[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-google-deepmind-chembl-database":3,"mdc-evd2ar-key":39,"related-org-google-deepmind-chembl-database":1970,"related-repo-google-deepmind-chembl-database":2128},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":11,"stars":28,"repoUrl":29,"updatedAt":30,"license":31,"forks":32,"topics":33,"repo":34,"sourceUrl":37,"mdContent":38},"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},"google-deepmind","Google DeepMind","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Fgoogle-deepmind.png",[12,16,19,22,25],{"name":13,"slug":14,"type":15},"Research","research","tag",{"name":17,"slug":18,"type":15},"Pharmacology","pharmacology",{"name":20,"slug":21,"type":15},"Database","database",{"name":23,"slug":24,"type":15},"ChEMBL","chembl",{"name":26,"slug":27,"type":15},"Chemistry","chemistry",2333,"https:\u002F\u002Fgithub.com\u002Fgoogle-deepmind\u002Fscience-skills","2026-07-12T07:51:35.544306",null,234,[],{"repoUrl":29,"stars":28,"forks":32,"topics":35,"description":36},[],"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\u002Fchembl_database","---\nname: chembl-database\ndescription: >\n  Query the ChEMBL database for bioactive molecules, drug targets, bioactivity\n  data, approved drugs, and chemical structures. Use when the user asks about\n  compounds, targets, IC50\u002FKi values, drug mechanisms, or structure searches.\n---\n\n# ChEMBL Database Query\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\u002Fchembl_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\n    https:\u002F\u002Fchembl.gitbook.io\u002Fchembl-interface-documentation\u002Fabout, then (2)\n    create the file recording the notification text and timestamp.\n\n## Core Rules\n\n-   [!IMPORTANT] **Use the Utility Scripts**: You MUST ALWAYS use the provided\n    utility script `scripts\u002Fchembl_api.py` for all ChEMBL API interactions,\n    including checking status. NEVER use `curl` or custom Python requests to\n    query the ChEMBL API directly. This ensures rate limit is enfoced and also\n    retries on network errors.\n\n-   **Output to File (Required)**: The `--output` flag is **required** for every\n    subcommand. All JSON results are written to the specified file. After\n    running the command, read the output file with jq or your own code to\n    extract the data. List results are typically wrapped in a JSON array keyed\n    by the endpoint name (e.g., `molecules`, `activities`).\n\n-   **Notification**: If this skill is used, ensure this is mentioned in the\n    output.\n\n## Utility Script\n\nAll ChEMBL API queries use one script with subcommands:\n\n```bash\nuv run scripts\u002Fchembl_api.py \u003Csubcommand> --output \u003Cfile> [options]\n```\n\n--------------------------------------------------------------------------------\n\n### 1. Check API Status\n\n```bash\nuv run scripts\u002Fchembl_api.py status --output \u002Ftmp\u002Fstatus.json\n```\n\n--------------------------------------------------------------------------------\n\n### 2. Molecule Queries\n\n**Fetch by ChEMBL ID:** `bash uv run scripts\u002Fchembl_api.py molecule --id\nCHEMBL25 --output \u002Ftmp\u002Fmol.json`\n\n**Search by name:** `bash uv run scripts\u002Fchembl_api.py molecule --search\n\"aspirin\" --limit 3 --output \u002Ftmp\u002Fmol_search.json`\n\n**Batch fetch:** `bash uv run scripts\u002Fchembl_api.py molecule --ids\n\"CHEMBL25;CHEMBL1642\" --limit 10 --output \u002Ftmp\u002Fmol_batch.json`\n\n**Filter by properties:** `bash uv run scripts\u002Fchembl_api.py molecule --filter\nmolecule_properties__mw_freebase__lte=500 --limit 5 --output\n\u002Ftmp\u002Fmol_filter.json`\n\n**Filter by range:** `bash uv run scripts\u002Fchembl_api.py molecule --filter\nmolecule_properties__mw_freebase__range=150,200 --limit 5 --output\n\u002Ftmp\u002Fmol_range.json`\n\n**Download SDF structure file:** `bash uv run scripts\u002Fchembl_api.py molecule\n--id CHEMBL25 --dl_format sdf --output \u002Ftmp\u002Faspirin.sdf`\n\n> **Tip**: SDF\u002FMOL files can be passed directly to tools like PyMOL or RDKit for\n> 3D visualization and analysis.