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Personalised nutrition report from consumer genetic data (23andMe, AncestryDNA, VCF) — interrogates nutritionally-relevant SNPs and generates actionable dietary guidance, all computed locally.
Install Nutrigx
$ npx skills add ClawBio/ClawBio --skill nutrigx -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install ClawBio/ClawBio nutrigx --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/ClawBio/ClawBio.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/nutrigx .claude/skills/nutrigx && rm -rf skills-srcUse ~/.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/
Install the "nutrigx" agent skill from https://github.com/ClawBio/ClawBio/tree/main/skills/nutrigx into .claude/skills/nutrigx/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nutrigx", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/ClawBio/ClawBio/tree/main/skills/nutrigxType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add ClawBio/ClawBio --skill nutrigx -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install ClawBio/ClawBio nutrigx --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ClawBio/ClawBio.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/nutrigx .agents/skills/nutrigx && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "nutrigx" agent skill from https://github.com/ClawBio/ClawBio/tree/main/skills/nutrigx into .agents/skills/nutrigx/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nutrigx", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add ClawBio/ClawBio --skill nutrigx -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install ClawBio/ClawBio nutrigx --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ClawBio/ClawBio.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/nutrigx .cursor/skills/nutrigx && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "nutrigx" agent skill from https://github.com/ClawBio/ClawBio/tree/main/skills/nutrigx into .cursor/skills/nutrigx/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nutrigx", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/ClawBio/ClawBio.git --path skills/nutrigx--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add ClawBio/ClawBio --skill nutrigx -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install ClawBio/ClawBio nutrigx --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ClawBio/ClawBio.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/nutrigx .gemini/skills/nutrigx && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "nutrigx" agent skill from https://github.com/ClawBio/ClawBio/tree/main/skills/nutrigx into .gemini/skills/nutrigx/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nutrigx", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install ClawBio/ClawBio nutrigxInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add ClawBio/ClawBio --skill nutrigx -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/ClawBio/ClawBio.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/nutrigx .github/skills/nutrigx && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "nutrigx" agent skill from https://github.com/ClawBio/ClawBio/tree/main/skills/nutrigx into .github/skills/nutrigx/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nutrigx", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add ClawBio/ClawBio --skill nutrigx -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install ClawBio/ClawBio nutrigx --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ClawBio/ClawBio.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/nutrigx .opencode/skills/nutrigx && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "nutrigx" agent skill from https://github.com/ClawBio/ClawBio/tree/main/skills/nutrigx into .opencode/skills/nutrigx/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nutrigx", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
nutrigx- GitHub stars
- 1.2k
- Used in
- 1 other repo
- Token cost
- ~3.7k tokens
- SKILL.md length
- 1,366 words
- Files
- 24
- Skills in repo
- 104
- Repo updated
- First seen
- Licence
- MIT
At a glance
Personalised nutrition report from consumer genetic data (23andMe, AncestryDNA, VCF) — interrogates nutritionally-relevant SNPs and generates actionable dietary guidance, all computed locally.
- Works in 5 steps: Input Parsing (parse_input.py) → Genotype Extraction (extract_genotypes.py) → Risk Scoring (score_variants.py) → …
- Tasks that involve Health and fitness tracking
- SKILL.md covers What This Skill Does, Trigger Phrases, Curated SNP Panel and Algorithm, plus 7 more sections
- Runs Python scripts from its folder; calls python
What it does
Nutrigx is an agent skill from ClawBio/ClawBio. Personalised nutrition report from consumer genetic data (23andMe, AncestryDNA, VCF) — interrogates nutritionally-relevant SNPs and generates actionable dietary guidance, all computed locally.
Its SKILL.md is about 3.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 27 other files (for example `api.py`, `data/snp_panel.json` and `examples/generate_patient.py`).
It sits in Productivity & Automation, covering Health and fitness tracking. The repository describes itself as: 🦖 ClawBio - The first bioinformatics-native AI agent skill library. Local-first. Reproducible. Open. Free. The licence is MIT.
When your agent uses it
- Tasks that involve Health and fitness tracking
Example prompts
- “/nutrigx”
Requirements
- Python 3
Workflow steps
5 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 5e045e3. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships script files (Python, from the files we listed), which the agent can run.
Shell commands in SKILL.md call:
python
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
github.com
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
Nutrigx loads about 3.7k tokens when it runs. Until then it costs about 50 tokens; SKILL.md has 1,366 words of instructions outside code blocks.
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 passed
The automated check found no risky patterns in SKILL.md.
