[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-google-deepmind-dbsnp-database":3,"mdc--xe8ryx-key":36,"related-org-google-deepmind-dbsnp-database":2930,"related-repo-google-deepmind-dbsnp-database":3086},{"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},"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},"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},"Bioinformatics","bioinformatics",{"name":20,"slug":21,"type":15},"Genetics","genetics",{"name":23,"slug":24,"type":15},"NCBI","ncbi",2333,"https:\u002F\u002Fgithub.com\u002Fgoogle-deepmind\u002Fscience-skills","2026-07-12T07:51:33.054229",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\u002Fdbsnp_database","---\nname: dbsnp-database\ndescription: >\n  Use when you want to look up, map, and search for short genetic variants\n  (SNPs, indels) in NCBI's dbSNP database. Resolves between rsIDs, genomic\n  coordinates in VCF format, and HGVS strings. For an rsID, returns variant\n  type, gene associations, clinical significance, allele frequencies, and\n  genomic coordinates (GRCh38).\n---\n\n# dbSNP Database Integration\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\u002Fdbsnp_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\u002Fwww.ncbi.nlm.nih.gov\u002Fsnp\u002F, then (2)\n    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 rate limit from 3 to 10\n    requests\u002Fsecond. The skill works without it, but a key is recommended if the\n    user plans many queries or encounters a 429 error. You can register for a\n    key for free at https:\u002F\u002Fwww.ncbi.nlm.nih.gov\u002Faccount\u002Fsettings\u002F. You **MUST**\n    use the safe credentials protocol in the `credentials` skill to check for\n    and request this key if this skill looks relevant to the user's request.\n\n## Core Rules\n\n-   **Use the Wrapper**: ALWAYS execute the provided wrapper script\n    `scripts\u002Fdbsnp_cli.py` to query the database rather than constructing custom\n    HTTP or curl requests. The script automatically handles rate limiting,\n    retries, and JSON parsing.\n-   **Command Choice**: Do NOT use `search-region` to find the rsID of a\n    specific variant; use `resolve-variant` instead.\n-   **Output Size**: Avoid using `--full` on `get-variant` unless specifically\n    needed, as raw payloads can exceed 1 MB.\n-   **Shell Safety**: Always wrap HGVS strings in single quotes to prevent shell\n    expansion errors.\n-   **Notification**: If this skill is used, ensure this is mentioned in the\n    output.\n\n## When to Use\n\n**Use this skill when you need to:**\n\n-   Map a genomic variant to its canonical rsID (from VCF coordinates or HGVS\n    notation).\n-   Retrieve summary data for an rsID: variant type, gene associations, clinical\n    significance, and population allele frequencies.\n-   Convert an rsID back to genomic coordinates on a specific assembly.\n-   Find all known variants within a chromosomal region.\n\n**Do NOT use when you need to:**\n\n-   Obtain clinical pathogenicity classifications with submitter rationales (use\n    **clinvar-database**).\n-   Get precise population-level allele frequencies stratified by ancestry (use\n    **gnomad-database**).\n-   Predict the functional effect of a novel mutation (use\n    **alphagenome-single-variant-analysis**).\n-   View 3D protein structures affected by a variant (use\n    **alphafold-database-fetch-and-analyze \u002F pdb-database**).\n\n## Command Selection Guide\n\n**Pick the right command on the first try.** Match the user's input to the\ncorrect subcommand below — one command call is almost always sufficient.