\n\n--------------------------------------------------------------------------------\n\n### 3. Target Queries\n\n**Search for targets:** `bash uv run scripts\u002Fchembl_api.py target --search\n\"EGFR\" --limit 5 --output \u002Ftmp\u002Ftargets.json`\n\n**Fetch by ID:** `bash uv run scripts\u002Fchembl_api.py target --id CHEMBL203\n--output \u002Ftmp\u002Fegfr.json`\n\n--------------------------------------------------------------------------------\n\n### 4. Bioactivity Data\n\n**Fetch activity by ID:** `bash uv run scripts\u002Fchembl_api.py activity --id 31863\n--output \u002Ftmp\u002Fact.json`\n\n**Search activities:** `bash uv run scripts\u002Fchembl_api.py activity --search\n\"EGFR\" --limit 5 --output \u002Ftmp\u002Fact_search.json`\n\n**Filter activities for a target:** `bash uv run scripts\u002Fchembl_api.py activity\n--filter target_chembl_id=CHEMBL203 standard_type=IC50 --limit 10 --output\n\u002Ftmp\u002Fegfr_ic50.json`\n\n**Normalize bioactivity units to nM:** `bash uv run scripts\u002Fchembl_api.py\nactivity --filter target_chembl_id=CHEMBL203 standard_type=IC50 --limit 5\n--normalize --output \u002Ftmp\u002Fegfr_normalized.json`\n\n> **Important**: Bioactivity values come in various units (nM, µM, pM). Use\n> `--normalize` to convert all values to nM for consistent comparison. Each\n> record will include `normalized_value_nM` and `normalization_note`.\n\n--------------------------------------------------------------------------------\n\n### 5. Drug Information\n\n**Fetch drug details:** `bash uv run scripts\u002Fchembl_api.py drug --id CHEMBL25\n--output \u002Ftmp\u002Fdrug.json`\n\n**Drug indications:** `bash uv run scripts\u002Fchembl_api.py drug_indication\n--filter molecule_chembl_id=CHEMBL25 --limit 10 --output \u002Ftmp\u002Findications.json`\n\n**Filter indications by phase:** `bash uv run scripts\u002Fchembl_api.py\ndrug_indication --filter molecule_chembl_id=CHEMBL25 max_phase_for_ind=4.0\n--limit 10 --output \u002Ftmp\u002Fapproved_indications.json`\n\n**Drug warnings:** `bash uv run scripts\u002Fchembl_api.py drug_warning --limit 5\n--output \u002Ftmp\u002Fwarnings.json`\n\n**Mechanisms of action:** `bash uv run scripts\u002Fchembl_api.py mechanism --filter\nmolecule_chembl_id=CHEMBL25 --limit 5 --output \u002Ftmp\u002Fmech.json`\n\n--------------------------------------------------------------------------------\n\n### 6. Structure-Based Searches\n\n> **Note**: Both similarity and substructure searches are performed\n> **server-side** on ChEMBL's pre-indexed database. They do not require a local\n> RDKit installation.\n\n**Similarity search (SMILES + threshold):** `bash uv run scripts\u002Fchembl_api.py\nsimilarity --smiles \"CC(=O)Oc1ccccc1C(=O)O\" --similarity 85 --limit 5 --output\n\u002Ftmp\u002Fsimilar.json`\n\n**Substructure search (SMILES):** `bash uv run scripts\u002Fchembl_api.py\nsubstructure --smiles \"c1ccccc1\" --limit 5 --output \u002Ftmp\u002Fsubstruct.json`\n\n--------------------------------------------------------------------------------\n\n### 7. Compound Image\n\nDownload a 2D structure image (SVG by default, scalable for publication):\n\n```bash\nuv run scripts\u002Fchembl_api.py image --id CHEMBL25 --output \u002Ftmp\u002Fchembl25.svg\n```\n\n*Options:*\n\n-   `--dimensions`: Image size in pixels (max 500, default 500).