[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-google-deepmind-gnomad-database":3,"mdc--l397k4-key":36,"related-repo-google-deepmind-gnomad-database":591,"related-org-google-deepmind-gnomad-database":696},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":11,"stars":25,"repoUrl":26,"updatedAt":27,"license":28,"forks":29,"topics":30,"repo":31,"sourceUrl":34,"mdContent":35},"gnomad-database","query genetic variant data from gnomAD","Query the Genome Aggregation Database (gnomAD). Use when determining the rarity or allele frequency of specific genetic variants, retrieving gene constraint metrics (pLI, LOEUF) to assess loss-of-function intolerance, finding variants in a genomic region or gene, or querying structural variants. Don't use for analyzing individual patient genomes, tracking somatic mutations in cancer (use COSMIC), or requesting raw sequencing reads (use ENA).\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},"google-deepmind","Google DeepMind","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Fgoogle-deepmind.png",[12,16,19,22],{"name":13,"slug":14,"type":15},"Research","research","tag",{"name":17,"slug":18,"type":15},"Life Sciences","life-sciences",{"name":20,"slug":21,"type":15},"Bioinformatics","bioinformatics",{"name":23,"slug":24,"type":15},"Genetics","genetics",2333,"https:\u002F\u002Fgithub.com\u002Fgoogle-deepmind\u002Fscience-skills","2026-07-12T07:51:38.213009",null,234,[],{"repoUrl":26,"stars":25,"forks":29,"topics":32,"description":33},[],"GDM Science Skills to speed up agentic scientific workflows with better grounding and higher token efficiency. Integrate insights from AlphaGenome, AFDB, UniProt and 30+ other databases and tools.","https:\u002F\u002Fgithub.com\u002Fgoogle-deepmind\u002Fscience-skills\u002Ftree\u002FHEAD\u002Fskills\u002Fgnomad_database","---\nname: gnomad-database\ndescription: >\n  Query the Genome Aggregation Database (gnomAD). Use when determining the\n  rarity or allele frequency of specific genetic variants, retrieving gene\n  constraint metrics (pLI, LOEUF) to assess loss-of-function intolerance,\n  finding variants in a genomic region or gene, or querying structural variants.\n  Don't use for analyzing individual patient genomes, tracking somatic mutations\n  in cancer (use COSMIC), or requesting raw sequencing reads (use ENA).\n---\n\n# gnomAD Database\n\n## Prerequisites\n\n1.  **`uv`**: Read the `uv` skill and follow its Setup instructions to ensure\n    `uv` is installed and on PATH.\n2.  **User Notification**: If .licenses\u002Fgnomad_database_LICENSE.txt does not\n    already exist in the workspace root directory then (1) prominently notify\n    the user to check the terms at https:\u002F\u002Fgnomad.broadinstitute.org\u002Fpolicies\n    and https:\u002F\u002Fgnomad.broadinstitute.org\u002Fdata#api, then (2) create the file\n    recording the notification text and timestamp.\n\n## Core Rules\n\n-   **Use the Wrapper**: ALWAYS execute the provided helper scripts to query the\n    database rather than accessing the database directly. The scripts\n    automatically enforce the gnomAD API rate limits gracefully.\n-   **Notification**: If this skill is used, ensure this is mentioned in the\n    output.\n\n## Utility Scripts\n\nAll scripts are located in the `scripts\u002F` subdirectory of this skill's\ninstallation directory. When running them, use the full absolute path to the\nscript (e.g. `\u002Fpath\u002Fto\u002Fgnomad_database\u002Fscripts\u002Fget_variant_frequency.py`).\n\n**1. Variant Frequency.** Retrieves global and ancestry-specific allele\nfrequencies, homozygote counts, and **Grpmax Filtering AF** (faf95\u002Ffaf99) for\nexome, genome, and total (exome+genome combined) data. The filtering allele\nfrequency (FAF) is the maximum credible genetic ancestry group AF (lower bound\nof the 95% or 99% CI). Variant ID format must be `chrom-pos-ref-alt` (e.g.,\n`1-55516888-G-GA`). Alternately, you may provide an `rsID`.