Variant AnnotationSAFE
skills/freedomintelligence/variant-annotation
The largest open-source medical AI skills library for OpenClaw🦞.
Verdict
SAFE
Grade
B
Trust score
89 /100
Version
—
Hosts
—
License
—
Stars
3,053
01
Overview
The largest open-source medical AI skills library for OpenClaw🦞.
Read from source at commit
29f31a89230cOBSERVED · 2026-10-0802
What it tells the agent
The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.
<!-- # COPYRIGHT NOTICE # This file is part of the "Universal Biomedical Skills" project. # Copyright (c) 2026 MD BABU MIA, PhD <[email protected]> # All Rights Reserved. # # This code is proprietary and confidential. # Unauthorized copying of this file, via any medium is strictly prohibited. # # Provenance: Authenticated by MD BABU MIA --> --- name: bio-variant-annotation description: Comprehensive variant annotation using bcftools annotate/csq, VEP, SnpEff, and ANNOVAR. Add database annotations, predict functional consequences, and assess clinical significance. Use when annotating variants with functional and clinical information. tool_type: mixed primary_tool: VEP measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- # Variant Annotation ## Tool Comparison | Tool | Best For | Speed | Output | |------|----------|-------|--------| | bcftools csq | Simple consequence prediction | Fast | VCF | | VEP | Comprehensive with plugins | Moderate | VCF/TXT | | SnpEff | Fast batch annotation | Fast | VCF | | ANNOVAR | Flexible databases | Moderate | TXT | ## bcftools annotate ### Add Annotations from Database ```bash bcftools annotate -a dbsnp.vcf.gz -c ID input.vcf.gz -Oz -o annotated.vcf.gz ``` ### Annotation Columns (`-c`) | Option | Description | |--------|-------------| | `ID` | Copy ID column | | `INFO` | Copy all INFO fields | | `INFO/TAG` | Copy specific INFO field | | `+INFO/TAG` | Add to existing values | ### Add rsIDs from dbSNP ```bash bcftools annotate -a dbsnp.vcf.gz -c ID input.vcf.gz -Oz -o with_rsids.vcf.gz ``` ### Add Multiple Annotations ```bash bcftools annotate -a database.vcf.gz -c ID,INFO/AF,INFO/CAF input.vcf.gz -Oz -o annotated.vcf.gz ``` ### Add from BED/TAB Files ```bash # BED with 4th column as annotation bcftools annotate -a regions.bed.gz -c CHROM,FROM,TO,INFO/REGION \ -h <(echo '##INFO=<ID=REGION,Number=1,Type=String,Description="Region name">') \ input.vcf.gz -Oz -o annotated.vcf.gz # Tab file: CHROM POS VALUE bcftools annotate -a annotations.tab.gz -c CHROM,POS,INFO/SCORE \ -h <(echo '##INFO=<ID=SCORE,Number=1,Type=Float,Description="Custom score">') \ input.vcf.gz -Oz -o annotated.vcf.gz ``` ### Remove Annotations ```bash bcftools annotate -x INFO/DP,INFO/MQ input.vcf.gz -Oz -o clean.vcf.gz bcftools annotate -x INFO input.vcf.gz -Oz -o minimal.vcf.gz # Remove all INFO ``` ### Set ID from Fields ```bash bcftools annotate --set-id '%CHROM\_%POS\_%REF\_%ALT' input.vcf.gz -Oz -o with_ids.vcf.gz ``` ## bcftools csq Simple consequence prediction using GFF annotation. ```bash bcftools csq -f reference.fa -g genes.gff3.gz input.vcf.gz -Oz -o consequences.vcf.gz ``` ### Consequence Types | Consequence | Description | |-------------|-------------| | `synonymous` | No amino acid change | | `missense` | Amino acid change | | `stop_gained` | Introduces stop codon | | `frameshift` | Changes reading frame | | `splice_donor/acceptor` | Affects splicing | ## Ensembl VEP ### Installation ```bash conda install -c bioconda ensembl-vep vep_install -a cf -s homo_sapiens -y GRCh38 --CONVERT ``` ### Basic Annotation ```bash vep -i input.vcf -o output.vcf --vcf --cache --offline ``` ### Comprehensive Annotation ```bash vep -i input.vcf -o output.vcf \ --vcf \ --cache --offline \ --species homo_sapiens \ --assembly GRCh38 \ --everything \ --fork 4 ``` ### --everything