[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-google-deepmind-foldseek-structural-search":3,"mdc-sjcmcp-key":33,"related-org-google-deepmind-foldseek-structural-search":609,"related-repo-google-deepmind-foldseek-structural-search":771},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":11,"stars":22,"repoUrl":23,"updatedAt":24,"license":25,"forks":26,"topics":27,"repo":28,"sourceUrl":31,"mdContent":32},"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},"google-deepmind","Google DeepMind","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Fgoogle-deepmind.png",[12,16,19],{"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",2333,"https:\u002F\u002Fgithub.com\u002Fgoogle-deepmind\u002Fscience-skills","2026-07-12T07:52:09.354992",null,234,[],{"repoUrl":23,"stars":22,"forks":26,"topics":29,"description":30},[],"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\u002Ffoldseek_structural_search","---\nname: foldseek-structural-search\ndescription: >\n    Performs 3D structural searches of proteins against various databases (PDB,\n    AlphaFold, CATH, MGnify, etc.) using the Foldseek API. Use ONLY when the\n    user provides a physical 3D coordinate file (.cif, .mmcif, or .pdb) and\n    wants to find structurally similar proteins. Do NOT use if the user only\n    provides a protein sequence, gene name, or UniProt ID.\n---\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\u002Ffoldseek_structural_search_LICENSE.txt\n    does not already exist in the workspace root directory then (1) prominently\n    notify the user to check the terms at https:\u002F\u002Fsearch.foldseek.com\u002Fsearch and\n    https:\u002F\u002Fgithub.com\u002Fsteineggerlab\u002Ffoldseek, then (2) create the file\n    recording the notification text and timestamp.\n\n## Goal\n\nSubmit a user-provided 3D protein structure file (`.cif`, `.mmcif`, or `.pdb`)\nto the Foldseek web server API to find structurally similar proteins. Report the\ntop structural hits, interpret key alignment metrics, summarize the inferred\nprotein functions, save the Markdown-formatted table to a `.md` file, and save\nthe full detailed results to a local JSON file.\n\n## Core Rules\n\n-   **File Requirement**: This tool absolutely cannot search by sequence, name,\n    or accession ID. It strictly requires a `.pdb`, `.cif`, or `.mmcif` file\n    path.\n-   **Strict Validation**: Never bypass the input validation or the database\n    allowlist check.\n-   **Do Not Parse the JSON**: Rely entirely on the generated `.md` file for\n    your immediate summary. The JSON is saved purely for subsequent, specialized\n    tool use.\n-   **No Raw Parsing**: Do not attempt to parse or read the raw 3D coordinates\n    yourself; always pass the file to the script.\n-   **Notification**: If this skill is used, ensure this is mentioned in the\n    output.\n\n## Instructions\n\n1.  **Strict Input Validation:** Verify that the user has explicitly provided a\n    valid path to a `.cif`, `.mmcif`, or `.pdb` file in their workspace.\n    *   If the user provided a protein name, an amino acid sequence, or an\n        accession ID (e.g., a UniProt ID) but NO downloaded structure file,\n        **halt immediately**. Do not run the script.\n    *   Inform the user that Foldseek requires a physical 3D coordinate file,\n        and suggest downloading the structure first (e.g., using the AlphaFold\n        fetch tool).\n2.  **Database Validation:** Check if the user requested specific databases to\n    search.\n    *   **Allowed List:** `afdb50`, `afdb-swissprot`, `pdb100`, `BFVD`,\n        `mgnify_esm30`, `cath50`, `gmgcl_id`, `bfmd`, `afdb-proteome`.\n    *   If the user requests a database NOT on this list, **halt immediately**.\n        Do not run the script. Inform the user that the database is unsupported\n        and provide them with the allowed list.\n3.  **Generate File Names:** Generate descriptive output file names for both the\n    JSON data and the Markdown table based on the input file (e.g.,\n    `proteinA_foldseek_results.json` and `proteinA_foldseek_results.md`).