\n-   `--engine`: Rendering engine (default: rdkit).\n-   `--img_format`: Output format — `svg` (default, vector) or `png` (raster).\n\n--------------------------------------------------------------------------------\n\n### 8. Cross-Referencing with Other Databases\n\nChEMBL integrates with UniProt, Ensembl, PubChem, and other databases. Common\ncross-referencing patterns:\n\n**Find a ChEMBL target from a UniProt accession:** `bash uv run\nscripts\u002Fchembl_api.py target --filter target_components__accession=P00533\n--limit 5 --output \u002Ftmp\u002Funiprot_target.json`\n\n**Resolve any ChEMBL ID to its entity type:** `bash uv run scripts\u002Fchembl_api.py\nchembl_id_lookup --id CHEMBL203 --output \u002Ftmp\u002Flookup.json`\n\n**Look up cross-reference sources:** `bash uv run scripts\u002Fchembl_api.py\nxref_source --limit 10 --output \u002Ftmp\u002Fxrefs.json`\n\n> **Tip**: Use the `target_component` endpoint to find UniProt accessions, gene\n> names, and protein sequences for any ChEMBL target.\n\n--------------------------------------------------------------------------------\n\n### 9. Pagination\n\nAll list endpoints support `--limit` and `--offset` for pagination:\n\n```bash\n# First page: 2 results starting at offset 0\nuv run scripts\u002Fchembl_api.py molecule --limit 2 --offset 0 --output \u002Ftmp\u002Fpage1.json\n\n# Second page: next 2 results starting at offset 2\nuv run scripts\u002Fchembl_api.py molecule --limit 2 --offset 2 --output \u002Ftmp\u002Fpage2.json\n```\n\nThe response includes `page_meta` with `total_count`, `limit`, `offset`, `next`,\nand `previous` links. Use successive `--offset` values to page through large\nresult sets.\n\n--------------------------------------------------------------------------------\n\n### 10. Other Endpoints\n\nAll remaining endpoints follow the same pattern:\n\n```bash\nuv run scripts\u002Fchembl_api.py \u003Csubcommand> --output \u003Cfile> [--id ID | --ids ID1;ID2 | --search QUERY] [--limit N] [--offset N] [--filter KEY=VAL ...]\n```\n\n**Key subcommands at a glance:**\n\n-   `molecule` (searchable: true): Molecules\u002Fcompounds — the primary entry point\n-   `target` (searchable: true): Drug targets (proteins, organisms, etc.)\n-   `activity` (searchable: true): Bioactivity data (IC50, Ki, EC50, etc.)\n-   `drug` (searchable: false): Approved drugs\n-   `mechanism` (searchable: false): Mechanisms of action\n-   `assay` (searchable: true): Assay descriptions\n-   `similarity` (searchable: false): Similarity search (special)\n-   `substructure` (searchable: false): Substructure search (special)\n-   `image` (searchable: false): Compound image download (special)\n\n**Full subcommand list:**\n\n-   `activity_supp` (searchable: false): Supplementary activity data\n-   `assay_class` (searchable: false): Assay classifications\n-   `atc_class` (searchable: false): ATC drug classifications\n-   `binding_site` (searchable: false): Binding site information\n-   `biotherapeutic` (searchable: false): Biotherapeutic molecules\n-   `cell_line` (searchable: false): Cell line details\n-   `chembl_id_lookup` (searchable: true): ChEMBL ID resolution\n-   `chembl_release` (searchable: false): Database release info\n-   `compound_record` (searchable: false): Compound records\n-   `compound_structural_alert` (searchable: false): Structural alerts\n-   `document` (searchable: true): Literature documents\n-   `document_similarity` (searchable: false): Document similarity\n-   `drug_indication` (searchable: false): Drug indications\n-   `drug_warning` (searchable: false): Drug safety warnings\n-   `go_slim` (searchable: false): GO slim terms\n-   `metabolism` (searchable: false): Metabolism data\n-   `molecule_form` (searchable: false): Molecule forms (salts\u002Fparents)\n-   `organism` (searchable: false): Organisms\n-   `protein_classification` (searchable: true): Protein classifications\n-   `source` (searchable: false): Data sources\n-   `target_component` (searchable: false): Target protein components\n-   `target_relation` (searchable: false): Target relationships\n-   `tissue` (searchable: false): Tissue types\n-   `xref_source` (searchable: false): Cross-reference sources\n-   `status` (searchable: false): API status check (special)\n\n## Common Options\n\n-   `--output FILE`: **Required.** Output file path for JSON results.\n-   `--id ID`: Fetch a single record by ID.\n-   `--ids ID1;ID2;...`: Batch fetch multiple records.\n-   `--search QUERY`: Free-text search (only for searchable endpoints, marked\n    ✓).\n-   `--limit N`: Max results to return (default: 5).\n-   `--offset N`: Pagination offset.\n-   `--filter KEY=VAL`: Filter parameters (can specify multiple).\n-   `--normalize`: (activity only) Normalize values to nM.\n-   `--dl_format sdf|mol`: (molecule only) Download structure file.\n\n## Reference\n\n-   **API Endpoints Reference**: See\n    [references\u002Fapi_endpoints.md](references\u002Fapi_endpoints.md) for the full list\n    of endpoints and filter operators.\n\n## Workflow\n\n1.  Use `status --output \u002Ftmp\u002Fstatus.json` to verify the API is available.\n2.  Search for targets, molecules, or drugs using the relevant subcommand.\n3.  Read the output JSON file to extract IDs and data.\n4.  Use IDs from search results to fetch detailed records.\n5.  Query `activity` with filters to get bioactivity data for targets\u002Fmolecules.\n    Use `--normalize` when comparing values across studies.\n6.  Use `similarity` or `substructure` for server-side structure-based queries.\n7.  Download compound images with `image` or structure files with `molecule\n    --dl_format sdf`.\n8.  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See\n",{"type":45,"tag":106,"props":1853,"children":1855},{"href":1854},"references\u002Fapi_endpoints.md",[1856],{"type":51,"value":1854},{"type":51,"value":1858}," for the full list\nof endpoints and filter operators.",{"type":45,"tag":54,"props":1860,"children":1862},{"id":1861},"workflow",[1863],{"type":51,"value":1864},"Workflow",{"type":45,"tag":61,"props":1866,"children":1867},{},[1868,1881,1886,1891,1896,1915,1933,1952],{"type":45,"tag":65,"props":1869,"children":1870},{},[1871,1873,1879],{"type":51,"value":1872},"Use ",{"type":45,"tag":73,"props":1874,"children":1876},{"className":1875},[],[1877],{"type":51,"value":1878},"status --output \u002Ftmp\u002Fstatus.json",{"type":51,"value":1880}," to verify the API is available.",{"type":45,"tag":65,"props":1882,"children":1883},{},[1884],{"type":51,"value":1885},"Search for targets, molecules, or drugs using the relevant subcommand.",{"type":45,"tag":65,"props":1887,"children":1888},{},[1889],{"type":51,"value":1890},"Read the output JSON file to extract IDs and data.",{"type":45,"tag":65,"props":1892,"children":1893},{},[1894],{"type":51,"value":1895},"Use IDs from search results to fetch detailed records.",{"type":45,"tag":65,"props":1897,"children":1898},{},[1899,1901,1906,1908,1913],{"type":51,"value":1900},"Query ",{"type":45,"tag":73,"props":1902,"children":1904},{"className":1903},[],[1905],{"type":51,"value":1365},{"type":51,"value":1907}," with filters to get bioactivity data for targets\u002Fmolecules.