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Agent skill

Personal Genomics

by sammcj in sammcj/agentic-coding

Analyse personal DNA / genome files for pharmacogenomics, disease risk, carrier status, ancestry and traits.

Apache-2.0Auto-check: notesResearch & Science

Install Personal Genomics

skills CLI
$ npx skills add sammcj/agentic-coding --skill personal-genomics -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install sammcj/agentic-coding personal-genomics --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/sammcj/agentic-coding.git skills-src && mkdir -p .claude/skills && cp -r skills-src/Skills_disabled/personal-genomics .claude/skills/personal-genomics && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
personal-genomics
GitHub stars
162
Token cost
~1.4k tokens
SKILL.md length
614 words
Files
1
Skills in repo
64
Repo updated
First seen
Licence
Apache-2.0

At a glance

Analyse personal DNA / genome files for pharmacogenomics, disease risk, carrier status, ancestry and traits.

  • Works in 3 steps: critical_alerts - state each gene,… → high_priority - pharmacogenomics and… → A short read of polygenic_risk_scores…
  • The user mentions DNA
  • SKILL.md covers First: track the workflow, Locate the toolkit, Locate the input files and Choose single-source or combined, plus 2 more sections
  • Calls python, python3 and pip

What it does

Personal Genomics is an agent skill from sammcj/agentic-coding. Analyse personal DNA / genome files for pharmacogenomics, disease risk, carrier status, ancestry and traits. Use whenever the user mentions DNA or genome analysis, a raw genome file, gene names, drug-gene interactions, or wants to combine multiple DNA sources.

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Research & Science, covering Bioinformatics. The repository describes itself as: Agentic Coding Rules, Templates etc... The licence is Apache-2.0.

When your agent uses it

  • The user mentions DNA
  • Genome analysis
  • A raw genome file
  • Drug-gene interactions

Example prompts

  • “/personal-genomics”

Requirements

  • Python 3
  • Pre-approved tools (allowed-tools): Bash, Read, Glob, SendUserFile

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. critical_alerts - state each gene, genotype, and the recommended action verbatim.
  2. high_priority - pharmacogenomics and actionable risk items.
  3. A short read of polygenic_risk_scores (these are percentile ranges with confidence, not verdicts) and apoe_status.

What it can do on your machine

Read from SKILL.md and the folder at commit 2f25ced. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Bash
    • Read
    • Glob
    • SendUserFile

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • python
    • python3
    • pip

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use pip, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Personal Genomics loads about 1.4k tokens when it runs. Until then it costs about 70 tokens; SKILL.md has 614 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~70
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Bash, Read, Glob, SendUserFile

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from sammcj/agentic-coding at commit 2f25ced, republished under its Apache-2.0 licence (© sammcj). 614 words, ~1,352 tokens.

Download SKILL.mdSave it as .claude/skills/personal-genomics/SKILL.md (or your agent's skills folder).
name
personal-genomics
description
Analyse personal DNA / genome files for pharmacogenomics, disease risk, carrier status, ancestry and traits. Use whenever the user mentions DNA or genome analysis, a raw genome file, gene names, drug-gene interactions, or wants to combine multiple DNA sources.
allowed-tools
Bash, Read, Glob, SendUserFile
disable-agent-invocation
true

Personal Genomics

Runs the local personal-genomics toolkit over one or more raw DNA files and reports the findings. All analysis is offline; genetic data never leaves the machine.

First: track the workflow

Create a task for each step below, then work them to completion. The run is multi-step and the reporting step (surfacing findings safely) is the one most often skipped once the analysis file is written.

Locate the toolkit

The scripts and their virtualenv live at ~/git/personal-genomics (a .venv/ with pandas/numpy/scipy/reportlab). Use that venv's Python: ~/git/personal-genomics/.venv/bin/python.

If the repo or venv is missing, set it up before analysing:

bash
cd ~/git/personal-genomics && python3 -m venv .venv && .venv/bin/pip install -r requirements.txt

If the toolkit lives elsewhere, ask the user for the path rather than guessing.

Locate the input files

Ask the user where their DNA file(s) are if not already given. Common location is ~/Downloads/DNA/. Supported inputs:

  • Array exports: 23andMe, AncestryDNA, MyHeritage, FTDNA (tab-delimited rsid text)
  • Sequencing: .vcf / .vcf.gz (whole genome or exome)

A .cram.crai on its own is not usable (it is only an index; the alignment data is in the .cram it points to). See Gotchas for what to do when the .cram itself is available.

Choose single-source or combined

One file -> comprehensive_analysis.py:

bash
~/git/personal-genomics/.venv/bin/python ~/git/personal-genomics/comprehensive_analysis.py <file> --out <dir>

Two or more files -> combine_sources.py, which merges them first:

bash
~/git/personal-genomics/.venv/bin/python ~/git/personal-genomics/combine_sources.py <file1> <file2> ... --out <dir>

Always merge when more than one source exists. A variants-only VCF (the usual WGS export) lists only sites where the person differs from the reference, so every homozygous-reference site is absent. The marker analysis treats an absent rsID as "not tested" and skips it, which makes a rich WGS file yield fewer findings than an array on its own. Merging restores the array's reference/normal calls and keeps the WGS's rare variants, producing a strict superset. The combiner resolves contested sites to the sequencing call and writes merge_stats.json recording overlap, agreement, and strand-flip counts.

Outputs land in <dir> (suggest ~/dna-analysis/reports for single, ~/dna-analysis/reports-combined for merged): agent_summary.json, full_analysis.json, report.txt, dashboard.html.