\n\n```bash\n# By variant ID:\nuv run scripts\u002Fget_variant_frequency.py --variant_id {variant_id} [--dataset {dataset}] --output variant_frequency.json\n\n# By rsID (e.g., rs1800562):\nuv run scripts\u002Fget_variant_frequency.py --rsid {rsid} [--dataset {dataset}] --output variant_frequency.json\n```\n\n**2. Gene Constraint.** Retrieves constraint metrics for a gene. The response\nwill explicitly contain `pli`, and the LOEUF score is represented by\n`oe_lof_upper`.\n\n```bash\nuv run scripts\u002Fget_gene_constraint.py --gene {gene_symbol} --output {gene_symbol}_constraint.json\n```\n\n**3. Region\u002FGene Variant Search.** Finds all variants in a region or gene.\n\n```bash\n# By region:\nuv run scripts\u002Fsearch_variants.py --chrom {chrom} --start {start} --end {end} --output region_variants.json\n# By gene:\nuv run scripts\u002Fsearch_variants.py --gene {gene_symbol} --consequence {pLoF|missense} --output {gene_symbol}_variants.json\n```\n\n## References\n\nFurther documentation on the data: https:\u002F\u002Fgnomad.broadinstitute.org\u002Fdata#api\nMore general database documentation: https:\u002F\u002Fgnomad.broadinstitute.org\u002Fhelp\n",{"data":37,"body":38},{"name":4,"description":6},{"type":39,"children":40},"root",[41,49,56,119,125,149,155,177,218,353,378,420,430,561,567,585],{"type":42,"tag":43,"props":44,"children":45},"element","h1",{"id":4},[46],{"type":47,"value":48},"text","gnomAD Database",{"type":42,"tag":50,"props":51,"children":53},"h2",{"id":52},"prerequisites",[54],{"type":47,"value":55},"Prerequisites",{"type":42,"tag":57,"props":58,"children":59},"ol",{},[60,91],{"type":42,"tag":61,"props":62,"children":63},"li",{},[64,75,77,82,84,89],{"type":42,"tag":65,"props":66,"children":67},"strong",{},[68],{"type":42,"tag":69,"props":70,"children":72},"code",{"className":71},[],[73],{"type":47,"value":74},"uv",{"type":47,"value":76},": Read the ",{"type":42,"tag":69,"props":78,"children":80},{"className":79},[],[81],{"type":47,"value":74},{"type":47,"value":83}," skill and follow its Setup instructions to ensure\n",{"type":42,"tag":69,"props":85,"children":87},{"className":86},[],[88],{"type":47,"value":74},{"type":47,"value":90}," is installed and on PATH.",{"type":42,"tag":61,"props":92,"children":93},{},[94,99,101,109,111,117],{"type":42,"tag":65,"props":95,"children":96},{},[97],{"type":47,"value":98},"User Notification",{"type":47,"value":100},": If .licenses\u002Fgnomad_database_LICENSE.txt does not\nalready exist in the workspace root directory then (1) prominently notify\nthe user to check the terms at ",{"type":42,"tag":102,"props":103,"children":107},"a",{"href":104,"rel":105},"https:\u002F\u002Fgnomad.broadinstitute.org\u002Fpolicies",[106],"nofollow",[108],{"type":47,"value":104},{"type":47,"value":110},"\nand ",{"type":42,"tag":102,"props":112,"children":115},{"href":113,"rel":114},"https:\u002F\u002Fgnomad.broadinstitute.org\u002Fdata#api",[106],[116],{"type":47,"value":113},{"type":47,"value":118},", then (2) create the file\nrecording the notification text and timestamp.",{"type":42,"tag":50,"props":120,"children":122},{"id":121},"core-rules",[123],{"type":47,"value":124},"Core Rules",{"type":42,"tag":126,"props":127,"children":128},"ul",{},[129,139],{"type":42,"tag":61,"props":130,"children":131},{},[132,137],{"type":42,"tag":65,"props":133,"children":134},{},[135],{"type":47,"value":136},"Use the Wrapper",{"type":47,"value":138},": ALWAYS execute the provided helper scripts to query the\ndatabase rather than accessing the database directly. The scripts\nautomatically enforce the gnomAD API rate limits