# Send Variant Annotation to your agent Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually. ## Fast path - Download the package from Yavira. - Extract it into a folder your agent can access. - Paste one of the prompts below and point your agent at the extracted folder. ## Suggested prompts ### New install ```text I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete. ``` ### Upgrade existing ```text I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run. ``` ## Machine-readable fields ```json { "schemaVersion": "1.0", "item": { "slug": "variant-annotation", "name": "Variant Annotation", "source": "tencent", "type": "skill", "category": "开发工具", "sourceUrl": "https://clawhub.ai/AIPOCH-AI/variant-annotation", "canonicalUrl": "https://clawhub.ai/AIPOCH-AI/variant-annotation", "targetPlatform": "OpenClaw" }, "install": { "downloadUrl": "/downloads/variant-annotation", "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=variant-annotation", "sourcePlatform": "tencent", "targetPlatform": "OpenClaw", "packageFormat": "ZIP package", "primaryDoc": "SKILL.md", "includedAssets": [ "requirements.txt", "SKILL.md", "scripts/main.py", "references/acmg-guidelines.md", "references/clinvar-guide.md", "references/example-variants.md" ], "downloadMode": "redirect", "sourceHealth": { "source": "tencent", "slug": "variant-annotation", "status": "healthy", "reason": "direct_download_ok", "recommendedAction": "download", "checkedAt": "2026-05-10T13:25:44.261Z", "expiresAt": "2026-05-17T13:25:44.261Z", "httpStatus": 200, "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=variant-annotation", "contentType": "application/zip", "probeMethod": "head", "details": { "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=variant-annotation", "contentDisposition": "attachment; filename=\"variant-annotation-1.0.0.zip\"", "redirectLocation": null, "bodySnippet": null, "slug": "variant-annotation" }, "scope": "item", "summary": "Item download looks usable.", "detail": "Yavira can redirect you to the upstream package for this item.", "primaryActionLabel": "Download for OpenClaw", "primaryActionHref": "/downloads/variant-annotation" }, "validation": { "installChecklist": [ "Use the Yavira download entry.", "Review SKILL.md after the package is downloaded.", "Confirm the extracted package contains the expected setup assets." ], "postInstallChecks": [ "Confirm the extracted package includes the expected docs or setup files.", "Validate the skill or prompts are available in your target agent workspace.", "Capture any manual follow-up steps the agent could not complete." ] } }, "links": { "detailUrl": "https://openagent3.xyz/skills/variant-annotation", "downloadUrl": "https://openagent3.xyz/downloads/variant-annotation", "agentUrl": "https://openagent3.xyz/skills/variant-annotation/agent", "manifestUrl": "https://openagent3.xyz/skills/variant-annotation/agent.json", "briefUrl": "https://openagent3.xyz/skills/variant-annotation/agent.md" } } ``` ## Documentation ### Variant Annotation Query and interpret gene variant clinical significance from ClinVar and dbSNP databases with ACMG guideline support. ### Purpose Provide comprehensive variant annotation including: Clinical significance classification (Pathogenic, Likely Pathogenic, VUS, Likely Benign, Benign) ACMG guideline-based pathogenicity assessment Population allele frequencies (gnomAD, ExAC, 1000 Genomes) Disease and phenotype associations Functional predictions (SIFT, PolyPhen, CADD) ### Supported Input Formats FormatExampleDescriptionrsIDrs80357410dbSNP reference SNP IDHGVS cDNANM_007294.3:c.5096G>ACoding DNA changeHGVS ProteinNP_009225.1:p.Arg1699GlnProtein changeHGVS GenomicNC_000017.11:g.43094692G>AGenomic coordinateVCF-stylechr17:43094692:G>AChromosome:position:ref>altGene:AABRCA1:R1699QGene with amino acid change ### Python API from scripts.main import VariantAnnotator # Initialize annotator annotator = VariantAnnotator() # Query by rsID result = annotator.query_variant("rs80357410") # Query by HGVS notation result = annotator.query_variant("NM_007294.3:c.5096G>A") # Query by genomic coordinate result = annotator.query_variant("chr17:43094692:G>A") # Batch query results = annotator.batch_query(["rs80357410", "rs28897696", "rs11571658"]) ### Command Line # Single variant query python scripts/main.py --variant rs80357410 # HGVS notation python scripts/main.py --variant "NM_007294.3:c.5096G>A" # Genomic coordinate python scripts/main.py --variant "chr17:43094692:G>A" # Batch from file python scripts/main.py --file variants.txt --output results.json # With output format python scripts/main.py --variant rs80357410 --format json ### Output Format { "variant_id": "rs80357410", "gene": "BRCA1", "chromosome": "17", "position": 43094692, "ref_allele": "G", "alt_allele": "A", "hgvs_genomic": "NC_000017.11:g.43094692G>A", "hgvs_cdna": "NM_007294.3:c.5096G>A", "hgvs_protein": "NP_009225.1:p.Arg1699Gln", "clinical_significance": { "clinvar": "Pathogenic", "acmg_classification": "Pathogenic", "acmg_criteria": ["PS4", "PM1", "PM2", "PP2", "PP3", "PP5"], "acmg_score": 13.0, "review_status": "criteria provided, multiple submitters, no conflicts" }, "disease_associations": [ { "disease": "Breast-ovarian cancer, familial 1", "medgen_id": "C2676676", "significance": "Pathogenic" } ], "population_frequencies": { "gnomAD_genome_all": 0.000008, "gnomAD_exome_all": 0.000012, "1000G_all": 0.0 }, "functional_predictions": { "sift": "deleterious", "polyphen2": "probably_damaging", "cadd_score": 24.5, "mutation_taster": "disease_causing" }, "literature_count": 42, "last_evaluated": "2023-12-15", "interpretation_summary": "This variant (BRCA1 p.Arg1699Gln) is classified as Pathogenic based on ACMG