[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-google-deepmind-alphafold-database-fetch-and-analyze":3,"mdc--g5ik4-key":36,"related-org-google-deepmind-alphafold-database-fetch-and-analyze":532,"related-repo-google-deepmind-alphafold-database-fetch-and-analyze":692},{"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},"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},"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},"Genomics","genomics",2333,"https:\u002F\u002Fgithub.com\u002Fgoogle-deepmind\u002Fscience-skills","2026-07-12T07:51:51.827211",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\u002Falphafold_database_fetch_and_analyze","---\nname: alphafold-database-fetch-and-analyze\ndescription: >\n  Retrieve and analyze AlphaFold predicted structures for a protein. Use when\n  the user provides a specific UniProt Accession ID and wants structural\n  confidence metrics (pLDDT), domain boundary analysis, or disorder\n  assessment. Do not use if the user only has a protein name, gene name,\n  or amino acid sequence — ask for a UniProt ID first.\n---\n\n# AlphaFold Database: Fetch and Analyze\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\n    .licenses\u002Falphafold_database_fetch_and_analyze_LICENSE.txt does not already\n    exist in the workspace root directory then (1) prominently notify the user\n    to check the terms at https:\u002F\u002Falphafold.ebi.ac.uk\u002F, then (2) create the file\n    recording the notification text and timestamp.\n\n## Overview\n\nDownloads AlphaFold predicted structures (mmCIF) and Predicted Aligned Error\n(PAE) matrices from the AlphaFold Database for a given UniProt ID, then performs\nautomated heuristic analysis on structural confidence (pLDDT), intrinsically\ndisordered regions, rigid domain boundaries, and inter-domain flexibility.\n\n**Do NOT use when:**\n\n-   The user only has a protein name, gene name, or amino acid sequence (no\n    UniProt ID) — ask them to look up the ID on\n    [UniProt](https:\u002F\u002Fwww.uniprot.org).\n-   The user wants to search for structural homologs (use **Foldseek**).\n-   The user wants to run AlphaFold predictions on a custom sequence.\n-   The user needs experimental PDB structures (use **RCSB PDB**).\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 required rate limit gracefully.\n-   Do not attempt to calculate domain boundaries or assess structural disorder\n    yourself; always rely on the output provided by the script.\n-   If this skill is used, ensure this is mentioned in the output.\n\n## Utility Scripts\n\n**1. Fetch Structure Files**\n\nDownloads the `.cif` structure file, `_predicted_aligned_error.json`, and API\nmetadata JSON (`-metadata.json`) for a UniProt ID. Handles fragment fallback for\nvery large proteins.\n\nExamples:\n\n```bash\nuv run scripts\u002Ffetch_structure.py P00520 -o \u002Fpath\u002Fto\u002Foutput\u002F\nuv run scripts\u002Ffetch_structure.py P04637 -o \u002Fpath\u002Fto\u002Fcustom_results\u002F\n```\n\nAlways specify `-o` with an absolute path or a path relative to the user's\nproject root, never a path relative to the skill directory.\n\n**2. Analyze pLDDT Confidence**\n\nReads pLDDT confidence metrics from a saved AFDB metadata JSON file (produced by\n`fetch_structure.py`) and prints a heuristic confidence assessment (structured,\ndisordered, mixed).\n\nExample:\n\n```bash\nuv run scripts\u002Fanalyze_plddt.py .\u002Fdata\u002FAF-P00520-F1-metadata.json\n```\n\n**3. Analyze PAE \u002F Domain Boundaries**\n\nReads a downloaded PAE JSON file and detects rigid domain boundaries using a\nsliding-window PAE heuristic.\n\nExample:\n\n```bash\nuv run scripts\u002Fanalyze_pae.py .