[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-google-deepmind-pubmed-database":3,"mdc--5aaa1y-key":33,"related-org-google-deepmind-pubmed-database":1333,"related-repo-google-deepmind-pubmed-database":1500},{"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},"pubmed-database","search PubMed for scientific literature","Search PubMed for scientific literature, including published clinical trials. Fetch abstracts and full text. Link published research to biological databases (gene, protein, nucleotide, PubChem) to discover associations between papers and specific compounds or genes. Verify medical spelling, match raw citations, and cache result sets for bulk processing. Interfaces NCBI E-utilities and PMC BioC APIs.",{"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},"PubMed","pubmed",{"name":20,"slug":21,"type":15},"Life Sciences","life-sciences",2333,"https:\u002F\u002Fgithub.com\u002Fgoogle-deepmind\u002Fscience-skills","2026-07-12T07:51:56.899679",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\u002Fpubmed_database","---\nname: pubmed-database\ndescription: >-\n  Search PubMed for scientific literature, including published clinical trials.\n  Fetch abstracts and full text. Link published research to biological databases\n  (gene, protein, nucleotide, PubChem) to discover associations between papers\n  and specific compounds or genes. Verify medical spelling, match raw citations,\n  and cache result sets for bulk processing. Interfaces NCBI E-utilities and PMC\n  BioC APIs.\n---\n\n# PubMed API\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\u002Fpubmed_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\u002Fpubmed.ncbi.nlm.nih.gov\u002Fdisclaimer\u002F\n    and https:\u002F\u002Fwww.ncbi.nlm.nih.gov\u002Fhome\u002Fabout\u002Fpolicies\u002F and to always check\n    the license of the papers retrieved by the skill for any restrictions, then\n    (2) create the file recording the notification text and timestamp.\n3.  **`.env` file**: Make sure the `.env` file exists in your home directory.\n    Create one if it does not exist.\n4.  **`NCBI_API_KEY`** (optional): Raises the NCBI E-utilities rate limit from 3\n    to 10 requests\u002Fsecond. The skill works without it, but a key is recommended\n    if the user plans many queries or encounters a 429 error. You can register\n    for a key for free at https:\u002F\u002Fwww.ncbi.nlm.nih.gov\u002Faccount\u002Fsettings\u002F. You\n    **MUST** use the safe credentials protocol in the `credentials` skill to\n    check for and request this key if this skill looks relevant to the user's\n    request.\n5.  **`USER_EMAIL`** (optional): Identifies the caller to NCBI (recommended by\n    their Terms of Use). You **MUST** use the safe credentials protocol in the\n    `credentials` skill to check for and request this credential if this skill\n    looks relevant to the user's request.\n\nThis skill provides CLI access to the NCBI PubMed and PubMed Central APIs via\n`scripts\u002Fpubmed_api.py` — a single CLI with 10 functions covering search, fetch,\nlinking, full text, spelling, discovery, citation matching, and caching.\n\n## Core Rules\n\n-   **API Use**: Always use the provided wrapper `scripts\u002Fpubmed_api.py` which\n    manages rate limits automatically and prevents API abuse. Setting the\n    `NCBI_API_KEY` environment variable raises the rate limit from 3 to 10\n    requests\u002Fsecond. Querying the API any other way (e.g. via curl, wget, or\n    hand-written code) is strictly forbidden.\n-   **JSON Processing**: Use `jq` to filter and transform JSON output (or python\n    equivalents if `jq` is not available) to prevent hallucinations and context\n    overflow.\n-   **Temporary Files**: To avoid polluting the working directory with JSON\n    files, use a temporary directory inside the current directory. When running\n    multiple agents or tasks in parallel, ensure each uses a unique subdirectory\n    name (e.g., `tmp_$TASK_ID\u002F`) to avoid file collisions.\n-   **Notification**: If this skill is used, ensure this is mentioned in the\n    output AND list the URLs of all papers that were used in producing the\n    output.