Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/codebygarv/ai-skills/data-table-ux-designernpx skills add codebygarv/Ai-skills --skill data-table-ux-designergit clone --depth 1 https://github.com/codebygarv/Ai-skillsWrote 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/codebygarv/ai-skills/data-table-ux-designer)<a href="https://agentmods.dev/skills/codebygarv/ai-skills/data-table-ux-designer"><img src="https://agentmods.dev/badge/skills/codebygarv/ai-skills/data-table-ux-designer.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 | $0.00026 | $0.00332 |
| Opus 5 | $0.00013 | $0.00166 |
| Sonnet 5 | $0.00005 | $0.00066 |
| Haiku 4.5 | $0.00003 | $0.00033 |
Grade A, and why
data-table-ux-designer 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 yesterday.
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.
What it actually says
Purpose
Design accessible, high-performance data tables and grids that support massive datasets, dense information architecture, multi-column sorting, column reordering, inline editing, and virtualization.
When to Use
- Building enterprise dashboards, CRM lists, log viewers, or financial data grids.
- Users struggling to find records or complaining about slow rendering with 1,000+ rows.
- Designing responsive table adaptations for mobile and tablet screens.
What to Analyze
- Information Density: Compact vs Standard vs Comfortable row height toggles.
- Fixed Elements: Sticky table header (
position: sticky) and sticky left identifier / right action columns. - Filtering & Facets: Search bar, multi-select tag filters, date range pickers, and active filter pill bar.
- Column Controls: Visibility toggles, column resizing handles, and drag-and-drop reordering.
- Performance & Virtualization: Windowed DOM rendering (e.g. TanStack Table / react-window) for 10k+ rows.
Output Format
- Table Component Structure: HTML/React layout with sticky headers and action bar.
- UX Controls Blueprint: Filter bar, bulk actions toolbar, pagination/infinite scroll controls.
- Mobile Responsive Pattern: Card transformation or horizontal scrolling container specification.
Avoid
- Rendering thousands of un-virtualized DOM table rows simultaneously.
- Hiding crucial action buttons behind 3 nested dropdown menus per row.
What ships with it
2 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.
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.
- yesterday First seen · 34 lines · 26 tokens per session scan A 35ab75ebea9b
data-table-ux-designer is a skill published in the GitHub repository codebygarv/Ai-skills (25 stars, last pushed 16d ago), licensed MIT. It adds 26 tokens to every session and 332 once invoked, about $0.0001 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 2026-09-03.
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