{
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  "item": {
    "slug": "personal-genomics",
    "name": "Personal Genomics",
    "source": "tencent",
    "type": "skill",
    "category": "数据分析",
    "sourceUrl": "https://clawhub.ai/wkyleg/personal-genomics",
    "canonicalUrl": "https://clawhub.ai/wkyleg/personal-genomics",
    "targetPlatform": "OpenClaw"
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  "install": {
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    "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=personal-genomics",
    "sourcePlatform": "tencent",
    "targetPlatform": "OpenClaw",
    "installMethod": "Manual import",
    "extraction": "Extract archive",
    "prerequisites": [
      "OpenClaw"
    ],
    "packageFormat": "ZIP package",
    "includedAssets": [
      "CHANGELOG.md",
      "README.md",
      "SECURITY.md",
      "SKILL.md",
      "advanced_analysis.py",
      "analyze_dna.py"
    ],
    "primaryDoc": "SKILL.md",
    "quickSetup": [
      "Download the package from Yavira.",
      "Extract the archive and review SKILL.md first.",
      "Import or place the package into your OpenClaw setup."
    ],
    "agentAssist": {
      "summary": "Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.",
      "steps": [
        "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."
      ],
      "prompts": [
        {
          "label": "New install",
          "body": "I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete."
        },
        {
          "label": "Upgrade existing",
          "body": "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. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run."
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      "checkedAt": "2026-04-23T16:43:11.935Z",
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      "httpStatus": 200,
      "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=4claw-imageboard",
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      "summary": "Source download looks usable.",
      "detail": "Yavira can redirect you to the upstream package for this source.",
      "primaryActionLabel": "Download for OpenClaw",
      "primaryActionHref": "/downloads/personal-genomics"
    },
    "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."
      ]
    },
    "downloadPageUrl": "https://openagent3.xyz/downloads/personal-genomics",
    "agentPageUrl": "https://openagent3.xyz/skills/personal-genomics/agent",
    "manifestUrl": "https://openagent3.xyz/skills/personal-genomics/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/personal-genomics/agent.md"
  },
  "agentAssist": {
    "summary": "Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.",
    "steps": [
      "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."
    ],
    "prompts": [
      {
        "label": "New install",
        "body": "I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete."
      },
      {
        "label": "Upgrade existing",
        "body": "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. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run."
      }
    ]
  },
  "documentation": {
    "source": "clawhub",
    "primaryDoc": "SKILL.md",
    "sections": [
      {
        "title": "Personal Genomics Skill v4.2.0",
        "body": "Comprehensive local DNA analysis with 1600+ markers across 30 categories. Privacy-first genetic analysis for AI agents."
      },
      {
        "title": "Quick Start",
        "body": "python comprehensive_analysis.py /path/to/dna_file.txt"
      },
      {
        "title": "Triggers",