\n\n-   User gives you…: Run this command\n-   An rsID (e.g. `rs7412`, `rs268`): `get-variant`\n-   Genomic coordinates: chrom pos ref alt (e.g. `8 19962213 C T`):\n    `resolve-variant`\n-   An HGVS string (e.g. `NC_000008.11:g.19962213del`): `resolve-hgvs`\n-   An rsID and they want coordinates back: `resolve-rsid`\n-   A chromosomal region (chrom start end): `search-region`\n\n> [!CAUTION] **Do NOT use `search-region` to find the rsID of a specific\n> variant.** If the user provides a chromosome, position, reference allele, and\n> alternate allele (four values), use `resolve-variant` — it is a direct,\n> single-API-call lookup. `search-region` is only for surveying all variants\n> within a positional range and returns hundreds\u002Fthousands of results.\n\n## Quick Start\n\n```bash\n# Look up variant rs7412: type, gene, clinical significance, MAF\nuv run scripts\u002Fdbsnp_cli.py get-variant rs7412 --output \u002Ftmp\u002Frs7412.json\n\n# Find the rsID for a variant at chr8:19962213 C>T\nuv run scripts\u002Fdbsnp_cli.py resolve-variant 8 19962213 C T \\\n  --output \u002Ftmp\u002Fresolve.json\n```\n\nAll subcommands write JSON to disk. Always save output in the `\u002Ftmp\u002F` directory.\nThe `--output` flag is required.\n\n## Commands\n\n### 1. `get-variant` — Fetch Variant Record\n\nRetrieve the RefSNP record for one rsID. By default the output is abbreviated to\nthe most useful fields. Both `rs268` and `268` are accepted.\n\n```bash\nuv run scripts\u002Fdbsnp_cli.py get-variant rs268 --output \u002Ftmp\u002Frs268.json\nuv run scripts\u002Fdbsnp_cli.py get-variant 268 --assembly GCF_000001405.40 \\\n  --output \u002Ftmp\u002Frs268.json\n```\n\n*Arguments:*\n\n-   `rsid` (positional, required): The RefSNP identifier.\n-   `--assembly`: RefSeq assembly accession (default: `GCF_000001405.40` =\n    GRCh38).\n-   `--full`: Return the complete raw JSON payload — see warning below.\n-   `--output`: Output file path (default: `\u002Ftmp\u002Fdbsnp_output.json`).\n\n*Abbreviated output fields:*\n\n-   `refsnp_id`: Numeric rsID\n-   `variant_type`: e.g. `snv`, `ins`, `del`, `delins`\n-   `genes`: Sorted list of gene symbols (locus names)\n-   `clinical_significances`: List of clinical significance labels\n-   `minor_allele_frequencies`: Study name, allele count, total count\n-   `placements`: Genomic placements for the requested assembly\n\n> [!WARNING] **About `--full`:** The raw RefSNP payload is typically 50–500 KB\n> and can exceed 1 MB for clinically significant variants with many submissions.\n> Only use `--full` when you specifically need data absent from the abbreviated\n> output — for example:\n>\n> -   The complete HGVS nomenclature across every transcript and protein\n>     isoform.\n> -   Full submission history with individual submitter details and timestamps.\n> -   Population-level allele frequency breakdowns by sub-population within a\n>     study (e.g. per-population gnomAD counts).\n> -   The full set of genomic placements across multiple assemblies (GRCh37 and\n>     GRCh38 simultaneously).\n> -   Merge history showing which older rsIDs were merged into this one.\n\n### 2. `resolve-variant` — Genomic Coordinates → rsID\n\nDetermine the rsID(s) for a variant given its genomic coordinates (chromosome,\nposition, reference allele, alternate allele). **This is the command to use when\nthe user provides a variant as space-separated coordinates** like `8 19962213 C\nT`.