\u002Fdata\u002FAF-P00520-F1-predicted_aligned_error_v6.json\n```\n\n## Interpreting the Output\n\nThe script prints analysis to stdout. Read it carefully and synthesize the\nresults for the user:\n\n1.  **Isoform \u002F Large Protein Warning (MANDATORY):** Check the script output for\n    any `[!] WARNING` lines. If the script reports that no canonical entry was\n    found and an isoform was used, or if the protein is very large (>2700 AAs),\n    you **MUST** prominently relay this warning to the user. Do not omit this\n    warning.\n2.  **Synthesize the Structural Analysis**: Combine the \"pLDDT Conclusion\" and\n    the \"PAE Structural Conclusion\" into a single, cohesive overall summary.\n    Describe the protein's overall folding confidence, the presence of\n    disordered regions, and its rigid domain layout.\n3.  Highlight the supporting metrics:\n    -   Overall Global pLDDT and the breakdown of fraction confidence\n        (especially Very Low vs. Very High).\n    -   Domain Boundary Analysis (number of distinct global domains and their\n        specific residue ranges).\n4.  **Explicit Disorder Warning:** If the analysis concludes that the protein is\n    highly intrinsically disordered (e.g., high fraction of \u003C50 pLDDT or lack of\n    rigid domains), issue a separate, prominent warning. Advise the user against\n    proceeding with whole-protein downstream structural analysis (like Foldseek\n    or docking). If small ordered domains exist amidst the disorder, advise the\n    user to restrict any future analysis strictly to those specific residue\n    boundaries.\n5.  Remind the user that per-residue pLDDT is embedded in the B-factor column of\n    the downloaded mmCIF file.\n",{"data":37,"body":38},{"name":4,"description":6},{"type":39,"children":40},"root",[41,49,56,111,117,123,131,177,183,206,212,220,249,254,332,345,353,366,371,399,407,412,416,444,450,455,526],{"type":42,"tag":43,"props":44,"children":45},"element","h1",{"id":4},[46],{"type":47,"value":48},"text","AlphaFold Database: Fetch and Analyze",{"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],{"type":42,"tag":65,"props":95,"children":96},{},[97],{"type":47,"value":98},"User Notification",{"type":47,"value":100},": If\n.licenses\u002Falphafold_database_fetch_and_analyze_LICENSE.txt does not already\nexist in the workspace root directory then (1) prominently notify the user\nto check the terms at ",{"type":42,"tag":102,"props":103,"children":107},"a",{"href":104,"rel":105},"https:\u002F\u002Falphafold.ebi.ac.uk\u002F",[106],"nofollow",[108],{"type":47,"value":104},{"type":47,"value":110},", then (2) create the file\nrecording the notification text and timestamp.",{"type":42,"tag":50,"props":112,"children":114},{"id":113},"overview",[115],{"type":47,"value":116},"Overview",{"type":42,"tag":118,"props":119,"children":120},"p",{},[121],{"type":47,"value":122},"Downloads AlphaFold predicted structures (mmCIF) and Predicted Aligned Error\n(PAE) matrices from the AlphaFold Database for a given UniProt ID, then performs\nautomated heuristic analysis on structural confidence (pLDDT), intrinsically\ndisordered regions, rigid domain boundaries, and inter-domain flexibility.",{"type":42,"tag":118,"props":124,"children":125},{},[126],{"type":42,"tag":65,"props":127,"children":128},{},[129],{"type":47,"value":130},"Do NOT use when:",{"type":42,"tag":132,"props":133,"children":134},"ul",{},[135,149,161,166],{"type":42,"tag":61,"props":136,"children":137},{},[138,140,147],{"type":47,"value":139},"The user only has a protein name, gene name, or amino acid sequence (no\nUniProt ID) — ask them to look up the ID