\nUse ",{"type":45,"tag":73,"props":1909,"children":1911},{"className":1910},[],[1912],{"type":51,"value":590},{"type":51,"value":1914}," when comparing values across studies.",{"type":45,"tag":65,"props":1916,"children":1917},{},[1918,1919,1924,1926,1931],{"type":51,"value":1872},{"type":45,"tag":73,"props":1920,"children":1922},{"className":1921},[],[1923],{"type":51,"value":1409},{"type":51,"value":1925}," or 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UniProt.",{"type":45,"tag":1965,"props":1966,"children":1967},"style",{},[1968],{"type":51,"value":1969},"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":1971,"total":2127},[1972,1989,2004,2012,2024,2039,2055,2068,2080,2095,2106,2116],{"slug":1973,"name":1973,"fn":1974,"description":1975,"org":1976,"tags":1977,"stars":28,"repoUrl":29,"updatedAt":1988},"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},[1978,1981,1984,1987],{"name":1979,"slug":1980,"type":15},"Bioinformatics","bioinformatics",{"name":1982,"slug":1983,"type":15},"Genomics","genomics",{"name":1985,"slug":1986,"type":15},"Life Sciences","life-sciences",{"name":13,"slug":14,"type":15},"2026-07-12T07:51:51.827211",{"slug":1990,"name":1990,"fn":1991,"description":1992,"org":1993,"tags":1994,"stars":28,"repoUrl":29,"updatedAt":2003},"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},[1995,1996,1999,2000],{"name":1979,"slug":1980,"type":15},{"name":1997,"slug":1998,"type":15},"Genetics","genetics",{"name":13,"slug":14,"type":15},{"name":2001,"slug":2002,"type":15},"RNA-seq","rna-seq","2026-07-12T07:51:39.494803",{"slug":4,"name":4,"fn":5,"description":6,"org":2005,"tags":2006,"stars":28,"repoUrl":29,"updatedAt":30},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2007,2008,2009,2010,2011],{"name":23,"slug":24,"type":15},{"name":26,"slug":27,"type":15},{"name":20,"slug":21,"type":15},{"name":17,"slug":18,"type":15},{"name":13,"slug":14,"type":15},{"slug":2013,"name":2013,"fn":2014,"description":2015,"org":2016,"tags":2017,"stars":28,"repoUrl":29,"updatedAt":2023},"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},[2018,2021,2022],{"name":2019,"slug":2020,"type":15},"Clinical Trials","clinical-trials",{"name":1985,"slug":1986,"type":15},{"name":13,"slug":14,"type":15},"2026-07-12T07:52:06.846705",{"slug":2025,"name":2025,"fn":2026,"description":2027,"org":2028,"tags":2029,"stars":28,"repoUrl":29,"updatedAt":2038},"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},[2030,2033,2034,2037],{"name":2031,"slug":2032,"type":15},"ClinVar","clinvar",{"name":1997,"slug":1998,"type":15},{"name":2035,"slug":2036,"type":15},"Healthcare","healthcare",{"name":13,"slug":14,"type":15},"2026-07-12T07:51:36.86094",{"slug":2040,"name":2040,"fn":2041,"description":2042,"org":2043,"tags":2044,"stars":28,"repoUrl":29,"updatedAt":2054},"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},[2045,2048,2051],{"name":2046,"slug":2047,"type":15},"Compliance","compliance",{"name":2049,"slug":2050,"type":15},"Operations","operations",{"name":2052,"slug":2053,"type":15},"Security","security","2026-07-12T07:52:17.355491",{"slug":2056,"name":2056,"fn":2057,"description":2058,"org":2059,"tags":2060,"stars":28,"repoUrl":29,"updatedAt":2067},"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},[2061,2062,2063,2066],{"name":1979,"slug":1980,"type":15},{"name":1997,"slug":1998,"type":15},{"name":2064,"slug":2065,"type":15},"NCBI","ncbi",{"name":13,"slug":14,"type":15},"2026-07-12T07:51:33.054229",{"slug":2069,"name":2069,"fn":2070,"description":2071,"org":2072,"tags":2073,"stars":28,"repoUrl":29,"updatedAt":2079},"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},[2074,2075,2078],{"name":1979,"slug":1980,"type":15},{"name":2076,"slug":2077,"type":15},"Ontology","ontology",{"name":13,"slug":14,"type":15},"2026-07-12T07:51:59.368324",{"slug":2081,"name":2081,"fn":2082,"description":2083,"org":2084,"tags":2085,"stars":28,"repoUrl":29,"updatedAt":2094},"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},[2086,2087,2090,2091],{"name":1979,"slug":1980,"type":15},{"name":2088,"slug":2089,"type":15},"GraphQL","graphql",{"name":13,"slug":14,"type":15},{"name":2092,"slug":2093,"type":15},"REST