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 ClawBio/ClawBio at commit 5e045e3, republished under its MIT licence (© ClawBio). 1,366 words, ~3,684 tokens.
Download SKILL.mdSave it as
.claude/skills/nutrigx/SKILL.md (or your agent's skills folder). This skill also uses 23 other files; get the full folder from GitHub.- name
- nutrigx
- description
- Personalised nutrition report from consumer genetic data (23andMe, AncestryDNA, VCF) — interrogates nutritionally-relevant SNPs and generates actionable dietary guidance, all computed locally.
- license
- MIT
- metadata.version
- 0.2.0
- metadata.author
- David de Lorenzo
- metadata.tags
- nutrigenomics, nutrition, diet, genetics, 23andme, ancestrydna, vcf
NutriGx Advisor — Personalised Nutrition from Genetic Data
Author: David de Lorenzo (ClawBio Community) Requires: Python 3.11+, pandas, numpy, matplotlib, seaborn, reportlab (optional)
What This Skill Does
The NutriGx Advisor generates a personalised nutrition report from consumer genetic data (23andMe, AncestryDNA raw files or VCF). It interrogates a curated set of nutritionally-relevant SNPs drawn from GWAS Catalog, ClinVar, and peer-reviewed nutrigenomics literature, then translates genotype calls into actionable dietary and supplementation guidance — all computed locally.
Key outputs
- Markdown nutrition report with risk scores and recommendations
- Radar chart of nutrient risk profile
- Gene × nutrient heatmap
- Reproducibility bundle (
commands.sh,environment.yml, SHA-256 checksums)
Trigger Phrases
The Bio Orchestrator should route to this skill when the user says anything like:
- "personalised nutrition", "nutrigenomics", "diet genetics"
- "what should I eat based on my DNA"
- "nutrient metabolism", "vitamin absorption genetics"
- "MTHFR", "APOE", "FTO", "BCMO1", "VDR", "FADS1/2"
- "folate", "omega-3", "vitamin D", "caffeine metabolism", "lactose", "gluten"
- Input files:
.txtor.csv(23andMe),.csv(AncestryDNA),.vcf
Curated SNP Panel
Macronutrient Metabolism
| Gene | SNP | Nutrient Impact | Evidence |
|---|---|---|---|
| FTO | rs9939609 | Energy balance, fat mass, carb sensitivity | Strong (GWAS) |
| PPARG | rs1801282 | Fat metabolism, insulin sensitivity | Moderate |
| APOA5 | rs662799 | Triglyceride response to dietary fat | Strong |
| TCF7L2 | rs7903146 | Carbohydrate metabolism, T2D risk | Strong |
| ADRB2 | rs1042713 | Fat oxidation, exercise × diet interaction | Moderate |
Micronutrient Metabolism
| Gene | SNP | Nutrient | Effect of risk allele |
|---|---|---|---|
| MTHFR | rs1801133 | Folate / B12 | ↓ 5-MTHF conversion (~70%) |
| MTHFR | rs1801131 | Folate / B12 | ↓ enzyme activity (~30%) |
| MTR | rs1805087 | B12 / homocysteine | ↑ homocysteine risk |
| BCMO1 | rs7501331 | Beta-carotene → Vitamin A | ↓ conversion (~50%) |
| BCMO1 | rs12934922 | Beta-carotene → Vitamin A | ↓ conversion (compound het) |
| VDR | rs2228570 | Vitamin D absorption | ↓ VDR function |
| VDR | rs731236 | Vitamin D | ↓ bone mineral density response |
| GC | rs4588 | Vitamin D binding | ↑ deficiency risk |
| SLC23A1 | rs33972313 | Vitamin C transport | ↓ renal reabsorption |
| ALPL | rs1256335 | Vitamin B6 | ↓ alkaline phosphatase activity |
Omega-3 / Fatty Acid Metabolism
| Gene | SNP | Nutrient | Effect |
|---|---|---|---|
| FADS1 | rs174546 | LC-PUFA synthesis | ↑/↓ EPA/DHA from ALA |
| FADS2 | rs1535 | LC-PUFA synthesis | Modulates omega-6:omega-3 ratio |
| ELOVL2 | rs953413 | DHA synthesis | A allele: lower EPA→DHA conversion (association, not a requirement) |
| APOE | rs429358 | Saturated fat response | ε4 → ↑ LDL-C on high SFA diet |
| APOE | rs7412 | Saturated fat response | Combined with rs429358 for ε typing |
Caffeine & Alcohol
| Gene | SNP | Compound | Effect |
|---|---|---|---|
| CYP1A2 | rs762551 | Caffeine | Slow/Fast metaboliser |
| AHR | rs4410790 | Caffeine | Modulates CYP1A2 induction |
| ADH1B | rs1229984 | Alcohol | Acetaldehyde accumulation risk |
| ALDH2 | rs671 | Alcohol | Asian flush / toxicity risk |
