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 ihatesea69/kiro-kit --skill data-visualizationgit clone --depth 1 https://github.com/ihatesea69/kiro-kitWrote 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/ihatesea69/kiro-kit/data-visualization)<a href="https://agentmods.dev/skills/ihatesea69/kiro-kit/data-visualization"><img src="https://agentmods.dev/badge/skills/ihatesea69/kiro-kit/data-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/ihatesea69/kiro-kit/data-visualization"><img src="https://agentmods.dev/badge/skills/ihatesea69/kiro-kit/data-visualization.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00033 | $0.00297 |
| Opus 5.5 | $0.00013 | $0.00119 |
| Sonnet 5.5 | $0.00007 | $0.00059 |
| Haiku 4.5 | $0.00003 | $0.00030 |
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 1mo 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
Data Visualization
Activate this skill when creating charts, plots, or visual data presentations.
When to Use
- Creating exploratory data analysis plots
- Building publication-quality figures
- Designing interactive dashboards
- Communicating model results visually
- Comparing distributions and relationships
Libraries
- matplotlib: Foundation, full control
- seaborn: Statistical visualization, clean defaults
- plotly: Interactive charts, dashboards
- altair: Declarative, grammar of graphics
Patterns
import matplotlib.pyplot as plt
import seaborn as sns
fig, axes = plt.subplots(1, 2, figsize=(12, 5))
sns.histplot(data=df, x="value", hue="category", ax=axes[0])
sns.scatterplot(data=df, x="feature_1", y="target", ax=axes[1])
plt.tight_layout()
plt.savefig("analysis.png", dpi=150, bbox_inches="tight")
Rules
- Always label axes and add titles
- Use colorblind-friendly palettes
- Choose chart type based on data relationship
- Keep visualizations simple and focused
- Save figures at appropriate resolution (150+ DPI)
- Include units in axis labels
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.
- 1mo ago First seen · 47 lines · 33 tokens per session scan A 2ed7ff71bb86
data-visualization is a skill published in the GitHub repository ihatesea69/kiro-kit (19 stars, last pushed 1mo ago), licensed MIT. It adds 33 tokens to every session and 297 once invoked, about $0.0001 per session on Opus 5.5. 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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