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/dansasser/claude-code-marketplace/data-visualizationnpx skills add dansasser/claude-code-marketplace --skill data-visualizationgit clone --depth 1 https://github.com/dansasser/claude-code-marketplaceWhat 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 | $0.00029 | $0.00385 |
| Opus 5 | $0.00015 | $0.00192 |
| Sonnet 5 | $0.00006 | $0.00077 |
| Haiku 4.5 | $0.00003 | $0.00038 |
Grade A, and why
data-visualization 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.
What it actually says
Use the Remotion best practices skill (SKILL.md at the plugin root). Follow its scene planning algorithm for all production steps.
Data Visualization Dashboard
Input
$ARGUMENTS
Questionnaire
If not answered by the input, ask:
- What data? — CSV file path, API endpoint, or should I generate sample data?
- What story? — What's the key takeaway from this data?
- Style? — Default: dark glass-morphism dashboard. Other options: clean/minimal, corporate, neon.
Script
Analyze the data and propose:
- A dashboard title
- The single most impressive KPI stat (hero card)
- Best chart types for the data (bar, donut, line, etc.)
- Layout of 4 panels
Present for approval before building.
Panel Structure
- Panel 1: Hero KPI — large count-up number with trend indicator (arrow up/down)
- Panel 2: Comparison chart — horizontal bars or grouped bars
- Panel 3: Composition chart — donut or pie showing parts of a whole
- Panel 4: Trend chart — line chart with gradient fill showing change over time
Visual Approach
- 4-panel vertical stack with padding between panels
- Glass-morphism card backgrounds (semi-transparent, subtle border, blur)
- SVG-based charts — bars grow with spring animation, donut segments draw clockwise, line draws left-to-right
- Key numbers use count-up animation with
tabular-numsfont variant - Staggered panel entrances — each panel animates in after the previous one
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 · 42 lines · 29 tokens per session scan A ba012db657e2
data-visualization is a skill published in the GitHub repository dansasser/claude-code-marketplace (9 stars, last pushed 3mo ago), licensed MIT. It adds 29 tokens to every session and 385 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 2026-08-31.
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