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 cnv-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/cnv-visualization)<a href="https://agentmods.dev/skills/gptomics/bioskills/cnv-visualization"><img src="https://agentmods.dev/badge/skills/gptomics/bioskills/cnv-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/cnv-visualization"><img src="https://agentmods.dev/badge/skills/gptomics/bioskills/cnv-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 | $0.00130 | $0.03527 |
| Opus 5 | $0.00065 | $0.01764 |
| Sonnet 5 | $0.00026 | $0.00705 |
| Haiku 4.5 | $0.00013 | $0.00353 |
Grade A, and why
bio-copy-number-cnv-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 7d 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-copy-number-cnv-visualization — 97% identical, 12 lines differ
How it starts
The opening of the file, as written. The whole thing — 251 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Version Compatibility
Reference examples tested with: matplotlib 3.8+, pandas 2.2+, numpy 1.26+, seaborn 0.13+, CNVkit 0.9.10+, GATK 4.5+; R 4.3+ with ggplot2 3.5+.
Before using code patterns, verify installed versions match. If versions differ:
- Python:
pip show matplotlib pandasthenhelp(function)for signatures - R:
packageVersion('ggplot2')then?function_name - CLI:
cnvkit.py version,gatk --version
If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example rather than retrying.
CNV Visualization
"Plot my copy number profile" -> A CNV figure is an argument, not a picture. The plot type, the y-axis quantity, and where the diploid baseline sits all determine what the reader can conclude. The single most important rule: a depth-only log2 plot cannot show loss of heterozygosity, cannot show tumor purity, and silently misleads if the diploid baseline is centered on a non-diploid mode.
- CLI:
cnvkit.py scatter/diagram/heatmap;gatk PlotModeledSegments - Python:
matplotlibfor custom genome-wide and allele-specific tracks - R:
ggplot2,karyoploteRfor publication ideograms
Plot Selection — What Each View Reveals and Hides
| Plot | Answers | Reveals | Cannot show |
|---|---|---|---|
| Genome-wide log2 scatter + segments | Where are the gains/losses? | Focal vs broad events, noise level | LOH, purity, allele-specific state |
| Per-chromosome scatter | Is this focal event real and where are its boundaries? | Breakpoints, bin support, weight | Absolute CN without purity |
| BAF / minor-allele-fraction track | Is there allelic imbalance / LOH? | CN-neutral LOH, mirrored imbalance | Total copy number alone |
| Combined log2 + BAF (two-panel) | What is the allele-specific state? | Gains vs CN-LOH vs balanced | — (this is the complete view) |
| Cohort heatmap | What is recurrent across samples? | Shared arm/focal events | Per-sample breakpoint detail |
| Ideogram / diagram | Where do events sit relative to cytobands/genes? | Gene-level context | Quantitative amplitude |
| Circos | Genome-wide CNV + SV breakpoints together | CNV-SV co-localization | Fine amplitude detail |
| Caller-native (GATK/ASCAT/FACETS) | Did the caller fit correctly? | Model fit, segment confidence | — (diagnostic, not publication) |
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.
- 7d ago First seen · 251 lines · 130 tokens per session scan A ffeac9ef0fa0
bio-copy-number-cnv-visualization is a skill published in the GitHub repository GPTomics/bioSkills (1,199 stars, last pushed 26d ago), licensed MIT. It adds 130 tokens to every session and 3,527 once invoked, about $0.0006 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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