Dashboard Brief Skill

Convert a business question into a complete dashboard specification.

Dashboard Brief Skill — The Skill Playground: pick the Executive Update skill, fill in a few notes, hit run, and watch a structured executive… (from the mohitagw15856/pm-claude-skills README)

From the mohitagw15856/pm-claude-skills README — shows the whole collection, not only this skill. · view on GitHub

How to use it

Claude Code
  1. Run the line below. It pulls the whole folder into ~/.claude/skills/dashboard-brief.
  2. Describe your job in plain words. Claude Code follows the skill from there.
Claude Code — installs the whole folder, not just SKILL.md
npx degit mohitagw15856/pm-claude-skills/skills/dashboard-brief#main ~/.claude/skills/dashboard-brief

For one project only, change the path to .claude/skills/dashboard-brief.

Claude (web or desktop app)
  1. On this page open ⋯ → Download .md.
  2. Save it as SKILL.md in a folder, zip the folder, then Customize → Skills → + → Create skill → Upload a skill.
  3. Pick the file and Save. Claude shows the name and description and runs a security scan.
  4. Check the skill is switched on.
  5. Start a new chat and describe your job in plain words. The AI follows the skill from there.
ChatGPT or another app
  1. ChatGPT: make a Project and paste it into Instructions.
  2. Neither? Paste it at the top of a new chat — it works for that chat.
Not working?
  • Check which app you pasted it into — the steps above name the right one.
  • Some skills need the paid tier of Claude or ChatGPT.
Step-by-step guide with screenshots · Ask in the forum

Paste into Claude, ChatGPT or Cursor.

Source of Dashboard Brief Skill

Show the full text131 lines
namedescription
dashboard-briefConvert 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---
2name: dashboard-brief
3description: "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 
8This 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 
12Ask 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 
35List 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 
41Aim for 3–6 KPI cards. More than 6 is noise.
42 
43---
44 
45## Section 2: Charts & Visualisations
46 
47For 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 
64Global 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 
76Describe 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 
89List 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 
95Flag 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 

Discussion

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