\n4.  Execute the python script based on the user's request, redirecting the\n    standard output into your generated `.md` file:\n    *   **Default (No databases specified):** `uv run scripts\u002Fsearch.py\n        \u003Cpath-to-file> -o \u003Cgenerated-filename.json> > \u003Cgenerated-filename.md>`\n    *   **Custom (Valid databases specified):** `uv run scripts\u002Fsearch.py\n        \u003Cpath-to-file> -o \u003Cgenerated-filename.json> --databases \u003Cdb1,db2,db3> >\n        \u003Cgenerated-filename.md>`\n5.  The script will query the databases, save the full JSON payload, and write a\n    Markdown-formatted table to your specified `.md` file.\n6.  **Read the Results:** Open and read the newly generated `.md` file carefully\n    to view the Markdown table.\n7.  **Interpret the Metrics:** Summarize the top 3 to 5 structural matches that\n    have meaningfull annotations for the user. When reporting, assess the match\n    quality using these specific fields:\n    *   **Prob (Probability):** Values approaching 1.0 (100%) indicate extreme\n        confidence that the fold is a true structural homologue.\n    *   **Q-Cov (Query Coverage):** High percentages mean the match covers the\n        majority of the query protein's overall shape, rather than just a small\n        local motif.\n    *   **E-value & Seq Identity:** Use these to provide additional evolutionary\n        context.\n8.  **Perform Functional Analysis:** Analyze the text descriptions embedded\n    within the `Target ID` column for the reported matches.\n    *   Explicitly report the specific protein names\u002Ffunctions of the top\n        structural homologues.\n    *   Provide a synthesized overview summarizing the entire *variety* of\n        different functions, domains, or protein families found across the whole\n        list of homologues (e.g., \"Most hits are portal proteins, but there is\n        also a distinct cluster of viral capsid matches...\").\n9.  Explicitly inform the user of both newly created files (`.json` and `.md`)\n    and their locations so they can be seamlessly used in subsequent analysis\n    steps.\n\n## * If the API returns an error or the file is missing, inform the user clearly\n\nand ask them to verify the file path.\n",{"data":34,"body":35},{"name":4,"description":6},{"type":36,"children":37},"root",[38,47,110,116,154,160,240,246,598,604],{"type":39,"tag":40,"props":41,"children":43},"element","h2",{"id":42},"prerequisites",[44],{"type":45,"value":46},"text","Prerequisites",{"type":39,"tag":48,"props":49,"children":50},"ol",{},[51,82],{"type":39,"tag":52,"props":53,"children":54},"li",{},[55,66,68,73,75,80],{"type":39,"tag":56,"props":57,"children":58},"strong",{},[59],{"type":39,"tag":60,"props":61,"children":63},"code",{"className":62},[],[64],{"type":45,"value":65},"uv",{"type":45,"value":67},": Read the ",{"type":39,"tag":60,"props":69,"children":71},{"className":70},[],[72],{"type":45,"value":65},{"type":45,"value":74}," skill and follow its Setup instructions to ensure\n",{"type":39,"tag":60,"props":76,"children":78},{"className":77},[],[79],{"type":45,"value":65},{"type":45,"value":81}," is installed and on PATH.",{"type":39,"tag":52,"props":83,"children":84},{},[85,90,92,100,102,108],{"type":39,"tag":56,"props":86,"children":87},{},[88],{"type":45,"value":89},"User Notification",{"type":45,"value":91},": If .licenses\u002Ffoldseek_structural_search_LICENSE.txt\ndoes not already exist in the workspace root directory then (1) prominently\nnotify the user to check the terms at ",{"type":39,"tag":93,"props":94,"children":98},"a",{"href":95,"rel":96},"https:\u002F\u002Fsearch.foldseek.com\u002Fsearch",[97],"nofollow",[99],{"type":45,"value":95},{"type":45,"value":101}," and\n",{"type":39,"tag":93,"props":103,"children":106},{"href":104,"rel":105},"https:\u002F\u002Fgithub.com\u002Fsteineggerlab\u002Ffoldseek",[97],[107],{"type":45,"value":104},{"type":45,"value":109},", then (2) create the file\nrecording the notification text and