Skill: alex4xu/acmg-variant-classification (version 1.0.0)

--- name: acmg-variant-classification description: Standard workflow for ACMG/AMP germline small-variant classification — collect evidence, assign criteria, detect conflicts, and produce a review-ready classification summary. Use when a user wants a structured ACMG/AMP-style interpretation workflow for a germline SNV/indel, including guided evidence intake, criteria assignment, conflict handling, and provisional classification. --- # ACMG Variant Classification Use this skill when a user wants a structured ACMG/AMP-style interpretation workflow for a germline SNV/indel. ## Interaction mode Default to a guided interview workflow. When using this skill with a live user: 1. Ask for one block of information at a time 2. Wait for the user's answer before moving on 3. Do not request all evidence at once unless the user asks for a bulk template 4. Explicitly track what is known, unknown, and still needed 5. Treat phenotype, family history, segregation data, and parental genotypes as user-supplied inputs that may arrive incrementally Recommended guided sequence: 1. Variant identity: gene, transcript, build, c.HGVS, p.HGVS, variant type 2. Clinical phenotype / suspected disease 3. Inheritance model and family structure 4. Parental genotype status and de novo / segregation details 5. Population / database / literature evidence 6. Functional and computational evidence 7. Criteria assignment and final review At each step, summarize back in one compact block: - confirmed facts - missing facts - provisional ACMG implications ## Safety / scope Always say clearly: - This is decision support, not a final clinical diagnosis. - Gene/disease-specific ClinGen guidance overrides generic ACMG rules where applicable. - Final classification requires expert manual review. ## Inputs you should collect Use templates/intake.md and ask for or normalize these fields: - Gene - Transcript - Genome build - c.HGVS - p.HGVS - Variant type - Zygosity - Inheritance model - Phenotype / disease context - Population frequency evidence - Functional evidence - Segregation / de novo evidence - Database assertions - Literature evidence If transcript, genome build, or HGVS is unclear, stop and ask for clarification before classification. ## Standard workflow ### Step 1: Confirm scope Proceed only if all are true: 1. Variant is a germline small variant (SNV/indel) 2. Naming/build/transcript are defined 3. User understands output is review-only 4. Any gene-specific ACMG framework has been checked ### Step 2: Normalize the record Create a clean variant record using templates/intake.md. ### Step 3: Gather evidence by ACMG bucket Pathogenic side: - PVS1 - PS1, PS2, PS3, PS4 - PM1, PM2, PM3, PM4, PM5, PM6 - PP1, PP2, PP3, PP4 Benign side: - BA1 - BS1, BS2, BS3, BS4 - BP1, BP2, BP3, BP4, BP5, BP7 ### Step 4: Assign criteria carefully Use templates/evidence-table.md. For each criterion, record: - code - strength - triggered yes/no - reason - source - caveat / limitation Do not double count overlapping evidence. ### Step 5: Evaluate conflicts If both pathogenic and benign evidence exist: 1. Check whether evidence is truly independent 2. Downgrade/remove misapplied criteria if needed 3. If conflict remains unresolved, prefer VUS over forced certainty 4. State what additional data could resolve the conflict ### Step 6: Apply combination logic Use scripts/classifier.py or reproduce its logic manually. Pathogenic if any: - 1 Very Strong + >=1 Strong - 1 Very Strong + >=2 Moderate - 1 Very Strong + 1 Moderate + 1 Supporting - 1 Very Strong + >=2 Supporting - >=2 Strong - 1 Strong + >=3 Moderate - 1 Strong + 2 Moderate + >=2 Supporting - 1 Strong + 1 Moderate + >=4 Supporting - >=3 Moderate + >=3 Supporting Likely Pathogenic if any: - 1 Very Strong + 1 Moderate - 1 Strong + 1 to 2 Moderate - 1 Strong + >=2 Supporting - >=3 Moderate - 2 Moderate + >=2 Supporting - 1 Moderate + >=4 Supporting Benign if any: - BA1 - >=2 Strong benign criteria Likely Benign if any: - 1 Strong benign + 1 Supporting benign - >=2 Supporting benign Else: VUS ## Guided questioning pattern Use short, sequential prompts: - Step A: ask only for variant identity fields - Step B: ask only for phenotype and suspected diagnosis - Step C: ask only for pedigree / family history / inheritance - Step D: ask only for parental genotypes and segregation/de novo details - Step E: ask only for outside evidence such as ClinVar, literature, frequency, and functional assays - Step F: summarize triggered or candidate ACMG criteria before giving a provisional class ## Included files - templates/intake.md - templates/evidence-table.md - references/sop.md - references/test_cases.json - scripts/classifier.py


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