gracefully.",{"type":42,"tag":61,"props":140,"children":141},{},[142,147],{"type":42,"tag":65,"props":143,"children":144},{},[145],{"type":47,"value":146},"Notification",{"type":47,"value":148},": If this skill is used, ensure this is mentioned in the\noutput.",{"type":42,"tag":50,"props":150,"children":152},{"id":151},"utility-scripts",[153],{"type":47,"value":154},"Utility Scripts",{"type":42,"tag":156,"props":157,"children":158},"p",{},[159,161,167,169,175],{"type":47,"value":160},"All scripts are located in the ",{"type":42,"tag":69,"props":162,"children":164},{"className":163},[],[165],{"type":47,"value":166},"scripts\u002F",{"type":47,"value":168}," subdirectory of this skill's\ninstallation directory. When running them, use the full absolute path to the\nscript (e.g. ",{"type":42,"tag":69,"props":170,"children":172},{"className":171},[],[173],{"type":47,"value":174},"\u002Fpath\u002Fto\u002Fgnomad_database\u002Fscripts\u002Fget_variant_frequency.py",{"type":47,"value":176},").",{"type":42,"tag":156,"props":178,"children":179},{},[180,185,187,192,194,200,202,208,210,216],{"type":42,"tag":65,"props":181,"children":182},{},[183],{"type":47,"value":184},"1. Variant Frequency.",{"type":47,"value":186}," Retrieves global and ancestry-specific allele\nfrequencies, homozygote counts, and ",{"type":42,"tag":65,"props":188,"children":189},{},[190],{"type":47,"value":191},"Grpmax Filtering AF",{"type":47,"value":193}," (faf95\u002Ffaf99) for\nexome, genome, and total (exome+genome combined) data. The filtering allele\nfrequency (FAF) is the maximum credible genetic ancestry group AF (lower bound\nof the 95% or 99% CI). Variant ID format must be ",{"type":42,"tag":69,"props":195,"children":197},{"className":196},[],[198],{"type":47,"value":199},"chrom-pos-ref-alt",{"type":47,"value":201}," (e.g.,\n",{"type":42,"tag":69,"props":203,"children":205},{"className":204},[],[206],{"type":47,"value":207},"1-55516888-G-GA",{"type":47,"value":209},"). Alternately, you may provide an ",{"type":42,"tag":69,"props":211,"children":213},{"className":212},[],[214],{"type":47,"value":215},"rsID",{"type":47,"value":217},".",{"type":42,"tag":219,"props":220,"children":225},"pre",{"className":221,"code":222,"language":223,"meta":224,"style":224},"language-bash shiki shiki-themes material-theme-lighter material-theme material-theme-palenight","# By variant ID:\nuv run scripts\u002Fget_variant_frequency.py --variant_id {variant_id} [--dataset {dataset}] --output variant_frequency.json\n\n# By rsID (e.g., rs1800562):\nuv run scripts\u002Fget_variant_frequency.py --rsid {rsid} [--dataset {dataset}] --output variant_frequency.json\n","bash","",[226],{"type":42,"tag":69,"props":227,"children":228},{"__ignoreMap":224},[229,241,292,302,311],{"type":42,"tag":230,"props":231,"children":234},"span",{"class":232,"line":233},"line",1,[235],{"type":42,"tag":230,"props":236,"children":238},{"style":237},"--shiki-light:#90A4AE;--shiki-light-font-style:italic;--shiki-default:#546E7A;--shiki-default-font-style:italic;--shiki-dark:#676E95;--shiki-dark-font-style:italic",[239],{"type":47,"value":240},"# By variant ID:\n",{"type":42,"tag":230,"props":242,"children":244},{"class":232,"line":243},2,[245,250,256,261,266,271,277,282,287],{"type":42,"tag":230,"props":246,"children":248},{"style":247},"--shiki-light:#E2931D;--shiki-default:#FFCB6B;--shiki-dark:#FFCB6B",[249],{"type":47,"value":74},{"type":42,"tag":230,"props":251,"children":253},{"style":252},"--shiki-light:#91B859;--shiki-default:#C3E88D;--shiki-dark:#C3E88D",[254],{"type":47,"value":255}," run",{"type":42,"tag":230,"props":257,"children":258},{"style":252},[259],{"type":47,"value":260}," scripts\u002Fget_variant_frequency.py",{"type":42,"tag":230,"props":262,"children":263},{"style":252},[264],{"type":47,"value":265}," --variant_id",{"type":42,"tag":230,"props":267,"children":268},{"style":252},[269],{"type":47,"value":270}," {variant_id}",{"type":42,"tag":230,"props":272,"children":274},{"style":273},"--shiki-light:#90A4AE;--shiki-default:#EEFFFF;--shiki-dark:#BABED8",[275],{"type":47,"value":276}," [--dataset ",{"type":42,"tag":230,"props":278,"children":279},{"style":252},[280],{"type":47,"value":281},"{dataset}]",{"type":42,"tag":230,"props":283,"children":284},{"style":252},[285],{"type":47,"value":286}," --output",{"type":42,"tag":230,"props":288,"children":289},{"style":252},[290],{"type":47,"value":291}," variant_frequency.json\n",{"type":42,"tag":230,"props":293,"children":295},{"class":232,"line":294},3,[296],{"type":42,"tag":230,"props":297,"children":299},{"emptyLinePlaceholder":298},true,[300],{"type":47,"value":301},"\n",{"type":42,"tag":230,"props":303,"children":305},{"class":232,"line":304},4,[306],{"type":42,"tag":230,"props":307,"children":308},{"style":237},[309],{"type":47,"value":310},"# By rsID (e.g., rs1800562):\n",{"type":42,"tag":230,"props":312,"children":314},{"class":232,"line":313},5,[315,319,323,327,332,337,341,345,349],{"type":42,"tag":230,"props":316,"children":317},{"style":247},[318],{"type":47,"value":74},{"type":42,"tag":230,"props":320,"children":321},{"style":252},[322],{"type":47,"value":255},{"type":42,"tag":230,"props":324,"children":325},{"style":252},[326],{"type":47,"value":260},{"type":42,"tag":230,"props":328,"children":329},{"style":252},[330],{"type":47,"value":331}," --rsid",{"type":42,"tag":230,"props":333,"children":334},{"style":252},[335],{"type":47,"value":336}," {rsid}",{"type":42,"tag":230,"props":338,"children":339},{"style":273},[340],{"type":47,"value":276},{"type":42,"tag":230,"props":342,"children":343},{"style":252},[344],{"type":47,"value":281},{"type":42,"tag":230,"props":346,"children":347},{"style":252},[348],{"type":47,"value":286},{"type":42,"tag":230,"props":350,"children":351},{"style":252},[352],{"type":47,"value":291},{"type":42,"tag":156,"props":354,"children":355},{},[356,361,363,369,371,377],{"type":42,"tag":65,"props":357,"children":358},{},[359],{"type":47,"value":360},"2. Gene Constraint.",{"type":47,"value":362}," Retrieves constraint metrics for a gene. The response\nwill explicitly contain ",{"type":42,"tag":69,"props":364,"children":366},{"className":365},[],[367],{"type":47,"value":368},"pli",{"type":47,"value":370},", and the LOEUF score is represented by\n",{"type":42,"tag":69,"props":372,"children":374},{"className":373},[],[375],{"type":47,"value":376},"oe_lof_upper",{"type":47,"value":217},{"type":42,"tag":219,"props":379,"children":381},{"className":221,"code":380,"language":223,"meta":224,"style":224},"uv run scripts\u002Fget_gene_constraint.py --gene {gene_symbol} --output {gene_symbol}_constraint.json\n",[382],{"type":42,"tag":69,"props":383,"children":384},{"__ignoreMap":224},[385],{"type":42,"tag":230,"props":386,"children":387},{"class":232,"line":233},[388,392,396,401,406,411,415],{"type":42,"tag":230,"props":389,"children":390},{"style":247},[391],{"type":47,"value":74},{"type":42,"tag":230,"props":393,"children":394},{"style":252},[395],{"type":47,"value":255},{"type":42,"tag":230,"props":397,"children":398},{"style":252},[399],{"type":47,"value":400}," scripts\u002Fget_gene_constraint.py",{"type":42,"tag":230,"props":402,"children":403},{"style":252},[404],{"type":47,"value":405}," --gene",{"type":42,"tag":230,"props":407,"children":408},{"style":252},[409],{"type":47,"value":410}," {gene_symbol}",{"type":42,"tag":230,"props":412,"children":413},{"style":252},[414],{"type":47,"value":286},{"type":42,"tag":230,"props":416,"children":417},{"style":252},[418],{"type":47,"value":419}," {gene_symbol}_constraint.json\n",{"type":42,"tag":156,"props":421,"children":422},{},[423,428],{"type":42,"tag":65,"props":424,"children":425},{},[426],{"type":47,"value":427},"3. Region\u002FGene