        "body": "Activate this skill when user mentions:\n\nDNA analysis, genetic analysis, genome analysis\n23andMe, AncestryDNA, MyHeritage results\nPharmacogenomics, drug-gene interactions\nMedication interactions, drug safety\nGenetic risk, disease risk, health risk\nCarrier status, carrier testing\nVCF file analysis\nAPOE, MTHFR, CYP2D6, BRCA, or other gene names\nPolygenic risk scores\nHaplogroups, maternal lineage, paternal lineage\nAncestry composition, ethnicity\nHereditary cancer, Lynch syndrome\nAutoimmune genetics, HLA, celiac\nPain sensitivity, opioid response\nSleep optimization, chronotype, caffeine metabolism\nDietary genetics, lactose intolerance, celiac\nAthletic genetics, sports performance\nUV sensitivity, skin type, melanoma risk\nTelomere length, longevity genetics"
      },
      {
        "title": "Supported Files",
        "body": "23andMe, AncestryDNA, MyHeritage, FTDNA\nVCF files (whole genome/exome, .vcf or .vcf.gz)\nAny tab-delimited rsid format"
      },
      {
        "title": "Output Location",
        "body": "~/dna-analysis/reports/\n\nagent_summary.json - AI-optimized, priority-sorted\nfull_analysis.json - Complete data\nreport.txt - Human-readable\ngenetic_report.pdf - Professional PDF report"
      },
      {
        "title": "Haplogroup Analysis",
        "body": "Mitochondrial DNA (mtDNA) - maternal lineage\nY-chromosome - paternal lineage (males only)\nMigration history context\nPhyloTree/ISOGG standards"
      },
      {
        "title": "Ancestry Composition",
        "body": "Population comparisons (EUR, AFR, EAS, SAS, AMR)\nAdmixture detection\nAncestry informative markers"
      },
      {
        "title": "Hereditary Cancer Panel",
        "body": "BRCA1/BRCA2 comprehensive\nLynch syndrome (MLH1, MSH2, MSH6, PMS2)\nOther genes (APC, TP53, CHEK2, PALB2, ATM)\nACMG-style classification"
      },
      {
        "title": "Autoimmune HLA",
        "body": "Celiac (DQ2/DQ8) - can rule out if negative\nType 1 Diabetes\nAnkylosing spondylitis (HLA-B27)\nRheumatoid arthritis, lupus, MS"
      },
      {
        "title": "Pain Sensitivity",
        "body": "COMT Val158Met\nOPRM1 opioid receptor\nSCN9A pain signaling\nTRPV1 capsaicin sensitivity\nMigraine susceptibility"
      },
      {
        "title": "PDF Reports",
        "body": "Professional format\nPhysician-shareable\nExecutive summary\nDetailed findings\nDisclaimers included"
      },
      {
        "title": "Medication Interaction Checker",
        "body": "from markers.medication_interactions import check_medication_interactions\n\nresult = check_medication_interactions(\n    medications=[\"warfarin\", \"clopidogrel\", \"omeprazole\"],\n    genotypes=user_genotypes\n)\n# Returns critical/serious/moderate interactions with alternatives\n\nAccepts brand or generic names\nCPIC guidelines integrated\nPubMed citations included\nFDA warning flags"
      },
      {
        "title": "Sleep Optimization Profile",
        "body": "from markers.sleep_optimization import generate_sleep_profile\n\nprofile = generate_sleep_profile(genotypes)\n# Returns ideal wake/sleep times, coffee cutoff, etc.\n\nChronotype (morning/evening preference)\nCaffeine metabolism speed\nPersonalized timing recommendations"
      },
      {
        "title": "Dietary Interaction Matrix",
        "body": "from markers.dietary_interactions import analyze_dietary_interactions\n\ndiet = analyze_dietary_interactions(genotypes)\n# Returns food-specific guidance\n\nCaffeine, alcohol, saturated fat, lactose, gluten\nAPOE-specific diet recommendations\nBitter taste perception"
      },
      {
        "title": "Athletic Performance Profile",
        "body": "from markers.athletic_profile import calculate_athletic_profile\n\nprofile = calculate_athletic_profile(genotypes)\n# Returns power/endurance type, recovery profile, injury risk\n\nSport suitability scoring\nTraining recommendations\nInjury prevention guidance"
      },
      {
        "title": "UV Sensitivity Calculator",