Report the findings

Read agent_summary.json (it is priority-sorted) - not full_analysis.json, and never echo the raw genotype data. Surface, in order:

  1. critical_alerts - state each gene, genotype, and the recommended action verbatim.
  2. high_priority - pharmacogenomics and actionable risk items.
  3. A short read of polygenic_risk_scores (these are percentile ranges with confidence, not verdicts) and apoe_status.

Then offer the dashboard with SendUserFile (display: render).

Frame results as informational, not diagnostic. Recommend confirmatory clinical-grade testing and genetic counselling for any pathogenic hereditary-cancer variant, critical pharmacogenomic finding (e.g. DPYD, MT-RNR1, HLA-B risk alleles), APOE e4/e4, or carrier status with reproductive implications.

Show full SKILL.md (218 more words)Show less

Gotchas

  • Output directory write: the tool writes to ~/dna-analysis/ by default, outside a sandboxed working tree. If the run fails with "Operation not permitted", re-run with filesystem write access (this is the user's own data on their own machine).

  • rsID matching is build-agnostic: markers match by rsID, not position, so hg19 array data and hg38 WGS combine without liftover.

  • Strand flips: ~0.1% of overlapping sites disagree purely by strand (A/T vs complement); the combiner detects these and resolves to the sequencing call. A non-trivial count of real conflicts in merge_stats.json is worth flagging to the user.

  • CRAM, when available: the .cram (not the .crai index alone) holds the aligned reads, so marker positions can be genotyped directly — giving true hom-ref calls even at sites neither the array nor a variants-only VCF covered. Scripts live in cram/. Needs an hg38 reference FASTA matching the CRAM's contigs (the one it was aligned to) and samtools/bcftools/tabix. The marker sites file (cram/marker_sites_hg38.vcf.gz) is prebuilt; rebuild it with cram/build_targets.py only if markers change. Run:

    bash
    ~/git/personal-genomics/.venv/bin/python ~/git/personal-genomics/cram/genotype_cram.py \
  --cram <file.cram> --reference <hg38.fa> \
  --analyze --combine-with <array.txt> <genome.vcf.gz>

    This calls genotypes at the marker sites, merges them with the other sources, and writes a combined report to ~/dna-analysis/reports-cram.

  • Empty nutrition_insights / fitness_insights or a duplicated marker row are known quirks of the upstream tool, not data problems.

© sammcj, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in Skills_disabled/personal-genomics of sammcj/agentic-coding.

Open the folder on GitHubat commit 2f25ced

Compare with similar skills

Personal Genomics next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Personal Genomics compared with similar skills
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Personal Genomics this skillsammcj/agentic-coding162—~1.4kAutomated safety check: NotesApache-2.0
Alphagenome Single Variant Analysisgoogle-deepmind/science-skills3.2k2 repos~3kAutomated safety check: NotesApache-2.0
13C Metabolic Flux AnalysisK-Dense-AI/scientific-agent-skills48k1 repos~3.2kAutomated safety check: PassMIT
Clinvar Databasegoogle-deepmind/science-skills3.2k2 repos~3.9kAutomated safety check: NotesApache-2.0
Metabolic Study Planneraiming-lab/AutoResearchClaw15k—~1.9kAutomated safety check: PassMIT
Dbsnp Databasegoogle-deepmind/science-skills3.2k2 repos~3.4kAutomated safety check: NotesApache-2.0

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Categories

Questions about Personal Genomics

What does Personal Genomics do?

Analyse personal DNA / genome files for pharmacogenomics, disease risk, carrier status, ancestry and traits. Personal Genomics is an agent skill from sammcj/agentic-coding. Analyse personal DNA / genome files for pharmacogenomics, disease risk, carrier status, ancestry and traits.

When should I use Personal Genomics?

Personal Genomics fits situations like: the user mentions DNA; genome analysis; A raw genome file; drug-gene interactions.

How do I install Personal Genomics in Claude Code?

Run `npx skills add sammcj/agentic-coding --skill personal-genomics -a claude-code`. Or copy the skill folder (Skills_disabled/personal-genomics in sammcj/agentic-coding) into .claude/skills/personal-genomics in your project. Claude Code loads it when a task matches its description.

How do I install Personal Genomics in Codex?

Run `npx skills add sammcj/agentic-coding --skill personal-genomics -a codex`. Or copy the skill folder (Skills_disabled/personal-genomics in sammcj/agentic-coding) into .agents/skills/personal-genomics in your project. Codex loads it when a task matches its description.

Can I use Personal Genomics in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add sammcj/agentic-coding --skill personal-genomics -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/personal-genomics, .gemini/skills/personal-genomics, .github/skills/personal-genomics and .opencode/skills/personal-genomics in your project.

What does Personal Genomics need to run?

Going by SKILL.md and its folder, Personal Genomics needs the command-line tools its instructions call (python, python3 and pip). Our summary lists: Python 3. Its frontmatter pre-approves these tools: Bash, Read, Glob, SendUserFile.

Does Personal Genomics access the network?

SKILL.md contains no URLs. Its commands use pip, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Personal Genomics safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Personal Genomics use?

Personal Genomics is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Personal Genomics use?

About 1.4k tokens (SKILL.md is roughly 5.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Personal Genomics?

Skills that share tags, products or a category with Personal Genomics: Alphagenome Single Variant Analysis (google-deepmind/science-skills, 3.2k stars), 13C Metabolic Flux Analysis (K-Dense-AI/scientific-agent-skills, 48k stars), Clinvar Database (google-deepmind/science-skills, 3.2k stars) and Metabolic Study Planner (aiming-lab/AutoResearchClaw, 15k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Personal Genomics?

sammcj (a GitHub user) maintains it in sammcj/agentic-coding, which has 162 GitHub stars. The repository holds 64 skills in this directory. The repository was last updated on October 9, 2026.

Source: sammcj/agentic-coding on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.