\n\n```bash\nuv run scripts\u002Fdbsnp_cli.py resolve-variant 8 19962213 C T \\\n  --output \u002Ftmp\u002Fresolve.json\n```\n\n*Arguments:*\n\n-   `chrom` (positional): Chromosome number (e.g. `8`) or RefSeq sequence\n    accession (e.g. `NC_000008.11`). **Chromosomes X and Y must be passed as\n    their numeric equivalents: `23` for X and `24` for Y.**\n-   `pos` (positional): 1-based genomic position.\n-   `ref` (positional): Reference allele (e.g. `C`).\n-   `alts` (positional): Alternate allele(s), comma-separated (e.g. `T`).\n-   `--assembly`: RefSeq assembly accession (default: `GCF_000001405.40`).\n-   `--output`: Output file path (default: `\u002Ftmp\u002Fdbsnp_output.json`).\n\n*Output:* `{\"rsids\": [\"12345\", \"67890\"]}`\n\n### 3. `resolve-rsid` — rsID → Genomic Coordinates\n\nGet the genomic placement (sequence ID and allele details) for a known rsID on a\nspecific assembly.\n\n```bash\nuv run scripts\u002Fdbsnp_cli.py resolve-rsid rs7412 --output \u002Ftmp\u002Fcoords.json\n```\n\n*Arguments:*\n\n-   `rsid` (positional): The RefSNP identifier.\n-   `--assembly`: RefSeq assembly accession (default: `GCF_000001405.40`).\n-   `--output`: Output file path (default: `\u002Ftmp\u002Fdbsnp_output.json`).\n\n*Output:* `{\"rsid\": \"7412\", \"assembly\": \"...\", \"placements\": [...]}`\n\n### 4. `resolve-hgvs` — HGVS → rsID\n\nFind the rsID(s) corresponding to an HGVS expression.\n\n```bash\nuv run scripts\u002Fdbsnp_cli.py resolve-hgvs 'NC_000008.11:g.19962213del' \\\n  --output \u002Ftmp\u002Fhgvs.json\n```\n\n*Arguments:*\n\n-   `hgvs` (positional): The HGVS string.\n-   `--assembly`: RefSeq assembly accession (default: `GCF_000001405.40`).\n-   `--output`: Output file path (default: `\u002Ftmp\u002Fdbsnp_output.json`).\n\n*Output:* `{\"rsids\": [\"12345\"]}`\n\n> [!TIP] HGVS strings often contain characters that shells interpret (colons,\n> greater-than signs). Always wrap them in **single quotes** to prevent shell\n> expansion.\n\n### 5. `search-region` — Regional Variant Search\n\nFind all rsIDs within a bounded chromosomal region.\n\n```bash\nuv run scripts\u002Fdbsnp_cli.py search-region 7 117100000 117300000 \\\n  --output \u002Ftmp\u002Fregion.json\n```\n\n*Arguments:*\n\n-   `chrom` (positional): Chromosome (e.g. `7`). **Use `23` for chromosome X and\n    `24` for chromosome Y.**\n-   `start` (positional): Start position.\n-   `end` (positional): End position.\n-   `--retmax`: Maximum rsIDs to return (default: 500, ceiling: 5 000).\n-   `--output`: Output file path (default: `\u002Ftmp\u002Fdbsnp_output.json`).\n\n*Output:*\n\n```json\n{\n  \"rsids\": [\"12345\", \"67890\", \"...\"],\n  \"returned\": 500,\n  \"total_available\": 1423,\n  \"truncated\": true,\n  \"note\": \"Only 500 of 1423 variants returned.  Increase --retmax ...\"\n}\n```\n\nWhen `total_available` exceeds the returned count, the output includes a\n`truncated` flag and a `note`. Increase `--retmax` to retrieve more (up to 5\n000).\n\n## Typical Workflows\n\n### Identify a known variant from coordinates\n\n```bash\n# Step 1: Map VCF coordinates to rsID\nuv run scripts\u002Fdbsnp_cli.py resolve-variant 19 44908684 T C \\\n  --output \u002Ftmp\u002Fstep1.json\n\n# Step 2: Get the full details for the resolved rsID\nuv run scripts\u002Fdbsnp_cli.py get-variant \u003Crsid_from_step1> \\\n  --output \u002Ftmp\u002Fstep2.json\n```\n\n### Survey variants in a gene region\n\n```bash\n# Step 1: Find all variants in a region spanning the CFTR gene\nuv run scripts\u002Fdbsnp_cli.py search-region 7 117100000 117300000 \\\n  --retmax 1000 --output \u002Ftmp\u002Fregion.json\n\n# Step 2: Retrieve details on individual rsIDs of interest\nuv run scripts\u002Fdbsnp_cli.py get-variant \u003Crsid> --output \u002Ftmp\u002Fdetail.json\n```\n\n### Translate HGVS notation to genomic coordinates\n\n```bash\n# Step 1: Get the rsID for an HGVS expression\nuv run scripts\u002Fdbsnp_cli.py resolve-hgvs 'NC_000019.10:g.44908684T>C' \\\n  --output \u002Ftmp\u002Fhgvs.json\n\n# Step 2: Resolve that rsID to VCF-style coordinates\nuv run scripts\u002Fdbsnp_cli.py resolve-rsid \u003Crsid> --output \u002Ftmp\u002Fcoords.json\n```\n\n## Assembly Defaults and Automatic Fallback\n\nThe Variation Services endpoints (used by `get-variant`, `resolve-variant`,\n`resolve-rsid`, `resolve-hgvs`) expect a **RefSeq assembly accession**. The\nRefSeq accession for GRCh38 is `GCF_000001405.40`, and for GRCh37 it is\n`GCF_000001405.25`.\n\nThe `search-region` subcommand always searches GRCh38 positions.\n\n> [!IMPORTANT] **Automatic assembly fallback:** The `resolve-variant` and\n> `resolve-hgvs` commands automatically try GRCh38 first. If no rsIDs are found,\n> they retry with GRCh37 before reporting failure. When a fallback occurs the\n> output JSON includes a `\"note\"` field explaining which assembly succeeded.\n> **You do NOT need to manually retry with a different assembly** — the script\n> handles this transparently.\n\nYou only need to override `--assembly` when you specifically want to\n**restrict** the lookup to one assembly (e.g. because the user's coordinates are\nknown to be GRCh37).\n\n## NCBI API Key and Rate Limiting\n\nWithout an API key the script is limited to **3 requests per second**. With a\nkey this increases to **10 requests per second**.\n\nYou can register for a key for free at\nhttps:\u002F\u002Fwww.ncbi.nlm.nih.gov\u002Faccount\u002Fsettings\u002F. You **MUST** use the safe\ncredentials protocol in the `credentials` skill to check for and request this\nkey if this skill looks relevant to the user's request.\n\n## Troubleshooting HTTP 500 Errors\n\n### Reference Allele Mismatch\n\nIf you receive an HTTP 500 error with a message detailing that the asserted\nreference allele is not equal to the reference sequence:\n\n**What it means:** The coordinate position is likely valid, but the reference\nallele (`ref`) you provided does not match the base at that position in the\nrequested assembly.\n\n**Action:** 1. **DO NOT RETRY** the exact same query mechanically. 2. **Check\nthe assembly**: Coordinates are assembly-specific. 3. **Switch assembly**: If\nyou were querying GRCh37, try GRCh38 (using `--assembly GCF_000001405.40`), or\nif querying GRCh38, try GRCh37 (using `--assembly GCF_000001405.25`).\n\n## Common Mistakes\n\n-   **Mistake:** Forgetting to quote HGVS strings **Fix:** Wrap in single\n    quotes: `'NC_000008.11:g.19962213del'`\n\n-   **Mistake:** Passing a chromosome name to `resolve-variant` instead of a\n    sequence accession **Fix:** Use the numeric chromosome ID (e.g. `8`) or a\n    RefSeq accession like `NC_000008.11`\n\n-   **Mistake:** Using `--full` on `get-variant` without needing it **Fix:** The\n    abbreviated output covers most use cases; `--full` returns 50–500 KB+ of\n    JSON\n\n-   **Mistake:** Expecting `search-region` to return all results by default\n    **Fix:** The default `--retmax` is 500; check `total_available` in the\n    output to see if results were truncated\n\n-   **Mistake:** Using GRCh37 coordinates with `search-region` **Fix:**\n    `search-region` always uses GRCh38 positions; lift over coordinates first if\n    starting from GRCh37\n\n-   **Mistake:** Manually retrying `resolve-variant` or `resolve-hgvs` with a\n    different `--assembly` when the first call fails **Fix:** The script\n    automatically tries GRCh38 then GRCh37; a single call is sufficient\n\n-   **Mistake:** Passing `X` or `Y` as the chromosome value **Fix:** Use the\n    numeric equivalents: `23` for chromosome X and `24` for chromosome Y. 