        "body": "from markers.uv_sensitivity import generate_uv_sensitivity_report\n\nuv = generate_uv_sensitivity_report(genotypes)\n# Returns skin type, SPF recommendation, melanoma risk\n\nFitzpatrick skin type estimation\nVitamin D synthesis capacity\nMelanoma risk factors"
      },
      {
        "title": "Natural Language Explanations",
        "body": "from markers.explanations import generate_plain_english_explanation\n\nexplanation = generate_plain_english_explanation(\n    rsid=\"rs3892097\", gene=\"CYP2D6\", genotype=\"GA\",\n    trait=\"Drug metabolism\", finding=\"Poor metabolizer carrier\"\n)\n\nPlain-English summaries\nResearch variant flagging\nPubMed links"
      },
      {
        "title": "Telomere & Longevity",
        "body": "from markers.advanced_genetics import estimate_telomere_length\n\ntelomere = estimate_telomere_length(genotypes)\n# Returns relative estimate with appropriate caveats\n\nTERT, TERC, OBFC1 variants\nLongevity associations (FOXO3, APOE)"
      },
      {
        "title": "Data Quality",
        "body": "Call rate analysis\nPlatform detection\nConfidence scoring\nQuality warnings"
      },
      {
        "title": "Export Formats",
        "body": "Genetic counselor clinical export\nApple Health compatible\nAPI-ready JSON\nIntegration hooks"
      },
      {
        "title": "Marker Categories (21 total)",
        "body": "Pharmacogenomics (159) - Drug metabolism\nPolygenic Risk Scores (277) - Disease risk\nCarrier Status (181) - Recessive carriers\nHealth Risks (233) - Disease susceptibility\nTraits (163) - Physical/behavioral\nHaplogroups (44) - Lineage markers\nAncestry (124) - Population informative\nHereditary Cancer (41) - BRCA, Lynch, etc.\nAutoimmune HLA (31) - HLA associations\nPain Sensitivity (20) - Pain/opioid response\nRare Diseases (29) - Rare conditions\nMental Health (25) - Psychiatric genetics\nDermatology (37) - Skin and hair\nVision & Hearing (33) - Sensory genetics\nFertility (31) - Reproductive health\nNutrition (34) - Nutrigenomics\nFitness (30) - Athletic performance\nNeurogenetics (28) - Cognition/behavior\nLongevity (30) - Aging markers\nImmunity (43) - HLA and immune\nAncestry AIMs (24) - Admixture markers"
      },
      {
        "title": "Agent Integration",
        "body": "The agent_summary.json provides:\n\n{\n  \"critical_alerts\": [],\n  \"high_priority\": [],\n  \"medium_priority\": [],\n  \"pharmacogenomics_alerts\": [],\n  \"apoe_status\": {},\n  \"polygenic_risk_scores\": {},\n  \"haplogroups\": {\n    \"mtDNA\": {\"haplogroup\": \"H\", \"lineage\": \"maternal\"},\n    \"Y_DNA\": {\"haplogroup\": \"R1b\", \"lineage\": \"paternal\"}\n  },\n  \"ancestry\": {\n    \"composition\": {},\n    \"admixture\": {}\n  },\n  \"hereditary_cancer\": {},\n  \"autoimmune_risk\": {},\n  \"pain_sensitivity\": {},\n  \"lifestyle_recommendations\": {\n    \"diet\": [],\n    \"exercise\": [],\n    \"supplements\": [],\n    \"avoid\": []\n  },\n  \"drug_interaction_matrix\": {},\n  \"data_quality\": {}\n}"
      },
      {
        "title": "Pharmacogenomics",
        "body": "DPYD variants - 5-FU/capecitabine FATAL toxicity risk\nHLA-B*5701 - Abacavir hypersensitivity\nHLA-B*1502 - Carbamazepine SJS (certain populations)\nMT-RNR1 - Aminoglycoside-induced deafness"
      },
      {
        "title": "Hereditary Cancer",
        "body": "BRCA1/BRCA2 pathogenic - Breast/ovarian cancer syndrome\nLynch syndrome genes - Colorectal/endometrial cancer\nTP53 pathogenic - Li-Fraumeni syndrome (multi-cancer)"
      },
      {
        "title": "Disease Risk",
        "body": "APOE ε4/ε4 - ~12x Alzheimer's risk\nFactor V Leiden - Thrombosis risk, contraceptive implications\nHLA-B27 - Ankylosing spondylitis susceptibility (OR ~70)"
      },
      {
        "title": "Carrier Status",
