mohitagw15856/pm-claude-skills

dashboard-brief

Convert a business question into a complete dashboard specification.

First seen Apr 3, 2026

Installation

$ npx skills add mohitagw15856/pm-claude-skills --skill dashboard-brief

Summary

  • 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.

Similar popular skills

Related neighbors and high-traction skills in the same topics — useful to compare before installing.

Also in this package

Other skills from mohitagw15856/pm-claude-skills · top by installs.

npx skills add mohitagw15856/pm-claude-skills

Browse all from mohitagw15856/pm-claude-skills

More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 1.3K
License LICENSE
Default branch main
Open issues 7
Status Active

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 4,895 B
  • docs SUMMARY.md 339 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 53 installs

SKILL.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"