Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/ancoleman/ai-design-componentsnpx agentmods add skills/ancoleman/ai-design-components/creating-dashboardsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/ancoleman/ai-design-components/creating-dashboards)<a href="https://agentmods.dev/skills/ancoleman/ai-design-components/creating-dashboards"><img src="https://agentmods.dev/badge/skills/ancoleman/ai-design-components/creating-dashboards.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00062 | $0.03143 |
| Opus 5 | $0.00031 | $0.01571 |
| Sonnet 5 | $0.00012 | $0.00629 |
| Haiku 4.5 | $0.00006 | $0.00314 |
Grade A, and why
creating-dashboards scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 443 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Creating Dashboards
Purpose
This skill enables the creation of sophisticated dashboard interfaces that aggregate and present data through coordinated widgets including KPI cards, charts, tables, and filters. Dashboards serve as centralized command centers for data-driven decision making, combining multiple component types from other skills (data-viz, tables, design-tokens) into unified analytics experiences with real-time updates, responsive layouts, and interactive filtering.
When to Use
Activate this skill when:
- Building business intelligence or analytics dashboards
- Creating executive reporting interfaces
- Implementing real-time monitoring systems
- Designing KPI displays with metrics and trends
- Developing customizable widget-based layouts
- Coordinating filters across multiple data displays
- Building responsive data-heavy interfaces
- Implementing drag-and-drop dashboard editors
- Creating template-based analytics systems
- Designing multi-tenant SaaS dashboards
Core Dashboard Elements
KPI Card Anatomy
┌────────────────────────────┐
│ Revenue (This Month) │ ← Label with time period
│ │
│ $1,245,832 │ ← Big number (primary metric)
│ ↑ 15.3% vs last month │ ← Trend indicator with comparison
│ ▂▃▅▆▇█ (sparkline) │ ← Mini visualization
└────────────────────────────┘
Widget Container Structure
- Title bar with widget name and actions
- Loading state (skeleton or spinner)
- Error boundary with retry option
- Resize handles for adjustable layouts
- Settings menu (export, configure, refresh)
Dashboard Layout Types
Fixed Layout: Designer-defined placement, consistent across users Customizable Grid: User drag-and-drop, resizable widgets, saved layouts Template-Based: Pre-built patterns, industry-specific starting points
Global Dashboard Controls
- Date range picker (affects all widgets)
- Filter panel (coordinated across widgets)
- Refresh controls (manual/auto-refresh)
- Export actions (PDF, image, data)
- Theme switcher (light/dark/custom)
What ships with it
23 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- assets/dashboard-templates.json 11 KB
- assets/grid-layouts.json 5.2 KB
- assets/kpi-formats.json 3.5 KB
- assets/theme-tokens.json 2.7 KB
- assets/widget-library.json 14 KB
- examples/customizable-dashboard.tsx 4.5 KB
- examples/executive-dashboard.tsx 6.1 KB
- examples/filter-context.tsx 4.7 KB
- examples/monitoring-dashboard.tsx 6.5 KB
- examples/sales-dashboard.tsx 16 KB
- examples/tremor-dashboard.tsx 2.8 KB
- outputs.yaml 18 KB
- references/filter-coordination.md 21 KB
- references/kpi-card-patterns.md 12 KB
- references/layout-strategies.md 14 KB
- references/library-guide.md 18 KB
- references/performance-optimization.md 18 KB
- references/real-time-updates.md 21 KB
- scripts/calculate-kpi-metrics.py 12 KB runs code
- scripts/export-dashboard.py 6.6 KB runs code
- scripts/generate-dashboard-layout.py 9.7 KB runs code
- scripts/optimize-dashboard-performance.py 7.1 KB runs code
- scripts/validate-widget-config.py 16 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 443 lines · 62 tokens per session scan A 3c150031250e
creating-dashboards is a skill published in the GitHub repository ancoleman/ai-design-components (518 stars, last pushed 8mo ago), licensed MIT. It adds 62 tokens to every session and 3,143 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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