        "body": "CFTR - Cystic fibrosis (1 in 25 Europeans)\nHBB - Sickle cell (1 in 12 African Americans)\nHEXA - Tay-Sachs (1 in 30 Ashkenazi Jews)"
      },
      {
        "title": "Basic Analysis",
        "body": "from comprehensive_analysis import main\nmain()  # Uses command line args"
      },
      {
        "title": "Haplogroup Analysis",
        "body": "from markers.haplogroups import analyze_haplogroups\nresult = analyze_haplogroups(genotypes)\nprint(result[\"mtDNA\"][\"haplogroup\"])  # e.g., \"H\""
      },
      {
        "title": "Ancestry",
        "body": "from markers.ancestry_composition import get_ancestry_summary\nancestry = get_ancestry_summary(genotypes)"
      },
      {
        "title": "Cancer Panel",
        "body": "from markers.cancer_panel import analyze_cancer_panel\ncancer = analyze_cancer_panel(genotypes)\nif cancer[\"pathogenic_variants\"]:\n    print(\"ALERT: Pathogenic variants detected\")"
      },
      {
        "title": "Generate PDF",
        "body": "from pdf_report import generate_pdf_report\npdf_path = generate_pdf_report(analysis_results)"
      },
      {
        "title": "Export for Genetic Counselor",
        "body": "from exports import generate_genetic_counselor_export\nclinical = generate_genetic_counselor_export(results, \"clinical.json\")"
      },
      {
        "title": "Privacy",
        "body": "All analysis runs locally\nZero network requests\nNo data leaves the machine"
      },
      {
        "title": "Limitations",
        "body": "Consumer arrays miss rare variants (~0.1% of genome)\nResults are probabilistic, not deterministic\nNot a medical diagnosis\nMost conditions 50-80% non-genetic\nConsult healthcare providers for medical decisions\nNegative hereditary cancer result does NOT rule out cancer syndrome\nHaplogroup resolution limited without WGS"
      },
      {
        "title": "When to Recommend Genetic Counseling",
        "body": "Any pathogenic hereditary cancer variant\nAPOE ε4/ε4 genotype\nMultiple critical pharmacogenomic findings\nCarrier status with reproduction implications\nHigh-risk autoimmune HLA types with symptoms\nResults causing significant user distress"
      }
    ],
    "body": "Personal Genomics Skill v4.2.0\n\nComprehensive local DNA analysis with 1600+ markers across 30 categories. Privacy-first genetic analysis for AI agents.\n\nQuick Start\npython comprehensive_analysis.py /path/to/dna_file.txt\n\nTriggers\n\nActivate this skill when user mentions:\n\nDNA analysis, genetic analysis, genome analysis\n23andMe, AncestryDNA, MyHeritage results\nPharmacogenomics, drug-gene interactions\nMedication interactions, drug safety\nGenetic risk, disease risk, health risk\nCarrier status, carrier testing\nVCF file analysis\nAPOE, MTHFR, CYP2D6, BRCA, or other gene names\nPolygenic risk scores\nHaplogroups, maternal lineage, paternal lineage\nAncestry composition, ethnicity\nHereditary cancer, Lynch syndrome\nAutoimmune genetics, HLA, celiac\nPain sensitivity, opioid response\nSleep optimization, chronotype, caffeine metabolism\nDietary genetics, lactose intolerance, celiac\nAthletic genetics, sports performance\nUV sensitivity, skin type, melanoma risk\nTelomere length, longevity genetics\nSupported Files\n23andMe, AncestryDNA, MyHeritage, FTDNA\nVCF files (whole genome/exome, .vcf or .vcf.gz)\nAny tab-delimited rsid format\nOutput Location\n\n~/dna-analysis/reports/\n\nagent_summary.json - AI-optimized, priority-sorted\nfull_analysis.json - Complete data\nreport.txt - Human-readable\ngenetic_report.pdf - Professional PDF report\nNew v4.0 Features\nHaplogroup Analysis\nMitochondrial DNA (mtDNA) - maternal lineage\nY-chromosome - paternal lineage (males only)\nMigration history context\nPhyloTree/ISOGG standards\nAncestry Composition\nPopulation comparisons (EUR, AFR, EAS, SAS, AMR)\nAdmixture detection\nAncestry informative