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When a fallback occurs the\noutput JSON includes a ",{"type":42,"tag":70,"props":2520,"children":2522},{"className":2521},[],[2523],{"type":48,"value":2524},"\"note\"",{"type":48,"value":2526}," field explaining which assembly succeeded.\n",{"type":42,"tag":66,"props":2528,"children":2529},{},[2530],{"type":48,"value":2531},"You do NOT need to manually retry with a different assembly",{"type":48,"value":2533}," — the script\nhandles this transparently.",{"type":42,"tag":279,"props":2535,"children":2536},{},[2537,2539,2544,2546,2551],{"type":48,"value":2538},"You only need to override ",{"type":42,"tag":70,"props":2540,"children":2542},{"className":2541},[],[2543],{"type":48,"value":846},{"type":48,"value":2545}," when you specifically want to\n",{"type":42,"tag":66,"props":2547,"children":2548},{},[2549],{"type":48,"value":2550},"restrict",{"type":48,"value":2552}," the lookup to one assembly (e.g. because the user's coordinates are\nknown to be GRCh37).",{"type":42,"tag":51,"props":2554,"children":2556},{"id":2555},"ncbi-api-key-and-rate-limiting",[2557],{"type":48,"value":2558},"NCBI API Key and Rate Limiting",{"type":42,"tag":279,"props":2560,"children":2561},{},[2562,2564,2569,2571,2576],{"type":48,"value":2563},"Without an API key the script is limited to ",{"type":42,"tag":66,"props":2565,"children":2566},{},[2567],{"type":48,"value":2568},"3 requests per second",{"type":48,"value":2570},". 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lift over coordinates first if\nstarting from GRCh37",{"type":42,"tag":62,"props":2845,"children":2846},{},[2847,2851,2853,2858,2860,2865,2867,2872,2874,2878],{"type":42,"tag":66,"props":2848,"children":2849},{},[2850],{"type":48,"value":2697},{"type":48,"value":2852}," Manually retrying ",{"type":42,"tag":70,"props":2854,"children":2856},{"className":2855},[],[2857],{"type":48,"value":223},{"type":48,"value":2859}," or ",{"type":42,"tag":70,"props":2861,"children":2863},{"className":2862},[],[2864],{"type":48,"value":451},{"type":48,"value":2866}," with a\ndifferent ",{"type":42,"tag":70,"props":2868,"children":2870},{"className":2869},[],[2871],{"type":48,"value":846},{"type":48,"value":2873}," when the first call fails ",{"type":42,"tag":66,"props":2875,"children":2876},{},[2877],{"type":48,"value":2704},{"type":48,"value":2879}," The script\nautomatically tries GRCh38 then GRCh37; a single call is sufficient",{"type":42,"tag":62,"props":2881,"children":2882},{},[2883,2887,2889,2895,2896,2902,2904,2908,2910,2915,2917,2922],{"type":42,"tag":66,"props":2884,"children":2885},{},[2886],{"type":48,"value":2697},{"type":48,"value":2888}," Passing ",{"type":42,"tag":70,"props":2890,"children":2892},{"className":2891},[],[2893],{"type":48,"value":2894},"X",{"type":48,"value":2859},{"type":42,"tag":70,"props":2897,"children":2899},{"className":2898},[],[2900],{"type":48,"value":2901},"Y",{"type":48,"value":2903}," as the chromosome value ",{"type":42,"tag":66,"props":2905,"children":2906},{},[2907],{"type":48,"value":2704},{"type":48,"value":2909}," Use the\nnumeric equivalents: ",{"type":42,"tag":70,"props":2911,"children":2913},{"className":2912},[],[2914],{"type":48,"value":1185},{"type":48,"value":2916}," for chromosome X and ",{"type":42,"tag":70,"props":2918,"children":2920},{"className":2919},[],[2921],{"type":48,"value":1193},{"type":48,"value":2923}," for