Recombinator

Skill BioTender-max/awesome-bio-agent-skills/skills/clawbio/recombinator

Produce offspring genomes from parent pairs via meiotic recombination, mutation, and clinical evaluationFrom its SKILL.md

Install

npx -y skills add BioTender-max/awesome-bio-agent-skills --skill recombinator

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.

What its file declares

Copied from the file, not written here

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

2.5 KB, 515 tokens by cl100k_base, as published. Nobody here has run it

🧪 Recombinator

Purpose

Produce offspring genomes from selected parent pairs via simulated meiotic recombination. Models Mendelian segregation, de novo mutation, sex determination, and clinical evaluation against a disease registry.

How It Works

Mendelian segregation: one allele inherited from each parent per locus (random selection simulating independent assortment).
De novo mutation: configurable rate per locus (default 0.1%), with hotspot multipliers for cognitive, immune, and metabolic loci. Mutations are classified as disease-risk, protective, or neutral.
Sex determination: 50/50 coin flip (XY or XX).
Trait inference: reverse-map offspring genotype back to trait scores using the trait registry, accounting for dominance models.
Clinical evaluation: check offspring genotype against disease registry for penetrance, onset probability, and fitness cost.
Health score: computed from cumulative fitness costs of clinical conditions.

Input

Two parent .genome.json files (one Male, one Female)
GENOMEBOOK/DATA/trait_registry.json
GENOMEBOOK/DATA/disease_registry.json

Output

Offspring .genome.json with:
- Inherited loci and alleles
- Mutation log
- Inferred trait scores
- Clinical history
- Health score (0.0 to 1.0)

CLI Usage

# Demo: breed Einstein x Anning, produce 3 offspring
python skills/recombinator/recombinator.py --demo

# Breed specific parents
python skills/recombinator/recombinator.py \
  --father einstein-g0 --mother anning-g0 --offspring 3

# Custom generation number
python skills/recombinator/recombinator.py \
  --father einstein-g0 --mother curie-g0 --offspring 2 --generation 1

Output Format

ID:     g1-001-a3f2c1
Sex:    Female (XX)
Health: 0.9500
Mutations: 1
  - COMT_Val158Met: G->A (neutral, from mother)
Conditions: 0
Top traits:
  - curiosity: 0.92
  - analytical_thinking: 0.88
  - persistence: 0.85

What ships with it: 1 file

4.8 KB alongside SKILL.md, 1 of them executable

recombinator.pyruns4.8 KB