bio-data-visualization-interactive-visualization

A set of methods for creating interactive charts that support actions such as zooming and hovering over data points.

In plain words
What is it for?
Use it to make exploratory plots, interactive differential-expression or volcano plots, notebook visuals, HTML reports, and web dashboards.
Why use it?
Static charts can hide details in large datasets. Interactive HTML plots let people inspect individual values and explore patterns more closely.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/thesecondfox/skill/bio-data-visualization-interactive-visualization
Any agent
npx skills add thesecondfox/skill --skill bio-data-visualization-interactive-visualization
Clone the repo
git clone --depth 1 https://github.com/thesecondfox/skill

Made for: Claude Code, Codex.

Per session 51 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,673 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00051 $0.01673
Opus 5 $0.00026 $0.00837
Sonnet 5 $0.00010 $0.00335
Haiku 4.5 $0.00005 $0.00167

Measured 2d ago against content hash e17e07a6172d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 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.

Common_Skills/bio-data-visualization-interactive-visualization/SKILL.md · 210 lines

How it starts

The opening of the file, as written. The whole thing — 210 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Version Compatibility

Reference examples tested with: ggplot2 3.5+, pandas 2.2+

Before using code patterns, verify installed versions match. If versions differ:

  • Python: pip show <package> then help(module.function) to check signatures
  • R: packageVersion('<pkg>') then ?function_name to verify parameters

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

"Create interactive plots" → Build zoomable, hoverable visualizations for exploring large datasets in notebooks or HTML reports.

  • Python: plotly.express, bokeh, altair
  • R: plotly::ggplotly(), htmlwidgets

plotly (Python)

import plotly.express as px
import plotly.graph_objects as go
import pandas as pd

# Scatter plot
fig = px.scatter(df, x='PC1', y='PC2', color='condition', hover_data=['sample'],
                 title='PCA Plot')
fig.write_html('pca_interactive.html')
fig.show()

Interactive Volcano Plot

Goal: Create a zoomable, hoverable volcano plot for exploring differential expression results.

Approach: Compute significance categories, build a plotly scatter with gene names on hover and metadata tooltips, add threshold reference lines, and export as standalone HTML.

import plotly.express as px

df['neg_log_pval'] = -np.log10(df['pvalue'])
df['significant'] = (df['padj'] < 0.05) & (abs(df['log2FoldChange']) > 1)

fig = px.scatter(df, x='log2FoldChange', y='neg_log_pval',
                 color='significant', hover_name='gene',
                 hover_data=['baseMean', 'padj'],
                 color_discrete_map={True: 'red', False: 'grey'},
                 title='Interactive Volcano Plot')

fig.add_hline(y=-np.log10(0.05), line_dash='dash', line_color='grey')
fig.add_vline(x=-1, line_dash='dash', line_color='grey')
fig.add_vline(x=1, line_dash='dash', line_color='grey')

fig.update_layout(xaxis_title='Log2 Fold Change', yaxis_title='-Log10 P-value')
fig.write_html('volcano_interactive.html')

Read the full file on GitHub · 210 lines

Files

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.

Changes

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.

  1. 2d ago First seen · 210 lines · 51 tokens per session scan A e17e07a6172d

Subscribe to this mod's changes

bio-data-visualization-interactive-visualization is a skill published in the GitHub repository thesecondfox/skill (3 stars, last pushed 5mo ago), licensed MIT. It adds 51 tokens to every session and 1,673 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 2026-08-31.

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