\n\n## Structure of the skill folder\n\n-   `SKILL.md` - This file\n-   `scripts\u002Fpubmed_api.py` - The skill CLI\n-   `references\u002F` - Directory with detailed function specifications\n    -   `advanced-linking.md`\n    -   `advanced-search.md`\n    -   `bulk-workflows.md`\n    -   `citation-matching.md`\n    -   `cross-database-linking.md`\n    -   `fetch-and-resolve.md`\n    -   `search-and-discovery.md`\n    -   `utilities.md`\n\n## CLI Usage\n\n```bash\nuv run scripts\u002Fpubmed_api.py \u003Coutput_file> \u003Cfunction_name> \u003Crequired_args> [--flag value ...]\n```\n\n-   **Positional Arguments**: Arguments are positional; list arguments are\n    passed as comma-separated strings without spaces (e.g.\n    `\"35113657,31234568\"`).\n-   **Flag Options**: Optional arguments can be passed as `--flag value` instead\n    of positional args.\n-   **Output Handling**: On success, JSON is written to `output_file`. On error,\n    the process exits with a non-zero code and no output file is written.\n\n### Example Usage\n\n```bash\nuv run scripts\u002Fpubmed_api.py .\u002Fsearch_results.json search_pubmed \"BRCA1\" --max_results 5\ncat .\u002Fsearch_results.json | jq '.[]' -r\nuv run scripts\u002Fpubmed_api.py .\u002Fabstracts.json fetch_article_abstracts \"35113657\"\ncat .\u002Fabstracts.json | jq '.[0].title' -r\n```\n\n## Essential Recipes\n\n**Join PMIDs for the next call (most common chaining pattern):**\n\n```bash\ncat .\u002Fsearch_results.json | jq -r 'join(\",\")'\n```\n\n**Slim abstracts to essential fields and truncate long abstracts:**\n\n```bash\ncat .\u002Fabstracts.json | jq '[.[] | {pmid, title, snippet: (.abstract \u002F\u002F \"\")[:500]}]'\n```\n\n**Filter by keyword (null-safe):**\n\n```bash\ncat .\u002Fabstracts.json | jq '[.[] | select((.title \u002F\u002F \"\") | contains(\"Review\"))]'\n```\n\n### Context Management & Accuracy\n\nWhen processing larger result sets (>10 abstracts):\n\n1.  **Filter Early**: Use `jq` to verify keywords in abstracts *before* reading\n    the full JSON into context.\n2.  **Slimming**: Extract only `title` and `abstract` fields unless explicitly\n    instructed otherwise. Author lists and metadata contribute to noise.\n3.  **Bulk Operations (N > 10)**: Avoid fetching or processing IDs one-by-one.\n    The API and History Server are designed for bulk retrieval. Fetch all data\n    in a **single turn** and use shell pipelines to slim the results before\n    reading into context. This prevents turn exhaustion and context overflow.\n4.  **Grounding**: Never use internal knowledge to provide specific identifiers\n    (PMIDs, CIDs, Gene IDs) if no results are found. Report the tool's output\n    accurately to ensure results are grounded in the current database state.\n5.  **Search Termination**: When asked to find papers that may not exist, limit\n    exploration to 3–5 high-quality, varied search queries. If no results match\n    after these attempts, conclude that no papers meet the criteria rather than\n    continuing to iterate — unless explicitly instructed to be thorough.\n\n## Functions\n\n> **⚠️ MANDATORY**: You **MUST** read the linked reference file for a function\n> group **before calling any function** in that group. The tables below only\n> describe *what* each function does — not *how* to call it. Argument names,\n> argument order, flags, and output schemas are **only** documented in the\n> reference files. **Do NOT guess or infer arguments from function names.** If\n> you call a function without first reading its reference, you **will** produce\n> incorrect invocations.\n\n### [Search](references\u002Fsearch-and-discovery.md)\n\n-   `search_pubmed`: Find PMIDs matching a free-text or structured NCBI query.\n-   `global_database_discovery`: Count how many records match a query across\n    every NCBI database.\n\n### [Fetch & Resolve](references\u002Ffetch-and-resolve.md)\n\n-   `fetch_article_abstracts`: Retrieve metadata and abstracts for a batch of\n    PMIDs.\n-   `get_full_text_pmc`: Retrieve open-access full text from PMC.\n-   `fetch_database_summary`: Resolve opaque UIDs from any NCBI database into\n    human-readable metadata.\n\n### [Cross-Database Linking](references\u002Fcross-database-linking.md)\n\n-   `find_linked_biological_data`: Find records in other NCBI databases linked\n    to a source record.\n-   `discover_available_links`: List all available ELink linknames for a given\n    record.\n\n### [Bulk Workflows](references\u002Fbulk-workflows.md)\n\nWhen working with **more than ~10 PMIDs**, avoid processing IDs one-by-one.