on\n",{"type":42,"tag":102,"props":141,"children":144},{"href":142,"rel":143},"https:\u002F\u002Fwww.uniprot.org",[106],[145],{"type":47,"value":146},"UniProt",{"type":47,"value":148},".",{"type":42,"tag":61,"props":150,"children":151},{},[152,154,159],{"type":47,"value":153},"The user wants to search for structural homologs (use ",{"type":42,"tag":65,"props":155,"children":156},{},[157],{"type":47,"value":158},"Foldseek",{"type":47,"value":160},").",{"type":42,"tag":61,"props":162,"children":163},{},[164],{"type":47,"value":165},"The user wants to run AlphaFold predictions on a custom sequence.",{"type":42,"tag":61,"props":167,"children":168},{},[169,171,176],{"type":47,"value":170},"The user needs experimental PDB structures (use ",{"type":42,"tag":65,"props":172,"children":173},{},[174],{"type":47,"value":175},"RCSB PDB",{"type":47,"value":160},{"type":42,"tag":50,"props":178,"children":180},{"id":179},"core-rules",[181],{"type":47,"value":182},"Core Rules",{"type":42,"tag":132,"props":184,"children":185},{},[186,196,201],{"type":42,"tag":61,"props":187,"children":188},{},[189,194],{"type":42,"tag":65,"props":190,"children":191},{},[192],{"type":47,"value":193},"Use the Wrapper",{"type":47,"value":195},": ALWAYS execute the provided helper scripts to query the\ndatabase rather than accessing the database directly. The scripts\nautomatically enforce the required rate limit gracefully.",{"type":42,"tag":61,"props":197,"children":198},{},[199],{"type":47,"value":200},"Do not attempt to calculate domain boundaries or assess structural disorder\nyourself; always rely on the output provided by the script.",{"type":42,"tag":61,"props":202,"children":203},{},[204],{"type":47,"value":205},"If this skill is used, ensure this is mentioned in the output.",{"type":42,"tag":50,"props":207,"children":209},{"id":208},"utility-scripts",[210],{"type":47,"value":211},"Utility Scripts",{"type":42,"tag":118,"props":213,"children":214},{},[215],{"type":42,"tag":65,"props":216,"children":217},{},[218],{"type":47,"value":219},"1. 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Handles fragment fallback for\nvery large proteins.",{"type":42,"tag":118,"props":250,"children":251},{},[252],{"type":47,"value":253},"Examples:",{"type":42,"tag":255,"props":256,"children":261},"pre",{"className":257,"code":258,"language":259,"meta":260,"style":260},"language-bash shiki shiki-themes material-theme-lighter material-theme material-theme-palenight","uv run scripts\u002Ffetch_structure.py P00520 -o \u002Fpath\u002Fto\u002Foutput\u002F\nuv run scripts\u002Ffetch_structure.py P04637 -o \u002Fpath\u002Fto\u002Fcustom_results\u002F\n","bash","",[262],{"type":42,"tag":69,"props":263,"children":264},{"__ignoreMap":260},[265,302],{"type":42,"tag":266,"props":267,"children":270},"span",{"class":268,"line":269},"line",1,[271,276,282,287,292,297],{"type":42,"tag":266,"props":272,"children":274},{"style":273},"--shiki-light:#E2931D;--shiki-default:#FFCB6B;--shiki-dark:#FFCB6B",[275],{"type":47,"value":74},{"type":42,"tag":266,"props":277,"children":279},{"style":278},"--shiki-light:#91B859;--shiki-default:#C3E88D;--shiki-dark:#C3E88D",[280],{"type":47,"value":281}," run",{"type":42,"tag":266,"props":283,"children":284},{"style":278},[285],{"type":47,"value":286}," scripts\u002Ffetch_structure.py",{"type":42,"tag":266,"props":288,"children":289},{"style":278},[290],{"type":47,"value":291}," P00520",{"type":42,"tag":266,"props":293,"children":294},{"style":278},[295],{"type":47,"value":296}," -o",{"type":42,"tag":266,"props":298,"children":299},{"style":278},[300],{"type":47,"value":301}," \u002Fpath\u002Fto\u002Foutput\u002F\n",{"type":42,"tag":266,"props":303