API","rest-api","2026-07-12T07:52:10.597139",{"slug":2096,"name":2096,"fn":2097,"description":2098,"org":2099,"tags":2100,"stars":28,"repoUrl":29,"updatedAt":2105},"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},[2101,2102,2103,2104],{"name":1979,"slug":1980,"type":15},{"name":1997,"slug":1998,"type":15},{"name":1985,"slug":1986,"type":15},{"name":13,"slug":14,"type":15},"2026-07-12T07:51:41.645835",{"slug":2107,"name":2107,"fn":2108,"description":2109,"org":2110,"tags":2111,"stars":28,"repoUrl":29,"updatedAt":2115},"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},[2112,2113,2114],{"name":1979,"slug":1980,"type":15},{"name":1985,"slug":1986,"type":15},{"name":13,"slug":14,"type":15},"2026-07-12T07:52:09.354992",{"slug":2117,"name":2117,"fn":2118,"description":2119,"org":2120,"tags":2121,"stars":28,"repoUrl":29,"updatedAt":2126},"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},[2122,2123,2124,2125],{"name":1979,"slug":1980,"type":15},{"name":1997,"slug":1998,"type":15},{"name":1985,"slug":1986,"type":15},{"name":13,"slug":14,"type":15},"2026-07-12T07:51:38.213009",38,{"items":2129,"total":2127},[2130,2137,2144,2152,2158,2165,2171],{"slug":1973,"name":1973,"fn":1974,"description":1975,"org":2131,"tags":2132,"stars":28,"repoUrl":29,"updatedAt":1988},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2133,2134,2135,2136],{"name":1979,"slug":1980,"type":15},{"name":1982,"slug":1983,"type":15},{"name":1985,"slug":1986,"type":15},{"name":13,"slug":14,"type":15},{"slug":1990,"name":1990,"fn":1991,"description":1992,"org":2138,"tags":2139,"stars":28,"repoUrl":29,"updatedAt":2003},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2140,2141,2142,2143],{"name":1979,"slug":1980,"type":15},{"name":1997,"slug":1998,"type":15},{"name":13,"slug":14,"type":15},{"name":2001,"slug":2002,"type":15},{"slug":4,"name":4,"fn":5,"description":6,"org":2145,"tags":2146,"stars":28,"repoUrl":29,"updatedAt":30},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2147,2148,2149,2150,2151],{"name":23,"slug":24,"type":15},{"name":26,"slug":27,"type":15},{"name":20,"slug":21,"type":15},{"name":17,"slug":18,"type":15},{"name":13,"slug":14,"type":15},{"slug":2013,"name":2013,"fn":2014,"description":2015,"org":2153,"tags":2154,"stars":28,"repoUrl":29,"updatedAt":2023},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2155,2156,2157],{"name":2019,"slug":2020,"type":15},{"name":1985,"slug":1986,"type":15},{"name":13,"slug":14,"type":15},{"slug":2025,"name":2025,"fn":2026,"description":2027,"org":2159,"tags":2160,"stars":28,"repoUrl":29,"updatedAt":2038},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2161,2162,2163,2164],{"name":2031,"slug":2032,"type":15},{"name":1997,"slug":1998,"type":15},{"name":2035,"slug":2036,"type":15},{"name":13,"slug":14,"type":15},{"slug":2040,"name":2040,"fn":2041,"description":2042,"org":2166,"tags":2167,"stars":28,"repoUrl":29,"updatedAt":2054},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2168,2169,2170],{"name":2046,"slug":2047,"type":15},{"name":2049,"slug":2050,"type":15},{"name":2052,"slug":2053,"type":15},{"slug":2056,"name":2056,"fn":2057,"description":2058,"org":2172,"tags":2173,"stars":28,"repoUrl":29,"updatedAt":2067},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2174,2175,2176,2177],{"name":1979,"slug":1980,"type":15},{"name":1997,"slug":1998,"type":15},{"name":2064,"slug":2065,"type":15},{"name":13,"slug":14,"type":15}]