\nUpload them to the NCBI History Server via `cache_results_history` to get a\nsession handle (`webenv` + `query_key`), then pass that handle to\n`fetch_article_abstracts` or `find_linked_biological_data` for a single bulk\ncall. 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See the reference\nfor complete workflow recipes (search→fetch, cross-db exploration, citation\nresolution, and bulk retrieval with data slimming).",{"type":39,"tag":225,"props":1280,"children":1281},{},[1282],{"type":39,"tag":59,"props":1283,"children":1284},{},[1285,1290],{"type":39,"tag":67,"props":1286,"children":1288},{"className":1287},[],[1289],{"type":45,"value":1239},{"type":45,"value":1291},": Upload PMIDs to the NCBI History Server for bulk\nretrieval.",{"type":39,"tag":590,"props":1293,"children":1295},{"id":1294},"utilities",[1296],{"type":39,"tag":100,"props":1297,"children":1299},{"href":1298},"references\u002Futilities.md",[1300],{"type":45,"value":1301},"Utilities",{"type":39,"tag":225,"props":1303,"children":1304},{},[1305,1316],{"type":39,"tag":59,"props":1306,"children":1307},{},[1308,1314],{"type":39,"tag":67,"props":1309,"children":1311},{"className":1310},[],[1312],{"type":45,"value":1313},"verify_medical_spelling",{"type":45,"value":1315},": Spell-check biomedical terms before searching.",{"type":39,"tag":59,"props":1317,"children":1318},{},[1319,1325],{"type":39,"tag":67,"props":1320,"children":1322},{"className":1321},[],[1323],{"type":45,"value":1324},"match_raw_citations",{"type":45,"value":1326},": Resolve incomplete bibliographic citations to PMIDs.",{"type":39,"tag":1328,"props":1329,"children":1330},"style",{},[1331],{"type":45,"value":1332},"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":1334,"total":1499},[1335,1350,1365,1385,1397,1412,1427,1440,1452,1467,1478,1488],{"slug":1336,"name":1336,"fn":1337,"description":1338,"org":1339,"tags":1340,"stars":22,"repoUrl":23,"updatedAt":1349},"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},[1341,1344,1347,1348],{"name":1342,"slug":1343,"type":15},"Bioinformatics","bioinformatics",{"name":1345,"slug":1346,"type":15},"Genomics","genomics",{"name":20,"slug":21,"type":15},{"name":13,"slug":14,"type":15},"2026-07-12T07:51:51.827211",{"slug":1351,"name":1351,"fn":1352,"description":1353,"org":1354,"tags":1355,"stars":22,"repoUrl":23,"updatedAt":1364},"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},[1356,1357,1360,1361],{"name":1342,"slug":1343,"type":15},{"name":1358,"slug":1359,"type":15},"Genetics","genetics",{"name":13,"slug":14,"type":15},{"name":1362,"slug":1363,"type":15},"RNA-seq","rna-seq","2026-07-12T07:51:39.494803",{"slug":1366,"name":1366,"fn":1367,"description":1368,"org":1369,"tags":1370,"stars":22,"repoUrl":23,"updatedAt":1384},"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},[1371,1374,1377,1380,1383],{"name":1372,"slug":1373,"type":15},"ChEMBL","chembl",{"name":1375,"slug":1376,"type":15},"Chemistry","chemistry",{"name":1378,"slug":1379,"type":15},"Database","database",{"name":1381,"slug":1382,"type":15},"Pharmacology","pharmacology",{"name":13,"slug":14,"type":15},"2026-07-12T07:51:35.544306",{"slug":1386,"name":1386,"fn":1387,"description":1388,"org":1389,"tags":1390,"stars":22,"repoUrl":23,"updatedAt":1396},"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},[1391,1394,1395],{"name":1392,"slug":1393,"type":15},"Clinical Trials","clinical-trials",{"name":20,"slug":21,"type":15},{"name":13,"slug":14,"type":15},"2026-07-12T07:52:06.846705",{"slug":1398,"name":1398,"fn":1399,"description":1400,"org":1401,"tags":1402,"stars":22,"repoUrl":23,"updatedAt":1411},"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},[1403,1406,1407,1410],{"name":1404,"slug":1405,"type":15},"ClinVar","clinvar",{"name":1358,"slug":1359,"type":15},{"name":1408,"slug":1409,"type":15},"Healthcare","healthcare",{"name":13,"slug":14,"type":15},"2026-07-12T07:51:36.86094",{"slug":174,"name":174,"fn":1413,"description":1414,"org":1415,"tags":1416,"stars":22,"repoUrl":23,"updatedAt":1426},"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},[1417,1420,1423],{"name":1418,"slug":1419,"type":15},"Compliance","compliance",{"name":1421,"slug":1422,"type":15},"Operations","operations",{"name":1424,"slug":1425,"type":15},"Security","security","2026-07-12T07:52:17.355491",{"slug":1428,"name":1428,"fn":1429,"description":1430,"org":1431,"tags":1432,"stars":22,"repoUrl":23,"updatedAt":1439},"