chromosome Y. The\nCLI treats chromosomes numerically by default.",{"type":42,"tag":2925,"props":2926,"children":2927},"style",{},[2928],{"type":48,"value":2929},"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":2931,"total":3085},[2932,2947,2959,2979,2991,3005,3020,3027,3039,3054,3065,3075],{"slug":2933,"name":2933,"fn":2934,"description":2935,"org":2936,"tags":2937,"stars":25,"repoUrl":26,"updatedAt":2946},"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},[2938,2939,2942,2945],{"name":17,"slug":18,"type":15},{"name":2940,"slug":2941,"type":15},"Genomics","genomics",{"name":2943,"slug":2944,"type":15},"Life Sciences","life-sciences",{"name":13,"slug":14,"type":15},"2026-07-12T07:51:51.827211",{"slug":353,"name":353,"fn":2948,"description":2949,"org":2950,"tags":2951,"stars":25,"repoUrl":26,"updatedAt":2958},"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},[2952,2953,2954,2955],{"name":17,"slug":18,"type":15},{"name":20,"slug":21,"type":15},{"name":13,"slug":14,"type":15},{"name":2956,"slug":2957,"type":15},"RNA-seq","rna-seq","2026-07-12T07:51:39.494803",{"slug":2960,"name":2960,"fn":2961,"description":2962,"org":2963,"tags":2964,"stars":25,"repoUrl":26,"updatedAt":2978},"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},[2965,2968,2971,2974,2977],{"name":2966,"slug":2967,"type":15},"ChEMBL","chembl",{"name":2969,"slug":2970,"type":15},"Chemistry","chemistry",{"name":2972,"slug":2973,"type":15},"Database","database",{"name":2975,"slug":2976,"type":15},"Pharmacology","pharmacology",{"name":13,"slug":14,"type":15},"2026-07-12T07:51:35.544306",{"slug":2980,"name":2980,"fn":2981,"description":2982,"org":2983,"tags":2984,"stars":25,"repoUrl":26,"updatedAt":2990},"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},[2985,2988,2989],{"name":2986,"slug":2987,"type":15},"Clinical Trials","clinical-trials",{"name":2943,"slug":2944,"type":15},{"name":13,"slug":14,"type":15},"2026-07-12T07:52:06.846705",{"slug":330,"name":330,"fn":2992,"description":2993,"org":2994,"tags":2995,"stars":25,"repoUrl":26,"updatedAt":3004},"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},[2996,2999,3000,3003],{"name":2997,"slug":2998,"type":15},"ClinVar","clinvar",{"name":20,"slug":21,"type":15},{"name":3001,"slug":3002,"type":15},"Healthcare","healthcare",{"name":13,"slug":14,"type":15},"2026-07-12T07:51:36.86094",{"slug":169,"name":169,"fn":3006,"description":3007,"org":3008,"tags":3009,"stars":25,"repoUrl":26,"updatedAt":3019},"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},[3010,3013,3016],{"name":3011,"slug":3012,"type":15},"Compliance","compliance",{"name":3014,"slug":3015,"type":15},"Operations","operations",{"name":3017,"slug":3018,"type":15},"Security","security","2026-07-12T07:52:17.355491",{"slug":4,"name":4,"fn":5,"description":6,"org":3021,"tags":3022,"stars":25,"repoUrl":26,"updatedAt":27},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3023,3024,3025,3026],{"name":17,"slug":18,"type":15},{"name":20,"slug":21,"type":15},{"name":23,"slug":24,"type":15},{"name":13,"slug":14,"type":15},{"slug":3028,"name":3028,"fn":3029,"description":3030,"org":3031,"tags":3032,"stars":25,"repoUrl":26,"updatedAt":3038},"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},[3033,3034,3037],{"name":17,"slug":18,"type":15},{"name":3035,"slug":3036,"type":15},"Ontology","ontology",{"name":13,"slug":14,"type":15},"2026-07-12T07:51:59.368324",{"slug":3040,"name":3040,"fn":3041,"description":3042,"org":3043,"tags":3044,"stars":25,"repoUrl":26,"updatedAt":3053},"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},[3045,3046,3049,3050],{"name":17,"slug":18,"type":15},{"name":3047,"slug":3048,"type":15},"GraphQL","graphql",{"name":13,"slug":14,"type":15},{"name":3051,"slug":3052,"type":15},"REST