timestamp.",{"type":39,"tag":40,"props":111,"children":113},{"id":112},"goal",[114],{"type":45,"value":115},"Goal",{"type":39,"tag":117,"props":118,"children":119},"p",{},[120,122,128,130,136,138,144,146,152],{"type":45,"value":121},"Submit a user-provided 3D protein structure file (",{"type":39,"tag":60,"props":123,"children":125},{"className":124},[],[126],{"type":45,"value":127},".cif",{"type":45,"value":129},", ",{"type":39,"tag":60,"props":131,"children":133},{"className":132},[],[134],{"type":45,"value":135},".mmcif",{"type":45,"value":137},", or ",{"type":39,"tag":60,"props":139,"children":141},{"className":140},[],[142],{"type":45,"value":143},".pdb",{"type":45,"value":145},")\nto the Foldseek web server API to find structurally similar proteins. Report the\ntop structural hits, interpret key alignment metrics, summarize the inferred\nprotein functions, save the Markdown-formatted table to a ",{"type":39,"tag":60,"props":147,"children":149},{"className":148},[],[150],{"type":45,"value":151},".md",{"type":45,"value":153}," file, and save\nthe full detailed results to a local JSON file.",{"type":39,"tag":40,"props":155,"children":157},{"id":156},"core-rules",[158],{"type":45,"value":159},"Core Rules",{"type":39,"tag":161,"props":162,"children":163},"ul",{},[164,193,203,220,230],{"type":39,"tag":52,"props":165,"children":166},{},[167,172,174,179,180,185,186,191],{"type":39,"tag":56,"props":168,"children":169},{},[170],{"type":45,"value":171},"File Requirement",{"type":45,"value":173},": This tool absolutely cannot search by sequence, name,\nor accession ID. 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The JSON is saved purely for subsequent, specialized\ntool use.",{"type":39,"tag":52,"props":221,"children":222},{},[223,228],{"type":39,"tag":56,"props":224,"children":225},{},[226],{"type":45,"value":227},"No Raw Parsing",{"type":45,"value":229},": Do not attempt to parse or read the raw 3D coordinates\nyourself; always pass the file to the script.",{"type":39,"tag":52,"props":231,"children":232},{},[233,238],{"type":39,"tag":56,"props":234,"children":235},{},[236],{"type":45,"value":237},"Notification",{"type":45,"value":239},": If this skill is used, ensure this is mentioned in the\noutput.",{"type":39,"tag":40,"props":241,"children":243},{"id":242},"instructions",[244],{"type":45,"value":245},"Instructions",{"type":39,"tag":48,"props":247,"children":248},{},[249,298,397,423,468,480,497,540,579],{"type":39,"tag":52,"props":250,"children":251},{},[252,257,259,264,265,270,271,276,278],{"type":39,"tag":56,"props":253,"children":254},{},[255],{"type":45,"value":256},"Strict Input Validation:",{"type":45,"value":258}," Verify that the user has explicitly provided a\nvalid path to a ",{"type":39,"tag":60,"props":260,"children":262},{"className":261},[],[263],{"type":45,"value":127},{"type":45,"value":129},{"type":39,"tag":60,"props":266,"children":268},{"className":267},[],[269],{"type":45,"value":135},{"type":45,"value":137},{"type":39,"tag":60,"props":272,"children":274},{"className":273},[],[275],{"type":45,"value":143},{"type":45,"value":277}," file in their workspace.\n",{"type":39,"tag":161,"props":279,"children":280},{},[281,293],{"type":39,"tag":52,"props":282,"children":283},{},[284,286,291],{"type":45,"value":285},"If the user provided a protein name, an amino acid sequence, or an\naccession ID (e.g., a UniProt ID) but NO downloaded structure file,\n",{"type":39,"tag":56,"props":287,"children":288},{},[289],{"type":45,"value":290},"halt immediately",{"type":45,"value":292},". 