,"children":305},{"class":268,"line":304},2,[306,310,314,318,323,327],{"type":42,"tag":266,"props":307,"children":308},{"style":273},[309],{"type":47,"value":74},{"type":42,"tag":266,"props":311,"children":312},{"style":278},[313],{"type":47,"value":281},{"type":42,"tag":266,"props":315,"children":316},{"style":278},[317],{"type":47,"value":286},{"type":42,"tag":266,"props":319,"children":320},{"style":278},[321],{"type":47,"value":322}," P04637",{"type":42,"tag":266,"props":324,"children":325},{"style":278},[326],{"type":47,"value":296},{"type":42,"tag":266,"props":328,"children":329},{"style":278},[330],{"type":47,"value":331}," \u002Fpath\u002Fto\u002Fcustom_results\u002F\n",{"type":42,"tag":118,"props":333,"children":334},{},[335,337,343],{"type":47,"value":336},"Always specify ",{"type":42,"tag":69,"props":338,"children":340},{"className":339},[],[341],{"type":47,"value":342},"-o",{"type":47,"value":344}," with an absolute path or a path relative to the user's\nproject root, never a path relative to the skill directory.",{"type":42,"tag":118,"props":346,"children":347},{},[348],{"type":42,"tag":65,"props":349,"children":350},{},[351],{"type":47,"value":352},"2. Analyze pLDDT Confidence",{"type":42,"tag":118,"props":354,"children":355},{},[356,358,364],{"type":47,"value":357},"Reads pLDDT confidence metrics from a saved AFDB metadata JSON file (produced by\n",{"type":42,"tag":69,"props":359,"children":361},{"className":360},[],[362],{"type":47,"value":363},"fetch_structure.py",{"type":47,"value":365},") and prints a heuristic confidence assessment (structured,\ndisordered, mixed).",{"type":42,"tag":118,"props":367,"children":368},{},[369],{"type":47,"value":370},"Example:",{"type":42,"tag":255,"props":372,"children":374},{"className":257,"code":373,"language":259,"meta":260,"style":260},"uv run scripts\u002Fanalyze_plddt.py .\u002Fdata\u002FAF-P00520-F1-metadata.json\n",[375],{"type":42,"tag":69,"props":376,"children":377},{"__ignoreMap":260},[378],{"type":42,"tag":266,"props":379,"children":380},{"class":268,"line":269},[381,385,389,394],{"type":42,"tag":266,"props":382,"children":383},{"style":273},[384],{"type":47,"value":74},{"type":42,"tag":266,"props":386,"children":387},{"style":278},[388],{"type":47,"value":281},{"type":42,"tag":266,"props":390,"children":391},{"style":278},[392],{"type":47,"value":393}," scripts\u002Fanalyze_plddt.py",{"type":42,"tag":266,"props":395,"children":396},{"style":278},[397],{"type":47,"value":398}," .\u002Fdata\u002FAF-P00520-F1-metadata.json\n",{"type":42,"tag":118,"props":400,"children":401},{},[402],{"type":42,"tag":65,"props":403,"children":404},{},[405],{"type":47,"value":406},"3. Analyze PAE \u002F Domain Boundaries",{"type":42,"tag":118,"props":408,"children":409},{},[410],{"type":47,"value":411},"Reads a downloaded PAE JSON file and detects rigid domain boundaries using a\nsliding-window PAE heuristic.",{"type":42,"tag":118,"props":413,"children":414},{},[415],{"type":47,"value":370},{"type":42,"tag":255,"props":417,"children":419},{"className":257,"code":418,"language":259,"meta":260,"style":260},"uv run scripts\u002Fanalyze_pae.py .\u002Fdata\u002FAF-P00520-F1-predicted_aligned_error_v6.json\n",[420],{"type":42,"tag":69,"props":421,"children":422},{"__ignoreMap":260},[423],{"type":42,"tag":266,"props":424,"children":425},{"class":268,"line":269},[426,430,434,439],{"type":42,"tag":266,"props":427,"children":428},{"style":273},[429],{"type":47,"value":74},{"type":42,"tag":266,"props":431,"children":432},{"style":278},[433],{"type":47,"value":281},{"type":42,"tag":266,"props":435,"children":436},{"style":278},[437],{"type":47,"value":438}," scripts\u002Fanalyze_pae.py",{"type":42,"tag":266,"props":440,"children":441},{"style":278},[442],{"type":47,"value":443}," .