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 pileup-generationgit 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/pileup-generation)<a href="https://agentmods.dev/skills/gptomics/bioskills/pileup-generation"><img src="https://agentmods.dev/badge/skills/gptomics/bioskills/pileup-generation/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/pileup-generation"><img src="https://agentmods.dev/badge/skills/gptomics/bioskills/pileup-generation.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 | $0.00042 | $0.04027 |
| Opus 5 | $0.00021 | $0.02014 |
| Sonnet 5 | $0.00008 | $0.00805 |
| Haiku 4.5 | $0.00004 | $0.00403 |
Grade A, and why
bio-pileup-generation scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
ref_base = ref.fetch(chrom, pos, pos + 1) Copies of this mod
1 near-identical copy found in the catalogue:
- bio-pileup-generation — 97% identical, 12 lines differ
How it starts
The opening of the file, as written. The whole thing — 375 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Version Compatibility
Reference examples tested with: bcftools 1.19+, pysam 0.22+, samtools 1.19+
Before using code patterns, verify installed versions match. If versions differ:
- Python:
pip show <package>thenhelp(module.function)to check signatures - CLI:
<tool> --versionthen<tool> --helpto confirm flags
If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.
Pileup Generation
Generate pileup data for variant calling and position-level analysis.
"Generate pileup from BAM" -> Produce per-position read summaries showing depth, bases, and qualities.
- CLI:
samtools mpileup -f ref.fa input.bam - Python:
bam.pileup(chrom, start, end)(pysam)
"Count alleles at a position" -> Extract per-base read support at a specific genomic coordinate.
- Python: iterate
pileup_column.pileupsand count bases (pysam)
What is Pileup?
Pileup shows all reads covering each position in the reference, used for:
- Variant calling (with bcftools)
- Coverage analysis
- Allele frequency calculation
- SNP/indel detection
samtools mpileup vs bcftools mpileup (Deprecation)
samtools mpileup -g/-u (BCF output for variant calling) was deprecated in samtools 1.9 and removed in 1.15 (the option no longer exists; the usage/manpage directs users to bcftools mpileup) -- the genotype-likelihood code now lives in bcftools mpileup, which keeps mpileup logic versioned alongside bcftools call and avoids version-skew bugs.
| Use case | Recommended tool |
|---|---|
| Quick allele counts at known sites | samtools mpileup or pysam pileup |
| Germline variant calling (small genomes, simple cohorts) | bcftools mpileup -> bcftools call |
| Germline WGS / WES production | DeepVariant or HaplotypeCaller (not mpileup) |
| Somatic SNV/indel | Mutect2 / VarDict / VarScan2 (direct from BAM) |
| Long-read small variants | clair3 / DeepVariant ONT (direct from BAM) |
| Long-read SV | Sniffles / cuteSV (direct from BAM) |
| Ultra-low-frequency (ctDNA / MRD) | fgbio consensus -> bcftools call or hot-spot Mutect2 |
| Per-position allele counts (custom) | pysam pileup |
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 · 375 lines · 42 tokens per session scan A f45c0e280cd4
bio-pileup-generation is a skill published in the GitHub repository GPTomics/bioSkills (1,199 stars, last pushed 24d ago), licensed MIT. It adds 42 tokens to every session and 4,027 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
instrument-data-to-allotrope
Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full…
exploratory-data-analysis
Perform bounded, local exploratory analysis of explicitly supported scientific files. Use for redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain…
matlab
Build, review, migrate, and safely plan MATLAB or GNU Octave numerical workflows, including arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.
phylogenetics
Build and analyze phylogenetic trees using MAFFT (multiple alignment), IQ-TREE 2 (maximum likelihood), and FastTree (fast NJ/ML). Visualize with ETE3 or FigTree. For evolutionary analysis, microbial genomics, viral phylodynamics, protein family analysis, and molecular clock studies.
research-engineer
An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.
mapping-to-snomed
Maps clinical concept spans extracted by OpenMed to SNOMED CT concepts through a USER-SUPPLIED terminology server (the user's own Ontoserver, Snowstorm, or UMLS/UTS), never a bundled vocabulary. Use when the user wants to code findings, disorders, procedures, body structures, or substances to SNOMED CT, run an ECL…