markers\nHereditary Cancer Panel\nBRCA1/BRCA2 comprehensive\nLynch syndrome (MLH1, MSH2, MSH6, PMS2)\nOther genes (APC, TP53, CHEK2, PALB2, ATM)\nACMG-style classification\nAutoimmune HLA\nCeliac (DQ2/DQ8) - can rule out if negative\nType 1 Diabetes\nAnkylosing spondylitis (HLA-B27)\nRheumatoid arthritis, lupus, MS\nPain Sensitivity\nCOMT Val158Met\nOPRM1 opioid receptor\nSCN9A pain signaling\nTRPV1 capsaicin sensitivity\nMigraine susceptibility\nPDF Reports\nProfessional format\nPhysician-shareable\nExecutive summary\nDetailed findings\nDisclaimers included\nNew v4.1.0 Features\nMedication Interaction Checker\nfrom markers.medication_interactions import check_medication_interactions\n\nresult = check_medication_interactions(\n    medications=[\"warfarin\", \"clopidogrel\", \"omeprazole\"],\n    genotypes=user_genotypes\n)\n# Returns critical/serious/moderate interactions with alternatives\n\nAccepts brand or generic names\nCPIC guidelines integrated\nPubMed citations included\nFDA warning flags\nSleep Optimization Profile\nfrom markers.sleep_optimization import generate_sleep_profile\n\nprofile = generate_sleep_profile(genotypes)\n# Returns ideal wake/sleep times, coffee cutoff, etc.\n\nChronotype (morning/evening preference)\nCaffeine metabolism speed\nPersonalized timing recommendations\nDietary Interaction Matrix\nfrom markers.dietary_interactions import analyze_dietary_interactions\n\ndiet = analyze_dietary_interactions(genotypes)\n# Returns food-specific guidance\n\nCaffeine, alcohol, saturated fat, lactose, gluten\nAPOE-specific diet recommendations\nBitter taste perception\nAthletic Performance Profile\nfrom markers.athletic_profile import calculate_athletic_profile\n\nprofile = calculate_athletic_profile(genotypes)\n# Returns power/endurance type, recovery profile, injury risk\n\nSport suitability scoring\nTraining recommendations\nInjury prevention guidance\nUV Sensitivity Calculator\nfrom markers.uv_sensitivity import generate_uv_sensitivity_report\n\nuv = generate_uv_sensitivity_report(genotypes)\n# Returns skin type, SPF recommendation, melanoma risk\n\nFitzpatrick skin type estimation\nVitamin D synthesis capacity\nMelanoma risk factors\nNatural Language Explanations\nfrom markers.explanations import generate_plain_english_explanation\n\nexplanation = generate_plain_english_explanation(\n    rsid=\"rs3892097\", gene=\"CYP2D6\", genotype=\"GA\",\n    trait=\"Drug metabolism\", finding=\"Poor metabolizer carrier\"\n)\n\nPlain-English summaries\nResearch variant flagging\nPubMed links\nTelomere & Longevity\nfrom markers.advanced_genetics import estimate_telomere_length\n\ntelomere = estimate_telomere_length(genotypes)\n# Returns relative estimate with appropriate caveats\n\nTERT, TERC, OBFC1 variants\nLongevity associations (FOXO3, APOE)\nData Quality\nCall rate analysis\nPlatform detection\nConfidence scoring\nQuality warnings\nExport Formats\nGenetic counselor clinical export\nApple Health compatible\nAPI-ready JSON\nIntegration hooks\nMarker Categories (21 total)\nPharmacogenomics (159) - Drug metabolism\nPolygenic Risk Scores (277) - Disease risk\nCarrier Status (181) - Recessive carriers\nHealth Risks (233) - Disease susceptibility\nTraits (163) - Physical/behavioral\nHaplogroups (44) - Lineage markers\nAncestry (124) - Population informative\nHereditary Cancer (41) - BRCA, Lynch, etc.