Variant Search.",{"type":47,"value":429}," Finds all variants in a region or gene.",{"type":42,"tag":219,"props":431,"children":433},{"className":221,"code":432,"language":223,"meta":224,"style":224},"# By region:\nuv run scripts\u002Fsearch_variants.py --chrom {chrom} --start {start} --end {end} --output region_variants.json\n# By gene:\nuv run scripts\u002Fsearch_variants.py --gene {gene_symbol} --consequence {pLoF|missense} --output {gene_symbol}_variants.json\n",[434],{"type":42,"tag":69,"props":435,"children":436},{"__ignoreMap":224},[437,445,500,508],{"type":42,"tag":230,"props":438,"children":439},{"class":232,"line":233},[440],{"type":42,"tag":230,"props":441,"children":442},{"style":237},[443],{"type":47,"value":444},"# By region:\n",{"type":42,"tag":230,"props":446,"children":447},{"class":232,"line":243},[448,452,456,461,466,471,476,481,486,491,495],{"type":42,"tag":230,"props":449,"children":450},{"style":247},[451],{"type":47,"value":74},{"type":42,"tag":230,"props":453,"children":454},{"style":252},[455],{"type":47,"value":255},{"type":42,"tag":230,"props":457,"children":458},{"style":252},[459],{"type":47,"value":460}," scripts\u002Fsearch_variants.py",{"type":42,"tag":230,"props":462,"children":463},{"style":252},[464],{"type":47,"value":465}," --chrom",{"type":42,"tag":230,"props":467,"children":468},{"style":252},[469],{"type":47,"value":470}," {chrom}",{"type":42,"tag":230,"props":472,"children":473},{"style":252},[474],{"type":47,"value":475}," --start",{"type":42,"tag":230,"props":477,"children":478},{"style":252},[479],{"type":47,"value":480}," {start}",{"type":42,"tag":230,"props":482,"children":483},{"style":252},[484],{"type":47,"value":485}," --end",{"type":42,"tag":230,"props":487,"children":488},{"style":252},[489],{"type":47,"value":490}," {end}",{"type":42,"tag":230,"props":492,"children":493},{"style":252},[494],{"type":47,"value":286},{"type":42,"tag":230,"props":496,"children":497},{"style":252},[498],{"type":47,"value":499}," region_variants.json\n",{"type":42,"tag":230,"props":501,"children":502},{"class":232,"line":294},[503],{"type":42,"tag":230,"props":504,"children":505},{"style":237},[506],{"type":47,"value":507},"# By gene:\n",{"type":42,"tag":230,"props":509,"children":510},{"class":232,"line":304},[511,515,519,523,527,531,536,541,547,552,556],{"type":42,"tag":230,"props":512,"children":513},{"style":247},[514],{"type":47,"value":74},{"type":42,"tag":230,"props":516,"children":517},{"style":252},[518],{"type":47,"value":255},{"type":42,"tag":230,"props":520,"children":521},{"style":252},[522],{"type":47,"value":460},{"type":42,"tag":230,"props":524,"children":525},{"style":252},[526],{"type":47,"value":405},{"type":42,"tag":230,"props":528,"children":529},{"style":252},[530],{"type":47,"value":410},{"type":42,"tag":230,"props":532,"children":533},{"style":252},[534],{"type":47,"value":535}," --consequence",{"type":42,"tag":230,"props":537,"children":538},{"style":252},[539],{"type":47,"value":540}," {pLoF",{"type":42,"tag":230,"props":542,"children":544},{"style":543},"--shiki-light:#39ADB5;--shiki-default:#89DDFF;--shiki-dark:#89DDFF",[545],{"type":47,"value":546},"|",{"type":42,"tag":230,"props":548,"children":549},{"style":247},[550],{"type":47,"value":551},"missense}",{"type":42,"tag":230,"props":553,"children":554},{"style":252},[555],{"type":47,"value":286},{"type":42,"tag":230,"props":557,"children":558},{"style":252},[559],{"type":47,"value":560}," {gene_symbol}_variants.json\n",{"type":42,"tag":50,"props":562,"children":564},{"id":563},"references",[565],{"type":47,"value":566},"References",{"type":42,"tag":156,"props":568,"children":569},{},[570,572,577,579],{"type":47,"value":571},"Further documentation on the data: ",{"type":42,"tag":102,"props":573,"children":575},{"href":113,"rel":574},[106],[576],{"type":47,"value":113},{"type":47,"value":578},"\nMore general database documentation: ",{"type":42,"tag":102,"props":580,"children":583},{"href":581,"rel":582},"https:\u002F\u002Fgnomad.broadinstitute.org\u002Fhelp",[106],[584],{"type":47,"value":581},{"type":42,"tag":586,"props":587,"children":588},"style",{},[589],{"type":47,"value":590},"html .light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html.light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html .default .