bio-viromics

bio-viromics is a skill for Claude Code from fmschulz/omics-skills. It costs 52 tokens per session (2,122 once invoked), scanned A, original, MIT.

A workflow for finding viral DNA fragments in genome assemblies and determining their quality and likely classification.

In plain words
What is it for?
It helps screen contigs, compare evidence across hypotheses, verify reference databases, assess viral genomes, and assign viral groups.
Why use it?
It combines checks for viral completeness, contamination, taxonomy, and alternative technical explanations when results are uncertain.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions AGENTS.md.

Part of the omics-skills plugin — 34 skills, 4 agents shipped together

Good fit It helps screen contigs, compare evidence across hypotheses, verify reference databases, assess viral genomes, and assign viral groups.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/fmschulz/omics-skills/bio-viromics
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.

Any agent
npx skills add fmschulz/omics-skills --skill bio-viromics
Clone the repo
git clone --depth 1 https://github.com/fmschulz/omics-skills

Made for: Claude Code.

Or install omics-skills, the plugin that ships this one along with the rest of its 34 skills, 4 agents.

Wrote 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.

agentmods badge for bio-viromics

README.md
[![agentmods](https://agentmods.dev/badge/skills/fmschulz/omics-skills/bio-viromics/github.svg)](https://agentmods.dev/skills/fmschulz/omics-skills/bio-viromics)
Your own site
<a href="https://agentmods.dev/skills/fmschulz/omics-skills/bio-viromics"><img src="https://agentmods.dev/badge/skills/fmschulz/omics-skills/bio-viromics/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.

agentmods 80×15 button for bio-viromics

Your own site · 80×15
<a href="https://agentmods.dev/skills/fmschulz/omics-skills/bio-viromics"><img src="https://agentmods.dev/badge/skills/fmschulz/omics-skills/bio-viromics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 52 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,122 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 5.1 $0.00052 $0.02122
Opus 5.5 $0.00021 $0.00849
Sonnet 5.5 $0.00010 $0.00424
Haiku 4.5 $0.00005 $0.00212

Measured 23d ago against content hash d6e197275de1, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

bio-viromics 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 23d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/build_viromics_evidence.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/bio-viromics/SKILL.md · 92 lines

How it starts

The opening of the file, as written. The whole thing — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Bio Viromics

Detect, quality-check, and classify viral contigs, then compare each viral genome against a literature-derived reference set.

Instructions

Tool guides, versions, and verified flags: docs/README.md.

Run geNomad, CheckV, GVClass, and vConTACT3 on a workstation or compute node, never on a login node. Pass an explicit thread count to each tool (-t). Without it, geNomad and CheckV use every CPU available to the process, and vConTACT3 uses every CPU on the host, even inside a smaller Slurm allocation. On HPC, submit through sbatch with CPUs matched to that thread count and follow the site's account and partition rules.

  1. Start from /tracking-taxonomy-updates QuickClade domain routing when assemblies, MAGs, genomes, or contigs have not been screened. Viral, virus-like, mixed, or low-confidence contigs enter this skill; bacterial, archaeal, and eukaryotic rows stay on their domain routes unless later evidence contradicts the triage.
  2. Detect viruses with geNomad v1.12.0 (database v1.9) as the primary virus and plasmid classifier: genomad end-to-end -t <n> contigs.fna out/ genomad_db. For prokaryotic-virus discovery, VirSorter2 v2.2.4 is a complementary detector; combine either detector with CheckV QC to remove false positives.
  3. Run CheckV v1.1.1 with database v1.5 for completeness, contamination, and host-region trimming: checkv end_to_end viral.fna out/ -d checkv-db-v1.5 -t <n>.
  4. Infer the likely viral group from QuickClade, geNomad taxonomy, genome statistics, and marker or similarity evidence.
  5. Search the literature for that group (/polars-dovmed) and write analysis_playbook.md: typical reference sets, markers, comparative analyses, genome features, plots, and outlier signals used by people who study the group.
  6. Choose taxonomy, clustering, phylogenetic, and comparative methods from the playbook:
    • Bacteriophages and other prokaryotic viruses: vConTACT3 gene-sharing networks for genus-to-order assignment. vConTACT3 replaces vConTACT2. The upstream source tag is 3.2.4; bioconda ships 3.1.6. Record the version you ran.
    • Nucleocytoviricota, Mirusviricota, and Preplasmiviricota: GVClass v2.0.3 with resource bundle v2.0.0, plus marker-gene phylogenies of core genes through /bio-phylogenomics.
    • RNA viruses, ssDNA viruses, and other groups that vConTACT3 does not cover well: group-specific markers, phylogenomics, and protein-family methods from the playbook. Do not force a phage-oriented workflow on them.
  7. For each viral genome or high-quality viral contig, call genes and annotate proteins when needed (/bio-gene-calling, /bio-annotation), then inspect the annotation set according to the playbook rather than a fixed feature list.
  8. Compare each query to the literature-supported reference set on the comparative axes in the repository AGENTS.md: marker census, per-family copy number, conserved neighborhoods, and ncRNA census. Write marker_census.tsv, family_copy_number_comparison.tsv, conserved_neighborhoods.tsv, and ncRNA_census.tsv to one comparison directory. Report what matches expectations, what is missing, expanded, or query-specific, and which patterns are likely artifacts.
  9. Genome-size frontier: place each query's genome size and gene count in the distribution of close relatives and the literature-reported extremes for the group. State the percentile, the distance from the group median, and whether the query exceeds the known record size, and cite the paper that defines the record. A mid-distribution placement is still a result.
  10. Assemble the evidence bundle. The driver checksum-verifies the geNomad, CheckV, GVClass, and vConTACT3 database resources, checks the hypothesis register and reflections, copies the four comparative tables, and computes genome_size_frontier.tsv:

Read the full file on GitHub · 92 lines

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. 23d ago Changed · +2 lines · +17 tokens per session d6e197275de1
  2. 1mo ago Changed 22da94175213
  3. 1mo ago First seen · 90 lines · 35 tokens per session scan A 3cf083884091

Subscribe to this mod's changes

bio-viromics is a skill published in the GitHub repository fmschulz/omics-skills (11 stars, last pushed 23d ago), licensed MIT. It adds 52 tokens to every session and 2,122 once invoked, about $0.0002 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 2026-08-31.

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