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/altimateai/altimate-code/data-viznpx skills add AltimateAI/altimate-code --skill data-vizgit clone --depth 1 https://github.com/AltimateAI/altimate-codeWhat 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 | $0.00189 | $0.01981 |
| Opus 5 | $0.00095 | $0.00991 |
| Sonnet 5 | $0.00038 | $0.00396 |
| Haiku 4.5 | $0.00019 | $0.00198 |
Grade A, and why
data-viz 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 2d 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 — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI-First Data Visualization
Philosophy
Build production-quality interactive data interfaces with modern component libraries — no vendor lock-in, embeddable anywhere. When no tool is specified, build code-first. When the user explicitly names a BI tool, use it — only suggest code-first if they ask for options or hit a technical blocker.
Technology Stack
Full API patterns & code: references/component-guide.md
Framework Priority
- React + Tailwind — Default when JSX/TSX supported
- HTML + CSS + Vanilla JS — Fallback (use D3 or Chart.js)
- Python (Plotly/Dash) — Python-only environments only
Library Selection
| Library | Best For |
|---|---|
| shadcn/ui charts | Default first choice — general dashboards, most chart types |
| Recharts | Line, bar, area, composed, radar — fine-grained control |
| Tremor | KPI cards, metric displays, full dashboard layouts |
| Nivo | Heatmaps, treemaps, choropleth, calendar, Sankey, funnel |
| visx | Bespoke custom viz — D3-level control with React |
| D3.js | Force-directed graphs, DAGs, maps — maximum flexibility |
| Victory | When animation quality matters most |
Supporting: Tailwind CSS · Radix UI · Framer Motion · Lucide React · date-fns · Papaparse · lodash
Building a Visualization
Step 1: Understand the Data Story
Before code, identify: What question does the data answer? Who is the audience (exec → KPIs only, analyst → drill-down, public → narrative)? What's the ONE key insight? Design around it.
Step 2: Choose Chart Type
| Data Relationship | Chart Type | Library |
|---|---|---|
| Trend over time | Line, Area | shadcn/Recharts |
| Category comparison | Bar (horizontal if many) | shadcn/Recharts |
| Part of whole | Donut, Treemap | shadcn/Nivo |
| Distribution | Histogram, Box, Violin | Nivo/visx |
| Correlation | Scatter, Bubble | Recharts/visx |
| Geographic | Choropleth, Dot map | Nivo/D3 |
| Hierarchical | Treemap, Sunburst | Nivo |
| Flow / Process | Sankey, Funnel | Nivo/D3 |
| Single KPI | Metric card, Gauge, Sparkline | Tremor/shadcn |
| Multi-metric overview | Dashboard grid of cards | Tremor + shadcn |
| Ranking | Horizontal bar, Bar list | Tremor |
| Column/model lineage | Force-directed DAG | D3 |
| Pipeline dependencies | Hierarchical tree, DAG | D3/Nivo |
| Multi-dimensional quality | Radar/Spider | Recharts |
| Activity density over time | Calendar heatmap | Nivo |
| Incremental change breakdown | Waterfall | Recharts (custom) |
What ships with it
1 file 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.
- 2d ago First seen · 151 lines · 189 tokens per session scan A 3fffc2fbe92c
data-viz is a skill published in the GitHub repository AltimateAI/altimate-code (803 stars, last pushed 2d ago), licensed MIT. It adds 189 tokens to every session and 1,981 once invoked, about $0.0009 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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