |
| 120 | [ ] Do not include more than 8–10 primary metrics on a single dashboard — more creates noise, not insight |
| 121 | [ ] Do not skip the primary business question — a dashboard without a north-star question becomes a vanity metrics display |
| 122 | [ ] Do not choose chart types for aesthetic reasons — every chart type must match the data relationship it represents |
| 123 | [ ] Do not leave filter configurations vague — specify exact filter values, not just filter categories |
| 124 | |
| 125 | ## Example Trigger Phrases |
| 126 | |
| 127 | "Design a dashboard to track [business process]" |
| 128 | "Give me a spec for a [team] performance dashboard" |
| 129 | "What should go on a [topic] dashboard?" |
| 130 | "Write a dashboard brief for our [metric] monitoring" |
| 131 |
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