\u002Fdata\u002FAF-P00520-F1-predicted_aligned_error_v6.json\n",{"type":42,"tag":50,"props":445,"children":447},{"id":446},"interpreting-the-output",[448],{"type":47,"value":449},"Interpreting the Output",{"type":42,"tag":118,"props":451,"children":452},{},[453],{"type":47,"value":454},"The script prints analysis to stdout. Read it carefully and synthesize the\nresults for the user:",{"type":42,"tag":57,"props":456,"children":457},{},[458,483,493,511,521],{"type":42,"tag":61,"props":459,"children":460},{},[461,466,468,474,476,481],{"type":42,"tag":65,"props":462,"children":463},{},[464],{"type":47,"value":465},"Isoform \u002F Large Protein Warning (MANDATORY):",{"type":47,"value":467}," Check the script output for\nany ",{"type":42,"tag":69,"props":469,"children":471},{"className":470},[],[472],{"type":47,"value":473},"[!] WARNING",{"type":47,"value":475}," lines. If the script reports that no canonical entry was\nfound and an isoform was used, or if the protein is very large (>2700 AAs),\nyou ",{"type":42,"tag":65,"props":477,"children":478},{},[479],{"type":47,"value":480},"MUST",{"type":47,"value":482}," prominently relay this warning to the user. 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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},[547,548,551,552],{"name":20,"slug":21,"type":15},{"name":549,"slug":550,"type":15},"Genetics","genetics",{"name":13,"slug":14,"type":15},{"name":553,"slug":554,"type":15},"RNA-seq","rna-seq","2026-07-12T07:51:39.494803",{"slug":557,"name":557,"fn":558,"description":559,"org":560,"tags":561,"stars":25,"repoUrl":26,"updatedAt":575},"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},[562,565,568,571,574],{"name":563,"slug":564,"type":15},"ChEMBL","chembl",{"name":566,"slug":567,"type":15},"Chemistry","chemistry",{"name":569,"slug":570,"type":15},"Database","database",{"name":572,"slug":573,"type":15},"Pharmacology","pharmacology",{"name":13,"slug":14,"type":15},"2026-07-12T07:51:35.544306",{"slug":577,"name":577,"fn":578,"description":579,"org":580,"tags":581,"stars":25,"repoUrl":26,"updatedAt":587},"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},[582,585,586],{"name":583,"slug":584,"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":589,"name":589,"fn":590,"description":591,"org":592,"tags":593,"stars":25,"repoUrl":26,"updatedAt":602},"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},[594,597,598,601],{"name":595,"slug":596,"type":15},"ClinVar","clinvar",{"name":549,"slug":550,"type":15},{"name":599,"slug":600,"type":15},"Healthcare","healthcare",{"name":13,"slug":14,"type":15},"2026-07-12T07:51:36.86094",{"slug":604,"name":604,"fn":605,"description":606,"org":607,"tags":608,"stars":25,"repoUrl":26,"updatedAt":618},"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},[609,612,615],{"name":610,"slug":611,"type":15},"Compliance","compliance",{"name":613,"slug":614,"type":15},"Operations","operations",{"name":616,"slug":617,"type":15},"Security","security","2026-07-12T07:52:17.355491",{"slug":620,"name":620,"fn":621,"description":622,"org":623,"tags":624,"stars":25,"repoUrl":26,"updatedAt":631},"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},[625,626,627,630],{"name":20,"slug":21,"type":15},{"name":549,"slug":550,"type":15},{"name":628,"slug":629,"type":15},"NCBI","ncbi",{"name":13,"slug":14,"type":15},"2026-07-12T07:51:33.054229",{"slug":633,"name":633,"fn":634,"description":635,"org":636,"tags":637,"stars":25,"repoUrl":26,"updatedAt":643},"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},[638,639,642],{"name":20,"slug":21,"type":15},{"name":640,"slug":641,"type":15},"Ontology","ontology",{"name":13,"slug":14,"type":15},"2026-07-12T07:51:59.368324",{"slug":645,"name":645,"fn":646,"description":647,"org":648,"tags":649,"stars":25,"repoUrl":26,"updatedAt":658},"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},[650,651,654,655],{"name":20,"slug":21,"type":15},{"name":652,"slug":653,"type":15},"GraphQL","graphql",{"name":13,"slug":14,"type":15},{"name":656,"slug":657,"type":15},"REST