Food Sensitivities
| Gene | SNP | Sensitivity | Effect |
|---|---|---|---|
| MCM6 | rs4988235 | Lactose intolerance | Risk allele G (GRCh38 plus / -13910C) is non-persistence; persistence allele A (-13910T) is dominant |
| HLA-DQ2 | Proxy SNPs | Coeliac / gluten | HLA-DQA1/DQB1 risk haplotypes |
Antioxidant & Detoxification
| Gene | SNP | Pathway | Effect |
|---|---|---|---|
| SOD2 | rs4880 | Manganese SOD | ↓ mitochondrial antioxidant |
| GPX1 | rs1050450 | Selenium / GSH-Px | ↓ glutathione peroxidase |
| GSTT1 | Deletion | Glutathione-S-trans | Null genotype → ↑ oxidative risk |
| NQO1 | rs1800566 | Coenzyme Q10 | ↓ CoQ10 regeneration |
| COMT | rs4680 | Catechol / B vitamins | Met/Val → methylation load |
Algorithm
1. Input Parsing (parse_input.py)
Accepts:
- 23andMe
.txtor.csv(tab-separated: rsid, chromosome, position, genotype) - AncestryDNA
.csv - Standard VCF (extracts GT field)
Auto-detects format from header lines. Normalises alleles to forward strand using a hard-coded reference table (avoids requiring external databases).
2. Genotype Extraction (extract_genotypes.py)
For each SNP in the panel:
- Look up rsid in parsed data
- Return genotype string (e.g.
"AT","TT","AA") - Flag as
"NOT_TESTED"if absent (common for chip-to-chip variation)
Palindromic SNPs. Three panel SNPs are palindromic, so strand cannot be told from the genotype: rs9939609 (FTO, T/A), rs12934922 (BCMO1, A/T) and rs1801282 (PPARG, C/G). Their calls are read as reported on the plus strand, which is how 23andMe and AncestryDNA export them. A file on the minus strand would score these three the wrong way round without warning.
3. Risk Scoring (score_variants.py)
Each SNP is scored on a 0 / 0.5 / 1.0 scale by default:
0.0— homozygous reference (lowest risk)0.5— heterozygous1.0— homozygous risk allele
Lactose (rs4988235) uses inheritance: dominant_protective. One copy of the
persistence allele is enough, so AA and AG score as persistent (0.0) and only
GG scores as non-persistence (1.0).
Composite Nutrient Risk Scores (0–10) are computed per nutrient domain by summing weighted SNP scores. Weights are derived from reported effect sizes (beta coefficients or OR) in the primary literature.
Risk categories:
- 0–3: Low risk — standard dietary advice applies
- 3–6: Moderate risk — dietary optimisation recommended
- 6–10: Elevated risk — consider testing and targeted supplementation
Important caveat: These are polygenic risk indicators based on common variants. They are not diagnostic. Rare pathogenic variants (e.g. MTHFR compound heterozygosity with high homocysteine) require clinical confirmation.
4. Report Generation (generate_report.py)
Outputs a structured Markdown report with:
- Executive summary (top 3 personalised findings)
- Per-nutrient sections: genotype table → interpretation → recommendation
- Radar chart (matplotlib) of nutrient risk scores
- Gene × nutrient heatmap (seaborn)
- Supplement interactions table
- Disclaimer section
- Reproducibility block
5. Reproducibility Bundle (nutrigx_repro_bundle.py)
Delegates to the shared clawbio.common.reproducibility layer and exports to
<output_dir>/reproducibility/ (not committed to the repo):
commands.sh— full CLI to reproduce analysisenvironment.yml— pinned conda environmentchecksums.sha256— SHA-256 checksums of output files, labelled relative to the output directory (verify withcd <output_dir> && sha256sum -c reproducibility/checksums.sha256); files that fail to generate abort the bundle rather than being silently omittedprovenance.json— timestamp, ClawBio version tag, and SHA-256 checksums of the input file and SNP panel
Show full SKILL.md (535 more words)Show less
Usage
# From 23andMe raw data
openclaw "Generate my personalised nutrition report from genome.csv"
# From VCF
openclaw "Run NutriGx analysis on variants.vcf and flag any folate pathway risks"
# Targeted query
openclaw "What does my APOE status mean for my saturated fat intake?"
