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 skills add GPTomics/bioSkills --skill interactive-visualizationgit clone --depth 1 https://github.com/GPTomics/bioSkillsWrote 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/gptomics/bioskills/interactive-visualization)<a href="https://agentmods.dev/skills/gptomics/bioskills/interactive-visualization"><img src="https://agentmods.dev/badge/skills/gptomics/bioskills/interactive-visualization/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/gptomics/bioskills/interactive-visualization"><img src="https://agentmods.dev/badge/skills/gptomics/bioskills/interactive-visualization.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00101 | $0.02914 |
| Opus 5 | $0.00051 | $0.01457 |
| Sonnet 5 | $0.00020 | $0.00583 |
| Haiku 4.5 | $0.00010 | $0.00291 |
Grade A, and why
bio-data-visualization-interactive-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 6d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- bio-data-visualization-interactive-visualization — 95% identical, 12 lines differ
How it starts
The opening of the file, as written. The whole thing — 265 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Version Compatibility
Reference examples tested with: plotly 5.24+, plotly R 4.10+, bokeh 3.4+, kaleido 1.0+ (note: v1 dropped bundled Chrome), gganimate 1.0.9+, altair 5.4+, htmlwidgets 1.6+.
Before using code patterns, verify installed versions match. If versions differ:
- Python:
pip show <package>thenhelp(module.function) - R:
packageVersion('<pkg>')then?function_name
If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.
Interactive Visualization
"Build an interactive plot" -> Render a zoomable, hoverable, panable HTML/web visualization, knowing that interactive output is a SUPPLEMENT to (not replacement for) the static figure needed for journal submission. Choose plotly for fastest onboarding and ggplot2 conversion (ggplotly); bokeh for streaming/server-side; altair for grammar-of-graphics; D3.js for full custom.
- Python:
plotly.graph_objects,plotly.express,bokeh,altair - R:
plotly(viaggplotly),htmlwidgetsecosystem (leaflet, networkD3, DT)
The Single Most Important Modern Insight -- Kaleido v1 and the Static-Export Pipeline
Interactive plots produce HTML, but journals need static PDF/PNG. The plotly static-export pipeline changed materially in 2025:
- Orca is end-of-life (deprecated 2021, removed pipeline 2025)
fig.write_image(..., engine='orca')removed in plotly 6.2 (post-Sept 2025)- Kaleido v1+ is the current standard — pass no
engine=argument - Kaleido v1 dropped bundled Chrome — requires installed Chrome / Chromium
- EPS export removed in Kaleido v1 (was supported via orca's bundled Chromium)
For static export of plotly figures in 2026: pip install kaleido; verify Chrome installed; fig.write_image('out.pdf'). Test by writing to a known path and inspecting file size; silent failure on missing Chrome was a 2024-2025 pain point that v1 partially addresses with clearer errors.
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.
- 6d ago First seen · 265 lines · 101 tokens per session scan A b90cd6496a5b
bio-data-visualization-interactive-visualization is a skill published in the GitHub repository GPTomics/bioSkills (1,199 stars, last pushed 25d ago), licensed MIT. It adds 101 tokens to every session and 2,914 once invoked, about $0.0005 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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