API","rest-api","2026-07-12T07:52:10.597139",{"slug":3055,"name":3055,"fn":3056,"description":3057,"org":3058,"tags":3059,"stars":25,"repoUrl":26,"updatedAt":3064},"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},[3060,3061,3062,3063],{"name":17,"slug":18,"type":15},{"name":20,"slug":21,"type":15},{"name":2943,"slug":2944,"type":15},{"name":13,"slug":14,"type":15},"2026-07-12T07:51:41.645835",{"slug":3066,"name":3066,"fn":3067,"description":3068,"org":3069,"tags":3070,"stars":25,"repoUrl":26,"updatedAt":3074},"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},[3071,3072,3073],{"name":17,"slug":18,"type":15},{"name":2943,"slug":2944,"type":15},{"name":13,"slug":14,"type":15},"2026-07-12T07:52:09.354992",{"slug":342,"name":342,"fn":3076,"description":3077,"org":3078,"tags":3079,"stars":25,"repoUrl":26,"updatedAt":3084},"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},[3080,3081,3082,3083],{"name":17,"slug":18,"type":15},{"name":20,"slug":21,"type":15},{"name":2943,"slug":2944,"type":15},{"name":13,"slug":14,"type":15},"2026-07-12T07:51:38.213009",38,{"items":3087,"total":3085},[3088,3095,3102,3110,3116,3123,3129],{"slug":2933,"name":2933,"fn":2934,"description":2935,"org":3089,"tags":3090,"stars":25,"repoUrl":26,"updatedAt":2946},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3091,3092,3093,3094],{"name":17,"slug":18,"type":15},{"name":2940,"slug":2941,"type":15},{"name":2943,"slug":2944,"type":15},{"name":13,"slug":14,"type":15},{"slug":353,"name":353,"fn":2948,"description":2949,"org":3096,"tags":3097,"stars":25,"repoUrl":26,"updatedAt":2958},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3098,3099,3100,3101],{"name":17,"slug":18,"type":15},{"name":20,"slug":21,"type":15},{"name":13,"slug":14,"type":15},{"name":2956,"slug":2957,"type":15},{"slug":2960,"name":2960,"fn":2961,"description":2962,"org":3103,"tags":3104,"stars":25,"repoUrl":26,"updatedAt":2978},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3105,3106,3107,3108,3109],{"name":2966,"slug":2967,"type":15},{"name":2969,"slug":2970,"type":15},{"name":2972,"slug":2973,"type":15},{"name":2975,"slug":2976,"type":15},{"name":13,"slug":14,"type":15},{"slug":2980,"name":2980,"fn":2981,"description":2982,"org":3111,"tags":3112,"stars":25,"repoUrl":26,"updatedAt":2990},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3113,3114,3115],{"name":2986,"slug":2987,"type":15},{"name":2943,"slug":2944,"type":15},{"name":13,"slug":14,"type":15},{"slug":330,"name":330,"fn":2992,"description":2993,"org":3117,"tags":3118,"stars":25,"repoUrl":26,"updatedAt":3004},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3119,3120,3121,3122],{"name":2997,"slug":2998,"type":15},{"name":20,"slug":21,"type":15},{"name":3001,"slug":3002,"type":15},{"name":13,"slug":14,"type":15},{"slug":169,"name":169,"fn":3006,"description":3007,"org":3124,"tags":3125,"stars":25,"repoUrl":26,"updatedAt":3019},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3126,3127,3128],{"name":3011,"slug":3012,"type":15},{"name":3014,"slug":3015,"type":15},{"name":3017,"slug":3018,"type":15},{"slug":4,"name":4,"fn":5,"description":6,"org":3130,"tags":3131,"stars":25,"repoUrl":26,"updatedAt":27},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[3132,3133,3134,3135],{"name":17,"slug":18,"type":15},{"name":20,"slug":21,"type":15},{"name":23,"slug":24,"type":15},{"name":13,"slug":14,"type":15}]