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}html.dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}",{"items":592,"total":695},[593,606,619,639,651,666,682],{"slug":594,"name":594,"fn":595,"description":596,"org":597,"tags":598,"stars":25,"repoUrl":26,"updatedAt":605},"alphafold-database-fetch-and-analyze","retrieve and analyze AlphaFold protein structures","Retrieve and analyze AlphaFold predicted structures for a protein. Use when the user provides a specific UniProt Accession ID and wants structural confidence metrics (pLDDT), domain boundary analysis, or disorder assessment. Do not use if the user only has a protein name, gene name, or amino acid sequence — ask for a UniProt ID first.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[599,600,603,604],{"name":20,"slug":21,"type":15},{"name":601,"slug":602,"type":15},"Genomics","genomics",{"name":17,"slug":18,"type":15},{"name":13,"slug":14,"type":15},"2026-07-12T07:51:51.827211",{"slug":607,"name":607,"fn":608,"description":609,"org":610,"tags":611,"stars":25,"repoUrl":26,"updatedAt":618},"alphagenome-single-variant-analysis","analyze genetic variant effects with AlphaGenome","Analyzes genetic variant effects on gene expression (RNA-seq), chromatin accessibility (DNASE), histone marks (ChIP), and transcription factors using the AlphaGenome API. Use when the user asks about non-coding variant effects, pathogenicity, clinical significance, disease associations, functional effects, gene expression changes, splicing disruption, or regulatory effects in promoters and enhancers. Also use for resolving biological terms to tissue\u002Fcell-type ontologies (UBERON\u002FCL) or analyzing variants in chr:pos:ref>alt format.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[612,613,614,615],{"name":20,"slug":21,"type":15},{"name":23,"slug":24,"type":15},{"name":13,"slug":14,"type":15},{"name":616,"slug":617,"type":15},"RNA-seq","rna-seq","2026-07-12T07:51:39.494803",{"slug":620,"name":620,"fn":621,"description":622,"org":623,"tags":624,"stars":25,"repoUrl":26,"updatedAt":638},"chembl-database","query ChEMBL database for bioactive molecules","Query the ChEMBL database for bioactive molecules, drug targets, bioactivity data, approved drugs, and chemical structures. Use when the user asks about compounds, targets, IC50\u002FKi values, drug mechanisms, or structure searches.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[625,628,631,634,637],{"name":626,"slug":627,"type":15},"ChEMBL","chembl",{"name":629,"slug":630,"type":15},"Chemistry","chemistry",{"name":632,"slug":633,"type":15},"Database","database",{"name":635,"slug":636,"type":15},"Pharmacology","pharmacology",{"name":13,"slug":14,"type":15},"2026-07-12T07:51:35.544306",{"slug":640,"name":640,"fn":641,"description":642,"org":643,"tags":644,"stars":25,"repoUrl":26,"updatedAt":650},"clinical-trials-database","query clinical trial data","Query ClinicalTrials.gov via APIv2. Use when you want to search for trials by condition, drug, location, status, or phase; retrieve trial details by NCT ID; check eligibility\u002Finclusion criteria; count trials across conditions or time periods; identify a sponsor's trial portfolio; find recruiting trials for patient matching.