# Generate a random demo patient and run the report
python examples/generate_patient.py --runFile Structure
skills/nutrigx/
├── SKILL.md ← this file (agent instructions)
├── nutrigx.py ← main entry point
├── parse_input.py ← multi-format parser
├── extract_genotypes.py ← SNP lookup engine
├── score_variants.py ← risk scoring algorithm
├── generate_report.py ← Markdown + figures
├── nutrigx_repro_bundle.py ← reproducibility export
├── .gitignore
├── data/
│ └── snp_panel.json ← curated SNP definitions
├── tests/
│ ├── synthetic_patient.csv ← fixed 23andMe-format test data (for pytest)
│ ├── test_nutrigx.py ← pytest suite
│ └── test_repro_bundle.py ← reproducibility bundle tests
└── examples/
├── generate_patient.py ← random patient generator (demo use)
├── data/ ← generated patient files land here (gitignored)
└── output/
├── nutrigx_report.md ← pre-rendered demo report
├── nutrigx_radar.png ← demo radar chart (nutrient risk profile)
└── nutrigx_heatmap.png ← demo gene × nutrient heatmapNote: Runtime output directories and randomly generated patient files are excluded from version control via
.gitignore. Only the pre-rendered demo report inexamples/output/is committed.
Privacy
All computation runs locally. No genetic data is transmitted. Input files are read-only; no raw genotype data appears in any output file (reports contain only gene names, SNP IDs, and risk categories).
Limitations & Disclaimer
Symbolic links in the output path are refused. Report, figure and reproducibility files will not be written through a symlink, including a deliberately symlinked output directory; point --output at a real directory. On platforms without O_NOFOLLOW and dir_fd support (such as Windows) the same refusal is made with a less race-proof check.
- Not a medical device. This skill provides educational, research-oriented nutrigenomics analysis. It does not constitute medical advice.
- Common variants only. The panel covers SNPs with MAF > 1% in at least one major population. Rare pathogenic variants are out of scope.
- Population context. Effect sizes are predominantly derived from European GWAS cohorts. Risk estimates may not generalise equally across all ancestries.
- Gene–environment interaction. Genetic risk scores interact with baseline diet, lifestyle, microbiome, and epigenetic state. A "high risk" score does not mean a nutrient deficiency is present — it means the individual may benefit from monitoring.
- Simpson's Paradox note. Population-level associations used to derive weights may not reflect individual trajectories (see Corpas 2025, Nutrigenomics and the Ecological Fallacy).
Roadmap
- v0.2: Microbiome × genotype interaction module (16S rRNA input)
- v0.3: Longitudinal tracking — compare reports across time
- v0.4: HLA typing for immune-mediated food reactions (coeliac, gluten sensitivity)
- v0.5: Integration with NeoTree neonatal data for maternal nutrition risk scoring
- v1.0: Multi-omics integration (metabolomics + genomics + dietary recall)
References
Key literature underpinning the SNP panel and scoring algorithm:
- Corbin JM & Ruczinski I (2023). Nutrigenomics: current state and future directions. Annu Rev Nutr.
- Fenech M et al. (2011). Nutrigenetics and nutrigenomics: viewpoints on the current status. J Nutrigenet Nutrigenomics.
- Stover PJ (2006). Influence of human genetic variation on nutritional requirements. Am J Clin Nutr.
- Phillips CM (2013). Nutrigenetics and metabolic disease: current status and implications for personalised nutrition. Nutrients.
- Minihane AM et al. (2015). APOE genotype, cardiovascular risk and responsiveness to dietary fat manipulation. Proc Nutr Soc.
- Frayling TM et al. (2007). A common variant in the FTO gene is associated with body mass index. Science.
- Pare G et al. (2010). MTHFR variants and cardiovascular risk. Hum Genet.
- Lecerf JM & de Lorgeril M (2011). Dietary cholesterol: from physiology to cardiovascular risk. Br J Nutr.
- Tanaka T et al. (2009). Genome-wide association study of plasma polyunsaturated fatty acids in the InCHIANTI Study. PLoS Genet (FADS1/2; ELOVL2
rs953413, minor A allele with lower DHA). PMID 19148276. - rs953413 regulates polyunsaturated fatty acid metabolism by modulating ELOVL2 expression (2020). iScience (G allele gives higher ELOVL2 enhancer activity than A). PMID 31928966.