guidelines. It shows strong evidence of pathogenicity including population data (extremely rare), computational predictions (deleterious), and strong clinical significance (established association with hereditary breast-ovarian cancer)." } ### ACMG Classification Criteria The annotator implements the ACMG/AMP guidelines for variant interpretation: ### Pathogenic Evidence (Score) PVS1 (8.0): Null variant in a gene where LOF is known mechanism PS1 (4.0): Same amino acid change as known pathogenic PS2 (4.0): De novo with confirmed paternity/maternity PS3 (4.0): Well-established functional studies show damaging effect PS4 (4.0): Prevalence in affected > controls PM1 (2.0): Located in critical functional domain PM2 (2.0): Absent from controls (MAF <0.0001) PM3 (2.0): AR disorder, detected in trans with pathogenic PM4 (2.0): Protein length changing PM5 (2.0): Novel missense at same position as known pathogenic PM6 (2.0): Assumed de novo without confirmation PP1 (1.0): Cosegregation with disease PP2 (1.0): Missense in gene with low benign rate PP3 (1.0): Multiple computational evidence support PP4 (1.0): Phenotype/patient history matches gene PP5 (1.0): Reputable source reports pathogenic ### Benign Evidence BA1 (-8.0): MAF >5% in population BS1 (-4.0): MAF >expected for disorder BS2 (-4.0): Observed in healthy adult BS3 (-4.0): Functional studies show no damage BS4 (-4.0): Lack of cosegregation BP1 (-1.0): Missense in gene where truncating are pathogenic BP2 (-1.0): Observed in trans with pathogenic BP3 (-1.0): In-frame indel in repetitive region BP4 (-1.0): Multiple computational evidence benign BP5 (-1.0): Alternate cause found BP6 (-1.0): Reputable source reports benign BP7 (-1.0): Synonymous with no splicing impact ### Classification Thresholds ClassificationScore RangePathogenic≥ 10Likely Pathogenic6-9Uncertain Significance0-5Likely Benign-5 to -1Benign≤ -6 ### Technical Difficulty: HIGH ⚠️ AI自主验收状态: 需人工检查 This skill requires: NCBI E-utilities API integration (ClinVar, dbSNP) HGVS notation parsing and validation VCF format handling ACMG guideline implementation Multiple prediction algorithm integration Complex data transformation and scoring ### Data Sources DatabaseData TypeAPI/AccessClinVarClinical significance, disease associationsNCBI E-utilitiesdbSNPSNP data, allele frequenciesNCBI E-utilitiesgnomADPopulation frequenciesgnomAD APIEnsembl VEPFunctional predictionsREST APICADDDeleteriousness scoresREST API ### Limitations Requires internet connection for database queries NCBI API rate limits: 3 requests/second (API key increases to 10/sec) Some variants may not be present in ClinVar (VUS without clinical data) HGVS notation parsing may fail for complex variants Population frequencies not available for all variants Functional predictions are computational estimates only ### References See references/ for: ACMG guidelines publication (Richards et al. 2015) ClinVar documentation HGVS nomenclature guide dbSNP data dictionary Example variant outputs ### Safety & Disclaimer ⚠️ IMPORTANT: This tool is for research and educational purposes only. Variant interpretations are computational predictions and should not be used as the sole basis for clinical decisions. Always consult certified genetic counselors and clinical laboratories for diagnostic purposes. ACMG classifications in this tool are algorithmic estimates and may differ from expert panel reviews. ### Risk Assessment Risk IndicatorAssessmentLevelCode ExecutionPython scripts with toolsHighNetwork AccessExternal API callsHighFile System AccessRead/write dataMediumInstruction TamperingStandard prompt guidelinesLowData ExposureData handled securelyMedium ### Security Checklist No hardcoded credentials or API keys No unauthorized file system access (../) Output does not expose sensitive information Prompt injection protections in place API requests use HTTPS only Input validated against allowed patterns API timeout and retry mechanisms implemented Output directory restricted to workspace Script execution in sandboxed environment Error messages sanitized (no internal paths exposed) Dependencies audited No exposure of internal service architecture ### Prerequisites # Python dependencies pip install -r requirements.txt ### Success Metrics Successfully executes main functionality Output meets quality standards Handles edge cases gracefully Performance is acceptable ### Test Cases Basic Functionality: Standard input → Expected output Edge Case: Invalid input → Graceful error handling Performance: Large dataset → Acceptable processing time ### Lifecycle Status Current Stage: Draft Next Review Date: 2026-03-06 Known Issues: None Planned Improvements: Performance optimization Additional feature support ### Parameters ParameterTypeDefaultDescription--variantstrRequired--filestrRequired--outputstrRequired--formatstr"json"--api-keystrRequiredNCBI API key for increased rate limits--delayfloat0.34 ## Trust - Source: tencent - Verification: Indexed source record - Publisher: AIPOCH-AI - Version: 1.0.0 ## Source health - Status: healthy - Item download looks usable. - Yavira can redirect you to the upstream package for this item. - Health scope: item - Reason: direct_download_ok - Checked at: 2026-05-10T13:25:44.261Z - Expires at: 2026-05-17T13:25:44.261Z - Recommended action: Download for OpenClaw ## Links - [Detail page](https://openagent3.xyz/skills/variant-annotation) - [Send to Agent page](https://openagent3.xyz/skills/variant-annotation/agent) - [JSON manifest](https://openagent3.xyz/skills/variant-annotation/agent.json) - [Markdown brief](https://openagent3.xyz/skills/variant-annotation/agent.md) - [Download page](https://openagent3.xyz/downloads/variant-annotation)