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},[1433,1434,1435,1438],{"name":1342,"slug":1343,"type":15},{"name":1358,"slug":1359,"type":15},{"name":1436,"slug":1437,"type":15},"NCBI","ncbi",{"name":13,"slug":14,"type":15},"2026-07-12T07:51:33.054229",{"slug":1441,"name":1441,"fn":1442,"description":1443,"org":1444,"tags":1445,"stars":22,"repoUrl":23,"updatedAt":1451},"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},[1446,1447,1450],{"name":1342,"slug":1343,"type":15},{"name":1448,"slug":1449,"type":15},"Ontology","ontology",{"name":13,"slug":14,"type":15},"2026-07-12T07:51:59.368324",{"slug":1453,"name":1453,"fn":1454,"description":1455,"org":1456,"tags":1457,"stars":22,"repoUrl":23,"updatedAt":1466},"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},[1458,1459,1462,1463],{"name":1342,"slug":1343,"type":15},{"name":1460,"slug":1461,"type":15},"GraphQL","graphql",{"name":13,"slug":14,"type":15},{"name":1464,"slug":1465,"type":15},"REST API","rest-api","2026-07-12T07:52:10.597139",{"slug":1468,"name":1468,"fn":1469,"description":1470,"org":1471,"tags":1472,"stars":22,"repoUrl":23,"updatedAt":1477},"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},[1473,1474,1475,1476],{"name":1342,"slug":1343,"type":15},{"name":1358,"slug":1359,"type":15},{"name":20,"slug":21,"type":15},{"name":13,"slug":14,"type":15},"2026-07-12T07:51:41.645835",{"slug":1479,"name":1479,"fn":1480,"description":1481,"org":1482,"tags":1483,"stars":22,"repoUrl":23,"updatedAt":1487},"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},[1484,1485,1486],{"name":1342,"slug":1343,"type":15},{"name":20,"slug":21,"type":15},{"name":13,"slug":14,"type":15},"2026-07-12T07:52:09.354992",{"slug":1489,"name":1489,"fn":1490,"description":1491,"org":1492,"tags":1493,"stars":22,"repoUrl":23,"updatedAt":1498},"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},[1494,1495,1496,1497],{"name":1342,"slug":1343,"type":15},{"name":1358,"slug":1359,"type":15},{"name":20,"slug":21,"type":15},{"name":13,"slug":14,"type":15},"2026-07-12T07:51:38.213009",38,{"items":1501,"total":1499},[1502,1509,1516,1524,1530,1537,1543],{"slug":1336,"name":1336,"fn":1337,"description":1338,"org":1503,"tags":1504,"stars":22,"repoUrl":23,"updatedAt":1349},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1505,1506,1507,1508],{"name":1342,"slug":1343,"type":15},{"name":1345,"slug":1346,"type":15},{"name":20,"slug":21,"type":15},{"name":13,"slug":14,"type":15},{"slug":1351,"name":1351,"fn":1352,"description":1353,"org":1510,"tags":1511,"stars":22,"repoUrl":23,"updatedAt":1364},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1512,1513,1514,1515],{"name":1342,"slug":1343,"type":15},{"name":1358,"slug":1359,"type":15},{"name":13,"slug":14,"type":15},{"name":1362,"slug":1363,"type":15},{"slug":1366,"name":1366,"fn":1367,"description":1368,"org":1517,"tags":1518,"stars":22,"repoUrl":23,"updatedAt":1384},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1519,1520,1521,1522,1523],{"name":1372,"slug":1373,"type":15},{"name":1375,"slug":1376,"type":15},{"name":1378,"slug":1379,"type":15},{"name":1381,"slug":1382,"type":15},{"name":13,"slug":14,"type":15},{"slug":1386,"name":1386,"fn":1387,"description":1388,"org":1525,"tags":1526,"stars":22,"repoUrl":23,"updatedAt":1396},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1527,1528,1529],{"name":1392,"slug":1393,"type":15},{"name":20,"slug":21,"type":15},{"name":13,"slug":14,"type":15},{"slug":1398,"name":1398,"fn":1399,"description":1400,"org":1531,"tags":1532,"stars":22,"repoUrl":23,"updatedAt":1411},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1533,1534,1535,1536],{"name":1404,"slug":1405,"type":15},{"name":1358,"slug":1359,"type":15},{"name":1408,"slug":1409,"type":15},{"name":13,"slug":14,"type":15},{"slug":174,"name":174,"fn":1413,"description":1414,"org":1538,"tags":1539,"stars":22,"repoUrl":23,"updatedAt":1426},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1540,1541,1542],{"name":1418,"slug":1419,"type":15},{"name":1421,"slug":1422,"type":15},{"name":1424,"slug":1425,"type":15},{"slug":1428,"name":1428,"fn":1429,"description":1430,"org":1544,"tags":1545,"stars":22,"repoUrl":23,"updatedAt":1439},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1546,1547,1548,1549],{"name":1342,"slug":1343,"type":15},{"name":1358,"slug":1359,"type":15},{"name":1436,"slug":1437,"type":15},{"name":13,"slug":14,"type":15}]