Agent skill · Security

clinical-variant-reporter

Classify germline variants from VCF/BCF files according to the ACMG/AMP 2015 28-criteria evidence framework and generate clinical-grade interpretation reports with per-variant evidence audit trails and ACMG SF v3.2 secondary findings screening.

BioTender-maxgithub.com/BioTender-maxGitHub ↗
claude-codeships scriptsNOASSERTION
Install
npx skills add BioTender-max/awesome-bio-agent-skills --skill clinical-variant-reporter --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 7
SKILL.md size: 12 KB
Bundled scripts: yes
Version: 0.1.0
Declared author: Reza
Path: skills/clawbio/clinical-variant-reporter/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 135
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# 🏥 Clinical Variant Reporter You are **Clinical Variant Reporter**, a specialised ClawBio agent for guideline-grade germline variant classification. Your role is to apply the ACMG/AMP 2015 28-criteria evidence framework to variants in VCF/BCF files and produce auditable, clinical-grade interpretation reports. ## Why This Exists - **Without it**: Clinicians and researchers must manually evaluate up to 28 evidence criteria per variant across multiple databases (ClinVar, gnomAD, ClinGen, in silico predictors) — a process that takes 15–30 minutes per variant and is error-prone at exome/genome scale - **With it**: A full exome's worth of variants is ACMG-classified in minutes with every evidence decision traceable to its source database, version, and threshold - **Why ClawBio**: The existing `variant-annotation` skill explicitly disclaims ACMG adjudication — it produces annotation tiers, not guideline-grade classifications. This skill fills that gap with formal 28-criteria logic, combining rules, and evidence audit trails grounded in Richards et al. (2015), ClinGen SVI recommendations, and the ACMG SF v3.2 secondary findings list — never ungrounded speculation ## Core Capabilities 1.

What's inside
Steps it walks through
  1. Why This Exists
  2. Core Capabilities
  3. Input Formats
  4. Workflow
  5. CLI Reference
  6. Demo
  7. Algorithm / Methodology
  8. Evidence Criteria Evaluation
  9. Combining Rules
  10. Key Thresholds
  11. Example Queries
  12. Output Structure
  13. Dependencies
  14. Safety
Ships with 6 files
  • acmg_engine.py
  • clinical_variant_reporter.py
  • example_data/demo_evidence_cache.json
  • example_data/giab_acmg_panel.vcf
  • tests/__init__.py
  • tests/test_clinical_variant_reporter.py
Commands it runs
Standard usage — classify variants from a VCF
python skills/clinical-variant-reporter/clinical_variant_reporter.py \
Demo mode (GIAB-derived panel with known pathogenic/benign variants)
Restrict to a gene panel
Via ClawBio runner
python clawbio.py run acmg --input <file> --output <dir>
python clawbio.py run acmg --demo
More from awesome-bio-agent-skills
All skills →
About this skill
What does the clinical-variant-reporter skill do?

Classify germline variants from VCF/BCF files according to the ACMG/AMP 2015 28-criteria evidence framework and generate clinical-grade interpretation reports with per-variant evidence audit trails and ACMG SF v3.2 secondary findings screening.

How do I install it?

Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill clinical-variant-reporter --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going