\nAutoimmune HLA (31) - HLA associations\nPain Sensitivity (20) - Pain/opioid response\nRare Diseases (29) - Rare conditions\nMental Health (25) - Psychiatric genetics\nDermatology (37) - Skin and hair\nVision & Hearing (33) - Sensory genetics\nFertility (31) - Reproductive health\nNutrition (34) - Nutrigenomics\nFitness (30) - Athletic performance\nNeurogenetics (28) - Cognition/behavior\nLongevity (30) - Aging markers\nImmunity (43) - HLA and immune\nAncestry AIMs (24) - Admixture markers\nAgent Integration\n\nThe agent_summary.json provides:\n\n{\n  \"critical_alerts\": [],\n  \"high_priority\": [],\n  \"medium_priority\": [],\n  \"pharmacogenomics_alerts\": [],\n  \"apoe_status\": {},\n  \"polygenic_risk_scores\": {},\n  \"haplogroups\": {\n    \"mtDNA\": {\"haplogroup\": \"H\", \"lineage\": \"maternal\"},\n    \"Y_DNA\": {\"haplogroup\": \"R1b\", \"lineage\": \"paternal\"}\n  },\n  \"ancestry\": {\n    \"composition\": {},\n    \"admixture\": {}\n  },\n  \"hereditary_cancer\": {},\n  \"autoimmune_risk\": {},\n  \"pain_sensitivity\": {},\n  \"lifestyle_recommendations\": {\n    \"diet\": [],\n    \"exercise\": [],\n    \"supplements\": [],\n    \"avoid\": []\n  },\n  \"drug_interaction_matrix\": {},\n  \"data_quality\": {}\n}\n\nCritical Findings (Always Alert User)\nPharmacogenomics\nDPYD variants - 5-FU/capecitabine FATAL toxicity risk\nHLA-B*5701 - Abacavir hypersensitivity\nHLA-B*1502 - Carbamazepine SJS (certain populations)\nMT-RNR1 - Aminoglycoside-induced deafness\nHereditary Cancer\nBRCA1/BRCA2 pathogenic - Breast/ovarian cancer syndrome\nLynch syndrome genes - Colorectal/endometrial cancer\nTP53 pathogenic - Li-Fraumeni syndrome (multi-cancer)\nDisease Risk\nAPOE ε4/ε4 - ~12x Alzheimer's risk\nFactor V Leiden - Thrombosis risk, contraceptive implications\nHLA-B27 - Ankylosing spondylitis susceptibility (OR ~70)\nCarrier Status\nCFTR - Cystic fibrosis (1 in 25 Europeans)\nHBB - Sickle cell (1 in 12 African Americans)\nHEXA - Tay-Sachs (1 in 30 Ashkenazi Jews)\nUsage Examples\nBasic Analysis\nfrom comprehensive_analysis import main\nmain()  # Uses command line args\n\nHaplogroup Analysis\nfrom markers.haplogroups import analyze_haplogroups\nresult = analyze_haplogroups(genotypes)\nprint(result[\"mtDNA\"][\"haplogroup\"])  # e.g., \"H\"\n\nAncestry\nfrom markers.ancestry_composition import get_ancestry_summary\nancestry = get_ancestry_summary(genotypes)\n\nCancer Panel\nfrom markers.cancer_panel import analyze_cancer_panel\ncancer = analyze_cancer_panel(genotypes)\nif cancer[\"pathogenic_variants\"]:\n    print(\"ALERT: Pathogenic variants detected\")\n\nGenerate PDF\nfrom pdf_report import generate_pdf_report\npdf_path = generate_pdf_report(analysis_results)\n\nExport for Genetic Counselor\nfrom exports import generate_genetic_counselor_export\nclinical = generate_genetic_counselor_export(results, \"clinical.json\")\n\nPrivacy\nAll analysis runs locally\nZero network requests\nNo data leaves the machine\nLimitations\nConsumer arrays miss rare variants (~0.1% of genome)\nResults are probabilistic, not deterministic\nNot a medical diagnosis\nMost conditions 50-80% non-genetic\nConsult healthcare providers for medical decisions\nNegative hereditary cancer result does NOT rule out cancer syndrome\nHaplogroup resolution limited without WGS\nWhen to Recommend Genetic Counseling\nAny pathogenic hereditary cancer variant\nAPOE ε4/ε4 genotype\nMultiple critical pharmacogenomic findings\nCarrier status with reproduction implications\nHigh-risk autoimmune HLA types with symptoms\nResults causing significant user distress"
  },
  "trust": {
    "sourceLabel": "tencent",
    "provenanceUrl": "https://clawhub.ai/wkyleg/personal-genomics",
    "publisherUrl": "https://clawhub.ai/wkyleg/personal-genomics",
    "owner": "wkyleg",
    "version": "4.2.0",
    "license": null,
    "verificationStatus": "Indexed source record"
  },
  "links": {
    "detailUrl": "https://openagent3.xyz/skills/personal-genomics",
    "downloadUrl": "https://openagent3.xyz/downloads/personal-genomics",
    "agentUrl": "https://openagent3.xyz/skills/personal-genomics/agent",
    "manifestUrl": "https://openagent3.xyz/skills/personal-genomics/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/personal-genomics/agent.md"
  }
}