API","rest-api","2026-07-12T07:52:10.597139",{"slug":660,"name":660,"fn":661,"description":662,"org":663,"tags":664,"stars":25,"repoUrl":26,"updatedAt":669},"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},[665,666,667,668],{"name":20,"slug":21,"type":15},{"name":549,"slug":550,"type":15},{"name":17,"slug":18,"type":15},{"name":13,"slug":14,"type":15},"2026-07-12T07:51:41.645835",{"slug":671,"name":671,"fn":672,"description":673,"org":674,"tags":675,"stars":25,"repoUrl":26,"updatedAt":679},"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},[676,677,678],{"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":681,"name":681,"fn":682,"description":683,"org":684,"tags":685,"stars":25,"repoUrl":26,"updatedAt":690},"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},[686,687,688,689],{"name":20,"slug":21,"type":15},{"name":549,"slug":550,"type":15},{"name":17,"slug":18,"type":15},{"name":13,"slug":14,"type":15},"2026-07-12T07:51:38.213009",38,{"items":693,"total":691},[694,701,708,716,722,729,735],{"slug":4,"name":4,"fn":5,"description":6,"org":695,"tags":696,"stars":25,"repoUrl":26,"updatedAt":27},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[697,698,699,700],{"name":20,"slug":21,"type":15},{"name":23,"slug":24,"type":15},{"name":17,"slug":18,"type":15},{"name":13,"slug":14,"type":15},{"slug":542,"name":542,"fn":543,"description":544,"org":702,"tags":703,"stars":25,"repoUrl":26,"updatedAt":555},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[704,705,706,707],{"name":20,"slug":21,"type":15},{"name":549,"slug":550,"type":15},{"name":13,"slug":14,"type":15},{"name":553,"slug":554,"type":15},{"slug":557,"name":557,"fn":558,"description":559,"org":709,"tags":710,"stars":25,"repoUrl":26,"updatedAt":575},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[711,712,713,714,715],{"name":563,"slug":564,"type":15},{"name":566,"slug":567,"type":15},{"name":569,"slug":570,"type":15},{"name":572,"slug":573,"type":15},{"name":13,"slug":14,"type":15},{"slug":577,"name":577,"fn":578,"description":579,"org":717,"tags":718,"stars":25,"repoUrl":26,"updatedAt":587},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[719,720,721],{"name":583,"slug":584,"type":15},{"name":17,"slug":18,"type":15},{"name":13,"slug":14,"type":15},{"slug":589,"name":589,"fn":590,"description":591,"org":723,"tags":724,"stars":25,"repoUrl":26,"updatedAt":602},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[725,726,727,728],{"name":595,"slug":596,"type":15},{"name":549,"slug":550,"type":15},{"name":599,"slug":600,"type":15},{"name":13,"slug":14,"type":15},{"slug":604,"name":604,"fn":605,"description":606,"org":730,"tags":731,"stars":25,"repoUrl":26,"updatedAt":618},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[732,733,734],{"name":610,"slug":611,"type":15},{"name":613,"slug":614,"type":15},{"name":616,"slug":617,"type":15},{"slug":620,"name":620,"fn":621,"description":622,"org":736,"tags":737,"stars":25,"repoUrl":26,"updatedAt":631},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[738,739,740,741],{"name":20,"slug":21,"type":15},{"name":549,"slug":550,"type":15},{"name":628,"slug":629,"type":15},{"name":13,"slug":14,"type":15}]