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[645,648,649],{"name":646,"slug":647,"type":15},"Clinical Trials","clinical-trials",{"name":17,"slug":18,"type":15},{"name":13,"slug":14,"type":15},"2026-07-12T07:52:06.846705",{"slug":652,"name":652,"fn":653,"description":654,"org":655,"tags":656,"stars":25,"repoUrl":26,"updatedAt":665},"clinvar-database","retrieve clinical significance from ClinVar database","Use when needing clinical significance, pathogenicity classifications (e.g., Pathogenic, Benign, VUS), clinical evidence rationales, or finding \"hard positive\" benchmark controls for human genomic variants.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[657,660,661,664],{"name":658,"slug":659,"type":15},"ClinVar","clinvar",{"name":23,"slug":24,"type":15},{"name":662,"slug":663,"type":15},"Healthcare","healthcare",{"name":13,"slug":14,"type":15},"2026-07-12T07:51:36.86094",{"slug":667,"name":667,"fn":668,"description":669,"org":670,"tags":671,"stars":25,"repoUrl":26,"updatedAt":681},"credentials","manage and verify API credentials safely","Instructions for handling API keys and credentials safely, verifying their presence, and prompting the user to add them if missing using a safe protocol.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[672,675,678],{"name":673,"slug":674,"type":15},"Compliance","compliance",{"name":676,"slug":677,"type":15},"Operations","operations",{"name":679,"slug":680,"type":15},"Security","security","2026-07-12T07:52:17.355491",{"slug":683,"name":683,"fn":684,"description":685,"org":686,"tags":687,"stars":25,"repoUrl":26,"updatedAt":694},"dbsnp-database","search genetic variants in dbSNP database","Use when you want to look up, map, and search for short genetic variants (SNPs, indels) in NCBI's dbSNP database. Resolves between rsIDs, genomic coordinates in VCF format, and HGVS strings. For an rsID, returns variant type, gene associations, clinical significance, allele frequencies, and genomic coordinates (GRCh38).\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[688,689,690,693],{"name":20,"slug":21,"type":15},{"name":23,"slug":24,"type":15},{"name":691,"slug":692,"type":15},"NCBI","ncbi",{"name":13,"slug":14,"type":15},"2026-07-12T07:51:33.054229",38,{"items":697,"total":695},[698,705,712,720,726,733,739,746,758,773,784,794],{"slug":594,"name":594,"fn":595,"description":596,"org":699,"tags":700,"stars":25,"repoUrl":26,"updatedAt":605},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[701,702,703,704],{"name":20,"slug":21,"type":15},{"name":601,"slug":602,"type":15},{"name":17,"slug":18,"type":15},{"name":13,"slug":14,"type":15},{"slug":607,"name":607,"fn":608,"description":609,"org":706,"tags":707,"stars":25,"repoUrl":26,"updatedAt":618},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[708,709,710,711],{"name":20,"slug":21,"type":15},{"name":23,"slug":24,"type":15},{"name":13,"slug":14,"type":15},{"name":616,"slug":617,"type":15},{"slug":620,"name":620,"fn":621,"description":622,"org":713,"tags":714,"stars":25,"repoUrl":26,"updatedAt":638},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[715,716,717,718,719],{"name":626,"slug":627,"type":15},{"name":629,"slug":630,"type":15},{"name":632,"slug":633,"type":15},{"name":635,"slug":636,"type":15},{"name":13,"slug":14,"type":15},{"slug":640,"name":640,"fn":641,"description":642,"org":721,"tags":722,"stars":25,"repoUrl":26,"updatedAt":650},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[723,724,725],{"name":646,"slug":647,"type":15},{"name":17,"slug":18,"type":15},{"name":13,"slug":14,"type":15},{"slug":652,"name":652,"fn":653,"description":654,"org":727,"tags":728,"stars":25,"repoUrl":26,"updatedAt":665},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[729,730,731,732],{"name":658,"slug":659,"type":15},{"name":23,"slug":24,"type":15},{"name":662,"slug":663,"type":15},{"name":13,"slug":14,"type":15},{"slug":667,"name":667,"fn":668,"description