Data Dashboard Design

What it does

When your agent uses it

• The user needs to create a dashboard
• Choose the right visualizations
• Organize metrics for different audiences
• Evaluate dashboard tools — even if they say build a dashboard

Example prompts

• “build a dashboard”
• “our reports are confusing”
• “which chart should I use”
• “/data-dashboard-design”

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

1. 15-second rule: The dashboard's main message should be clear within 5 seconds
2. 2Above the fold: Most important metrics visible without scrolling
3. 3Consistent time range: All charts on one dashboard should use the same time period by default
4. 4Color with purpose: Use color to encode meaning (red = bad, green = good), not decoration
5. 5Comparison context: Every number needs context — vs prior period, vs target, vs benchmark
6. 6Progressive disclosure: Summary at top → click/drill to detail

What it can do on your machine

Read from SKILL.md and the folder at commit 4e7f4f8. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  No URLs in SKILL.md.

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Data Dashboard Design loads about 1.4k tokens when it runs, and up to ~9.2k if it reads all its reference files. Until then it costs about 109 tokens; SKILL.md has 458 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~109

When it runs · the whole SKILL.md, loaded when a task matches

~1.4k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~9.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from asgard-ai-platform/skills at commit 4e7f4f8, republished under its MIT licence (© asgard-ai-platform). 458 words, ~1,433 tokens.

name

data-dashboard-design

description

Design effective data dashboards with proper KPI hierarchy, chart type selection, and interactive features. Use this skill when the user needs to create a dashboard, choose the right visualizations, organize metrics for different audiences, or evaluate dashboard tools — even if they say 'build a dashboard', 'our reports are confusing', 'which chart should I use', or 'executives can't find the metrics they need'.

metadata.category

WP-04 數據分析

metadata.tags

data-analysis, dashboard, visualization, bi

IRON LAW: One Dashboard, One Audience, One Purpose

A dashboard that tries to serve the CEO, the marketing team, AND the
engineers will serve none of them well. Each audience has different
questions, different metrics, and different time horizons.

CEO: "Are we growing?" → North Star + revenue + key trends
Marketing: "Which campaigns work?" → CAC, ROAS, conversion by channel
Engineering: "Is the system healthy?" → Latency, error rate, uptime

          [North Star Metric]
         /                    \
    [L1: 3-5 Business KPIs]
       /         |         \
  [L2: Driving Metrics per KPI]
     /     |     |     |     \
[L3: Diagnostic / Operational Metrics]

# Dashboard Specification: {Name}

## Purpose & Audience
- Audience: {who}
- Key question: {what they need to answer}
- Refresh: {real-time / daily / weekly}

## KPI Hierarchy
- North Star: {metric}
- L1 KPIs: {3-5 metrics}
- L2 Driving Metrics: {per L1}

## Layout
| Position | Component | Chart Type | Metric |
|----------|-----------|-----------|--------|
| Top-left | {scorecard} | Big number | {North Star} |
| Top-right | {trend} | Line chart | {key KPI over time} |
| Mid-left | {comparison} | Bar chart | {breakdown by segment} |
| ... | ... | ... | ... |

## Filters
- Date range, product, segment, region

## Alerts
| Metric | Threshold | Alert To |
|--------|-----------|---------|
| {metric} | {value} | {team/person} |

© asgard-ai-platform, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (references) in data-dashboard-design of asgard-ai-platform/skills.

• SKILL.md
• examples/sample_scenario.md
• references/dashboard-templates.md
• references/metric-definitions.md

Open the folder on GitHubat commit 4e7f4f8