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Inform the user that the database is unsupported\nand provide them with the allowed list.",{"type":39,"tag":52,"props":398,"children":399},{},[400,405,407,413,415,421],{"type":39,"tag":56,"props":401,"children":402},{},[403],{"type":45,"value":404},"Generate File Names:",{"type":45,"value":406}," Generate descriptive output file names for both the\nJSON data and the Markdown table based on the input file (e.g.,\n",{"type":39,"tag":60,"props":408,"children":410},{"className":409},[],[411],{"type":45,"value":412},"proteinA_foldseek_results.json",{"type":45,"value":414}," and ",{"type":39,"tag":60,"props":416,"children":418},{"className":417},[],[419],{"type":45,"value":420},"proteinA_foldseek_results.md",{"type":45,"value":422},").",{"type":39,"tag":52,"props":424,"children":425},{},[426,428,433,435],{"type":45,"value":427},"Execute the python script based on the user's request, redirecting the\nstandard output into your generated ",{"type":39,"tag":60,"props":429,"children":431},{"className":430},[],[432],{"type":45,"value":151},{"type":45,"value":434}," file:\n",{"type":39,"tag":161,"props":436,"children":437},{},[438,453],{"type":39,"tag":52,"props":439,"children":440},{},[441,446,447],{"type":39,"tag":56,"props":442,"children":443},{},[444],{"type":45,"value":445},"Default (No databases specified):",{"type":45,"value":320},{"type":39,"tag":60,"props":448,"children":450},{"className":449},[],[451],{"type":45,"value":452},"uv run scripts\u002Fsearch.py \u003Cpath-to-file> -o \u003Cgenerated-filename.json> > \u003Cgenerated-filename.md>",{"type":39,"tag":52,"props":454,"children":455},{},[456,461,462],{"type":39,"tag":56,"props":457,"children":458},{},[459],{"type":45,"value":460},"Custom (Valid databases specified):",{"type":45,"value":320},{"type":39,"tag":60,"props":463,"children":465},{"className":464},[],[466],{"type":45,"value":467},"uv run scripts\u002Fsearch.py \u003Cpath-to-file> -o \u003Cgenerated-filename.json> --databases \u003Cdb1,db2,db3> > \u003Cgenerated-filename.md>",{"type":39,"tag":52,"props":469,"children":470},{},[471,473,478],{"type":45,"value":472},"The script will query the databases, save the full JSON payload, and write a\nMarkdown-formatted table to your specified ",{"type":39,"tag":60,"props":474,"children":476},{"className":475},[],[477],{"type":45,"value":151},{"type":45,"value":479}," file.",{"type":39,"tag":52,"props":481,"children":482},{},[483,488,490,495],{"type":39,"tag":56,"props":484,"children":485},{},[486],{"type":45,"value":487},"Read the Results:",{"type":45,"value":489}," Open and read the newly generated ",{"type":39,"tag":60,"props":491,"children":493},{"className":492},[],[494],{"type":45,"value":151},{"type":45,"value":496}," file carefully\nto view the Markdown table.",{"type":39,"tag":52,"props":498,"children":499},{},[500,505,507],{"type":39,"tag":56,"props":501,"children":502},{},[503],{"type":45,"value":504},"Interpret the Metrics:",{"type":45,"value":506}," Summarize the top 3 to 5 structural matches that\nhave meaningfull annotations for the user. When reporting, assess the match\nquality using these specific fields:\n",{"type":39,"tag":161,"props":508,"children":509},{},[510,520,530],{"type":39,"tag":52,"props":511,"children":512},{},[513,518],{"type":39,"tag":56,"props":514,"children":515},{},[516],{"type":45,"value":517},"Prob (Probability):",{"type":45,"value":519}," Values approaching 1.0 (100%) indicate extreme\nconfidence that the fold is a true structural homologue.",{"type":39,"tag":52,"props":521,"children":522},{},[523,528],{"type":39,"tag":56,"props":524,"children":525},{},[526],{"type":45,"value":527},"Q-Cov (Query Coverage):",{"type":45,"value":529}," High percentages mean the match covers the\nmajority of the query protein's overall shape, rather than just a small\nlocal motif.",{"type":39,"tag":52,"props":531,"children":532},{},[533,538],{"type":39,"tag":56,"props":534,"children":535},{},[536],{"type":45,"value":537},"E-value & Seq Identity:",{"type":45,"value":539}," Use these to provide additional evolutionary\ncontext.",{"type":39,"tag":52,"props":541,"children":542},{},[543,548,550,556,558],{"type":39,"tag":56,"props":544,"children":545},{},[546],{"type":45,"value":547},"Perform Functional Analysis:",{"type":45,"value":549}," Analyze the text descriptions embedded\nwithin the ",{"type":39,"tag":60,"props":551,"children":553},{"className":552},[],[554],{"type":45,"value":555},"Target ID",{"type":45,"value":557}," column for the reported matches.