":669,"org":734,"tags":735,"stars":25,"repoUrl":26,"updatedAt":681},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[736,737,738],{"name":673,"slug":674,"type":15},{"name":676,"slug":677,"type":15},{"name":679,"slug":680,"type":15},{"slug":683,"name":683,"fn":684,"description":685,"org":740,"tags":741,"stars":25,"repoUrl":26,"updatedAt":694},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[742,743,744,745],{"name":20,"slug":21,"type":15},{"name":23,"slug":24,"type":15},{"name":691,"slug":692,"type":15},{"name":13,"slug":14,"type":15},{"slug":747,"name":747,"fn":748,"description":749,"org":750,"tags":751,"stars":25,"repoUrl":26,"updatedAt":757},"embl-ebi-ols","search biomedical ontologies in EMBL-EBI OLS","Query and search the EMBL-EBI Ontology Lookup Service (OLS) for biomedical ontology terms, definitions, and hierarchies across 250+ ontologies (e.g., GO, DOID, HP). Use when the user asks to search for terms, retrieve details, navigate hierarchies (parents, children, ancestors), look up properties and individuals, get autocomplete suggestions, or access ontology metadata and statistics.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[752,753,756],{"name":20,"slug":21,"type":15},{"name":754,"slug":755,"type":15},"Ontology","ontology",{"name":13,"slug":14,"type":15},"2026-07-12T07:51:59.368324",{"slug":759,"name":759,"fn":760,"description":761,"org":762,"tags":763,"stars":25,"repoUrl":26,"updatedAt":772},"encode-ccres-database","query ENCODE regulatory and experimental data","Query the ENCODE Registry of cis-Regulatory Elements (cCREs) via the SCREEN GraphQL API, or make custom queries to the ENCODE Portal REST API for experiments and files (ChIP-seq peaks, etc.). Use when you want to query regulatory annotations or raw experimental data across human cell types.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[764,765,768,769],{"name":20,"slug":21,"type":15},{"name":766,"slug":767,"type":15},"GraphQL","graphql",{"name":13,"slug":14,"type":15},{"name":770,"slug":771,"type":15},"REST API","rest-api","2026-07-12T07:52:10.597139",{"slug":774,"name":774,"fn":775,"description":776,"org":777,"tags":778,"stars":25,"repoUrl":26,"updatedAt":783},"ensembl-database","query genomic and protein data from Ensembl","Query the Ensembl database to resolve gene, transcript, and protein IDs, fetch genomic or protein sequences, retrieve gene structures (exons), and get variant consequence and effect predictions (VEP). Use this skill as a primary ID translator, genomic sequence database and variant effect prediction tool.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[779,780,781,782],{"name":20,"slug":21,"type":15},{"name":23,"slug":24,"type":15},{"name":17,"slug":18,"type":15},{"name":13,"slug":14,"type":15},"2026-07-12T07:51:41.645835",{"slug":785,"name":785,"fn":786,"description":787,"org":788,"tags":789,"stars":25,"repoUrl":26,"updatedAt":793},"foldseek-structural-search","perform 3D protein structural searches","Performs 3D structural searches of proteins against various databases (PDB, AlphaFold, CATH, MGnify, etc.) using the Foldseek API. Use ONLY when the user provides a physical 3D coordinate file (.cif, .mmcif, or .pdb) and wants to find structurally similar proteins. Do NOT use if the user only provides a protein sequence, gene name, or UniProt ID.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[790,791,792],{"name":20,"slug":21,"type":15},{"name":17,"slug":18,"type":15},{"name":13,"slug":14,"type":15},"2026-07-12T07:52:09.354992",{"slug":4,"name":4,"fn":5,"description":6,"org":795,"tags":796,"stars":25,"repoUrl":26,"updatedAt":27},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[797,798,799,800],{"name":20,"slug":21,"type":15},{"name":23,"slug":24,"type":15},{"name":17,"slug":18,"type":15},{"name":13,"slug":14,"type":15}]