- Cornelis MC et al. (2006). Coffee, CYP1A2 genotype, and risk of myocardial infarction. JAMA.
- Enattah NS et al. (2002). Identification of a variant associated with adult-type hypolactasia. Nat Genet 30:233–237. PMID 11788828.
Contributing
The SNP panel (data/snp_panel.json) is maintained by the skill author.
To suggest additions or corrections, contact David de Lorenzo directly via
GitHub (@drdaviddelorenzo) or open
an issue tagging him in the main ClawBio repository.
© ClawBio, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 23 other files in skills/nutrigx of ClawBio/ClawBio.
- SKILL.md
- .gitignore
- api.py
- data/snp_panel.json
- examples/data/.gitkeep
- examples/generate_patient.py
- examples/output/nutrigx_heatmap.png
- examples/output/nutrigx_radar.png
- examples/output/nutrigx_report.md
- extract_genotypes.py
- generate_report.py
- nutrigx.py
- nutrigx_repro_bundle.py
- parse_input.py
- path_safety.py
- score_variants.py
- tests
- … and 7 more
Open the folder on GitHubat commit 5e045e3
Used in 1 other repository
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in ClawBio/ClawBio, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Nutrigx 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
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| Nutrigx this skillClawBio/ClawBio | 1.2k | 1 repos | ~3.7k | Automated safety check: Pass | MIT | |
| Fit Ride Studioop7418/guizang-sports-skill | 147 | — | ~2.8k | Automated safety check: Pass | AGPL-3.0 | |
| Healthkitdpearson2699/swift-ios-skills | 1.2k | — | ~4.2k | Automated safety check: Pass | Custom licence | |
| Withings Health Data Readerwin4r/MuseAI-Skills | 332 | 2 repos | ~1.3k | Automated safety check: Pass | None | |
| RuView Sensing Applicationsruvnet/RuView | 97k | — | ~1.1k | Automated safety check: Notes | MIT | |
| Fitness Analyzerhuifer/WellAlly-health | 961 | 6 repos | ~1.3k | Automated safety check: Pass | MIT |
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Questions about Nutrigx
What does Nutrigx do?
Personalised nutrition report from consumer genetic data (23andMe, AncestryDNA, VCF) — interrogates nutritionally-relevant SNPs and generates actionable dietary guidance, all computed locally. Nutrigx is an agent skill from ClawBio/ClawBio. Personalised nutrition report from consumer genetic data (23andMe, AncestryDNA, VCF) — interrogates nutritionally-relevant SNPs and generates actionable dietary guidance, all computed locally.
When should I use Nutrigx?
Nutrigx fits situations like: tasks that involve Health and fitness tracking.
How do I install Nutrigx in Claude Code?
Run `npx skills add ClawBio/ClawBio --skill nutrigx -a claude-code`. Or copy the skill folder (skills/nutrigx in ClawBio/ClawBio) into .claude/skills/nutrigx in your project. Claude Code loads it when a task matches its description.
How do I install Nutrigx in Codex?
Run `npx skills add ClawBio/ClawBio --skill nutrigx -a codex`. Or copy the skill folder (skills/nutrigx in ClawBio/ClawBio) into .agents/skills/nutrigx in your project. Codex loads it when a task matches its description.
Can I use Nutrigx 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 ClawBio/ClawBio --skill nutrigx -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/nutrigx, .gemini/skills/nutrigx, .github/skills/nutrigx and .opencode/skills/nutrigx in your project.
What does Nutrigx need to run?
Going by SKILL.md and its folder, Nutrigx needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.
Does Nutrigx access the network?
SKILL.md names 1 domain. As links in the text: github.com. This is read from the text; nothing was executed.
Is Nutrigx safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Nutrigx use?
Nutrigx is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Nutrigx use?
About 3.7k tokens (SKILL.md is roughly 15k 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 Nutrigx?
Skills that share tags, products or a category with Nutrigx: Fit Ride Studio (op7418/guizang-sports-skill, 147 stars), Healthkit (dpearson2699/swift-ios-skills, 1.2k stars), Withings Health Data Reader (win4r/MuseAI-Skills, 332 stars) and RuView Sensing Applications (ruvnet/RuView, 97k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Nutrigx?
ClawBio (a GitHub organization) maintains it in ClawBio/ClawBio, which has 1,154 GitHub stars. The repository holds 104 skills in this directory. The repository was last updated on October 7, 2026.
Source: ClawBio/ClawBio on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.