Enables - `--sift b` - SIFT predictions - `--polyphen b` - PolyPhen predictions - `--hgvs` - HGVS nomenclature - `--symbol` - Gene symbols - `--canonical` - Canonical transcript - `--af` - 1000 Genomes frequencies - `--af_gnomade/g` - gnomAD frequencies - `--pubmed` - PubMed IDs ### Filter by Impact ```bash vep -i input.vcf -o output.vcf --vcf \ --cache --offline \ --pick \ --filter "IMPACT in HIGH,MODERATE" ``` ### Plugins ```bash # CADD scores vep -i input.vcf -o output.vcf --vcf \ --cache --offline \ --plugin CADD,whole_genome_SNVs.tsv.gz # dbNSFP (multiple predictors) vep -i input.vcf -o output.vcf --vcf \ --cache --offline \ --plugin dbNSFP,dbNSFP4.3a.gz,ALL # Multiple plugins vep -i input.vcf -o output.vcf --vcf \ --cache --offline \ --plugin CADD,cadd.tsv.gz \ --plugin dbNSFP,dbnsfp.gz,SIFT_score,Polyphen2_HDIV_score \ --plugin SpliceAI,spliceai.vcf.gz ``` ### VEP Output Fields | Field | Description | |-------|-------------| | Consequence | SO term (e.g., missense_variant) | | IMPACT | HIGH, MODERATE, LOW, MODIFIER | | SYMBOL | Gene symbol | | HGVSc/HGVSp | HGVS coding/protein change | | SIFT/PolyPhen | Pathogenicity predictions | ## SnpEff ### Installation ```bash conda install -c bioconda snpeff snpEff download GRCh38.105 ``` ### Basic Annotation ```bash snpEff ann GRCh38.105 input.vcf > output.vcf ``` ### With Statistics ```bash snpEff ann -v -stats stats.html -csvStats stats.csv GRCh38.105 input.vcf > output.vcf ``` ### Filter by Impact ```bash snpEff ann GRCh38.105 input.vcf | \ SnpSift filter "(ANN[*].IMPACT = 'HIGH')" > high_impact.vcf ``` ### SnpEff Impact Categories | Impact | Examples | |--------|----------| | HIGH | Stop gained, frameshift, splice donor/acceptor | | MODERATE | Missense, inframe indel | | LOW | Synonymous, splice region | | MODIFIER | Intron, intergenic, UTR | ### SnpSift Database Annotations ```bash # dbSNP SnpSift annotate dbsnp.vcf.gz input.vcf > annotated.vcf # ClinVar SnpSift annotate clinvar.vcf.gz input.vcf > annotated.vcf # dbNSFP SnpSift dbnsfp -db dbNSFP4.3a.txt.gz input.vcf > annotated.vcf # Chain multiple snpEff ann GRCh38.105 input.vcf | \ SnpSift annotate dbsnp.vcf.gz | \ SnpSift annotate clinvar.vcf.gz > fully_annotated.vcf ``` ### SnpSift Filtering ```bash SnpSift filter "(QUAL >= 30) & (DP >= 10)" input.vcf > filtered.vcf SnpSift filter "(exists CLNSIG) & (CLNSIG has 'Pathogenic')" input.vcf > pathogenic.vcf ``` ## ANNOVAR
03
Trust audit
SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | PASS |
| L1 | Static analysis of the code | PASS |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (sandbox) | SKIPPED |
What the source does
- Filesystem
- none-observed
- Network
- none-observed
- Shell
- none-observed
- Dependencies
- pinned
- Secrets in source
- none-found
Findings (1)
LOWInventory / provenance · skill.no_frontmatter · CWE-1104
SKILL.md:1
Why it matters. SKILL.md lacks name/description frontmatter
Gates applied: no_behavioural_pass.
Audited 2026-10-08 · audit v0.4.1 · source sha
29f31a89230cfull audit observations/trust-audit/skill/freedomintelligence__variant-annotation.json · Report an issue / request a re-scan04
Audit history
Every audit this skill has had.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-10-08 | 29f31a89230c | SAFE | B | 89 | first audit |
05
Questions
What does the Variant Annotation skill do?
The largest open-source medical AI skills library for OpenClaw🦞.
Is Variant Annotation safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can Variant Annotation access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
How current is this page?
The grade is for one exact copy of the source (29f31a89230c), read on 2026-10-08. The repository is watched, and a new audit runs when it changes — this is the first audit.