\n",{"type":39,"tag":161,"props":559,"children":560},{},[561,566],{"type":39,"tag":52,"props":562,"children":563},{},[564],{"type":45,"value":565},"Explicitly report the specific protein names\u002Ffunctions of the top\nstructural homologues.",{"type":39,"tag":52,"props":567,"children":568},{},[569,571,577],{"type":45,"value":570},"Provide a synthesized overview summarizing the entire ",{"type":39,"tag":572,"props":573,"children":574},"em",{},[575],{"type":45,"value":576},"variety",{"type":45,"value":578}," of\ndifferent functions, domains, or protein families found across the whole\nlist of homologues (e.g., \"Most hits are portal proteins, but there is\nalso a distinct cluster of viral capsid matches...\").",{"type":39,"tag":52,"props":580,"children":581},{},[582,584,590,591,596],{"type":45,"value":583},"Explicitly inform the user of both newly created files (",{"type":39,"tag":60,"props":585,"children":587},{"className":586},[],[588],{"type":45,"value":589},".json",{"type":45,"value":414},{"type":39,"tag":60,"props":592,"children":594},{"className":593},[],[595],{"type":45,"value":151},{"type":45,"value":597},")\nand their locations so they can be seamlessly used in subsequent analysis\nsteps.",{"type":39,"tag":40,"props":599,"children":601},{"id":600},"if-the-api-returns-an-error-or-the-file-is-missing-inform-the-user-clearly",[602],{"type":45,"value":603},"* If the API returns an error or the file is missing, inform the user clearly",{"type":39,"tag":117,"props":605,"children":606},{},[607],{"type":45,"value":608},"and ask them to verify the file path.",{"items":610,"total":770},[611,624,639,659,671,686,702,715,727,742,753,759],{"slug":612,"name":612,"fn":613,"description":614,"org":615,"tags":616,"stars":22,"repoUrl":23,"updatedAt":623},"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},[617,618,621,622],{"name":20,"slug":21,"type":15},{"name":619,"slug":620,"type":15},"Genomics","genomics",{"name":17,"slug":18,"type":15},{"name":13,"slug":14,"type":15},"2026-07-12T07:51:51.827211",{"slug":625,"name":625,"fn":626,"description":627,"org":628,"tags":629,"stars":22,"repoUrl":23,"updatedAt":638},"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},[630,631,634,635],{"name":20,"slug":21,"type":15},{"name":632,"slug":633,"type":15},"Genetics","genetics",{"name":13,"slug":14,"type":15},{"name":636,"slug":637,"type":15},"RNA-seq","rna-seq","2026-07-12T07:51:39.494803",{"slug":640,"name":640,"fn":641,"description":642,"org":643,"tags":644,"stars":22,"repoUrl":23,"updatedAt":658},"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},[645,648,651,654,657],{"name":646,"slug":647,"type":15},"ChEMBL","chembl",{"name":649,"slug":650,"type":15},"Chemistry","chemistry",{"name":652,"slug":653,"type":15},"Database","database",{"name":655,"slug":656,"type":15},"Pharmacology","pharmacology",{"name":13,"slug":14,"type":15},"2026-07-12T07:51:35.544306",{"slug":660,"name":660,"fn":661,"description":662,"org":663,"tags":664,"stars":22,"repoUrl":23,"updatedAt":670},"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},[665,668,669],{"name":666,"slug":667,"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":672,"name":672,"fn":673,"description":674,"org":675,"tags":676,"stars":22,"repoUrl":23,"updatedAt":685},"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},[677,680,681,684],{"name":678,"slug":679,"type":15},"ClinVar","clinvar",{"name":632,"slug":633,"type":15},{"name":682,"slug":683,"type":15},"Healthcare","healthcare",{"name":13,"slug":14,"type":15},"2026-07-12T07:51:36.86094",{"slug":687,"name":687,"fn":688,"description":689,"org":690,"tags":691,"stars":22,"repoUrl":23,"updatedAt":701},"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},[692,695,698],{"name":693,"slug":694,"type":15},"Compliance","compliance",{"name":696,"slug":697,"type":15},"Operations","operations",{"name":699,"slug":700,"type":15},"Security","security","2026-07-12T07:52:17.355491",{"slug":703,"name":703,"fn":704,"description":705,"org":706,"tags":707,"stars":22,"repoUrl":23,"updatedAt":714},"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},[708,709,710,713],{"name":20,"slug":21,"type":15},{"name":632,"slug":633,"type":15},{"name":711,"slug":712,"type":15},"NCBI","ncbi",{"name":13,"slug":14,"type":15},"2026-07-12T07:51:33.054229",{"slug":716,"name":716,"fn":717,"description":718,"org":719,"tags":720,"stars":22,"repoUrl":23,"updatedAt":726},"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},[721,722,725],{"name":20,"slug":21,"type":15},{"name":723,"slug":724,"type":15},"Ontology","ontology",{"name":13,"slug":14,"type":15},"2026-07-12T07:51:59.368324",{"slug":728,"name":728,"fn":729,"description":730,"org":731,"tags":732,"stars":22,"repoUrl":23,"updatedAt":741},"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},[733,734,737,738],{"name":20,"slug":21,"type":15},{"name":735,"slug":736,"type":15},"GraphQL","graphql",{"name":13,"slug":14,"type":15},{"name":739,"slug":740,"type":15},"REST API","rest-api","2026-07-12T07:52:10.597139",{"slug":743,"name":743,"fn":744,"description":745,"org":746,"tags":747,"stars":22,"repoUrl":23,"updatedAt":752},"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},[748,749,750,751],{"name":20,"slug":21,"type":15},{"name":632,"slug":633,"type":15},{"name":17,"slug":18,"type":15},{"name":13,"slug":14,"type":15},"2026-07-12T07:51:41.645835",{"slug":4,"name":4,"fn":5,"description":6,"org":754,"tags":755,"stars":22,"repoUrl":23,"updatedAt":24},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[756,757,758],{"name":20,"slug":21,"type":15},{"name":17,"slug":18,"type":15},{"name":13,"slug":14,"type":15},{"slug":760,"name":760,"fn":761,"description":762,"org":763,"tags":764,"stars":22,"repoUrl":23,"updatedAt":769},"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},[765,766,767,768],{"name":20,"slug":21,"type":15},{"name":632,"slug":633,"type":15},{"name":17,"slug":18,"type":15},{"name":13,"slug":14,"type":15},"2026-07-12T07:51:38.213009",38,{"items":772,"total":770},[773,780,787,795,801,808,814],{"slug":612,"name":612,"fn":613,"description":614,"org":774,"tags":775,"stars":22,"repoUrl":23,"updatedAt":623},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[776,777,778,779],{"name":20,"slug":21,"type":15},{"name":619,"slug":620,"type":15},{"name":17,"slug":18,"type":15},{"name":13,"slug":14,"type":15},{"slug":625,"name":625,"fn":626,"description":627,"org":781,"tags":782,"stars":22,"repoUrl":23,"updatedAt":638},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[783,784,785,786],{"name":20,"slug":21,"type":15},{"name":632,"slug":633,"type":15},{"name":13,"slug":14,"type":15},{"name":636,"slug":637,"type":15},{"slug":640,"name":640,"fn":641,"description":642,"org":788,"tags":789,"stars":22,"repoUrl":23,"updatedAt":658},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[790,791,792,793,794],{"name":646,"slug":647,"type":15},{"name":649,"slug":650,"type":15},{"name":652,"slug":653,"type":15},{"name":655,"slug":656,"type":15},{"name":13,"slug":14,"type":15},{"slug":660,"name":660,"fn":661,"description":662,"org":796,"tags":797,"stars":22,"repoUrl":23,"updatedAt":670},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[798,799,800],{"name":666,"slug":667,"type":15},{"name":17,"slug":18,"type":15},{"name":13,"slug":14,"type":15},{"slug":672,"name":672,"fn":673,"description":674,"org":802,"tags":803,"stars":22,"repoUrl":23,"updatedAt":685},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[804,805,806,807],{"name":678,"slug":679,"type":15},{"name":632,"slug":633,"type":15},{"name":682,"slug":683,"type":15},{"name":13,"slug":14,"type":15},{"slug":687,"name":687,"fn":688,"description":689,"org":809,"tags":810,"stars":22,"repoUrl":23,"updatedAt":701},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[811,812,813],{"name":693,"slug":694,"type":15},{"name":696,"slug":697,"type":15},{"name":699,"slug":700,"type":15},{"slug":703,"name":703,"fn":704,"description":705,"org":815,"tags":816,"stars":22,"repoUrl":23,"updatedAt":714},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[817,818,819,820],{"name":20,"slug":21,"type":15},{"name":632,"slug":633,"type":15},{"name":711,"slug":712,"type":15},{"name":13,"slug":14,"type":15}]