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 PKU-YuanGroup/OpenAI4S --skill bio-copy-number-cnvkit-analysisgit clone --depth 1 https://github.com/PKU-YuanGroup/OpenAI4SWrote 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/pku-yuangroup/openai4s/bio-copy-number-cnvkit-analysis)<a href="https://agentmods.dev/skills/pku-yuangroup/openai4s/bio-copy-number-cnvkit-analysis"><img src="https://agentmods.dev/badge/skills/pku-yuangroup/openai4s/bio-copy-number-cnvkit-analysis/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/pku-yuangroup/openai4s/bio-copy-number-cnvkit-analysis"><img src="https://agentmods.dev/badge/skills/pku-yuangroup/openai4s/bio-copy-number-cnvkit-analysis.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 | $0.00152 | $0.04245 |
| Opus 5 | $0.00076 | $0.02122 |
| Sonnet 5 | $0.00030 | $0.00849 |
| Haiku 4.5 | $0.00015 | $0.00424 |
Grade A, and why
bio-copy-number-cnvkit-analysis 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 9d 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.
This is a copy
91% identical to bio-copy-number-cnvkit-analysis — 14 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 246 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Version Compatibility
Reference examples tested with: CNVkit 0.9.10+, samtools 1.19+, bedtools 2.31+, Python 3.10+, R 4.3+ with DNAcopy 1.76+.
Before using code patterns, verify installed versions match. If versions differ:
- CLI:
cnvkit.py versionthencnvkit.py batch --helpto confirm flags - Python:
pip show cnvkitthenpython3 -c "import cnvlib; help(cnvlib.read)" - R:
packageVersion('DNAcopy')(CBS backend)
If a command throws an unrecognized-argument or AttributeError, introspect the installed version and adapt the example rather than retrying. CNVkit segmentation methods (hmm, hmm-tumor, hmm-germline) depend on pomegranate; CBS depends on Bioconductor DNAcopy.
CNVkit Copy Number Analysis
"Detect copy number variants from my exome / panel data" -> Run a read-depth pipeline: normalize on-target and off-target coverage against a reference, segment the log2-ratio profile, and call gains/losses. CNVkit is a depth-only caller — it estimates relative copy number and cannot, on its own, resolve tumor purity, ploidy, or allele-specific state. Choosing CNVkit is a decision that the experiment does not require allelic resolution.
- CLI:
cnvkit.py batch tumor.bam --normal normal.bam --targets panel.bed --fasta ref.fa - Python API:
cnvlib.read('sample.cnr')for downstream filtering
Where CNVkit Sits — Caller Taxonomy
| Caller | Signal used | Output | Purity/ploidy aware | Fails when |
|---|---|---|---|---|
| CNVkit | Depth (on + off-target) | Relative log2, threshold-called CN | No (manual --purity) |
Sample purity < ~40%; hyper-aneuploid genome breaks median centering; balanced events invisible |
| GATK gCNV / somatic CNV | Depth (PCA/tangent denoised) | Copy-ratio segments, +/-/0 call | No (somatic); ploidy prior (germline) | Recurrent CNV in the PoN normalized away; ModelSegments gives no integer ASCN |
| ASCAT / Sequenza / FACETS | Depth + B-allele frequency | Integer allele-specific CN, purity, ploidy | Yes (jointly fit) | Near-diploid genome cannot anchor purity; low het-SNP density |
| ExomeDepth / GATK gCNV (cohort) | Depth across a cohort | Germline CN genotype | Germline ploidy only | < ~30-100 technically matched samples; common CNV |
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.
- 9d ago First seen · 246 lines · 152 tokens per session scan A cbbc2e664bf9
bio-copy-number-cnvkit-analysis is a skill published in the GitHub repository PKU-YuanGroup/OpenAI4S (407 stars, last pushed yesterday), licensed MIT. It adds 152 tokens to every session and 4,245 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to bio-copy-number-cnvkit-analysis, differing in 14 lines, and is treated as a copy.
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