[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6AFBZZMCD4Y58WW3041P5RR":3,"skill-same:01M6AFBZZMCD4Y58WW3041P5RR":79},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":23,"publishedAt":38,"linkOnly":39,"markdownContent":40,"markdownBody":41,"frontMatter":42,"refName":43,"commitSha":44,"skillDirectory":45,"forksCount":46,"repositoryHtmlUrl":47,"repositoryHomepageUrl":48,"ownerHtmlUrl":49,"ownerBlogUrl":50,"ownerDescription":51,"updatedAt":52,"install":53,"resources":66},"01M6AFBZZMCD4Y58WW3041P5RR","cosmic-database",null,"Access COSMIC cancer mutation database. Query somatic mutations, Cancer Gene Census, mutational signatures, gene fusions, for cancer research and precision oncology. Requires authentication.","davila7\u002Fclaude-code-templates","davila7","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F6216945?v=4","01M6ADEWWFPS191NFM0Y1EX1JH","Daniel Avila","01M6ADJHGM78PHQRD3XZTFDVKK",33481,"MIT","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fcosmic-database\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000010","后端与接口","SCENARIO","使用场景",[24,25,26,27,28,29,30,31,32,33,34,35,36,37],"database","cosmic database","research","authentication","access","mutations","somatic","query","signatures","mutation","precision oncology","for","gene","oncology","2026-11-10 10:12:30",false,"---\nname: cosmic-database\ndescription: \"Access COSMIC cancer mutation database. Query somatic mutations, Cancer Gene Census, mutational signatures, gene fusions, for cancer research and precision oncology. Requires authentication.\"\n---\n\n# COSMIC Database\n\n## Overview\n\nCOSMIC (Catalogue of Somatic Mutations in Cancer) is the world's largest and most comprehensive database for exploring somatic mutations in human cancer. Access COSMIC's extensive collection of cancer genomics data, including millions of mutations across thousands of cancer types, curated gene lists, mutational signatures, and clinical annotations programmatically.\n\n## When to Use This Skill\n\nThis skill should be used when:\n- Downloading cancer mutation data from COSMIC\n- Accessing the Cancer Gene Census for curated cancer gene lists\n- Retrieving mutational signature profiles\n- Querying structural variants, copy number alterations, or gene fusions\n- Analyzing drug resistance mutations\n- Working with cancer cell line genomics data\n- Integrating cancer mutation data into bioinformatics pipelines\n- Researching specific genes or mutations in cancer contexts\n\n## Prerequisites\n\n### Account Registration\nCOSMIC requires authentication for data downloads:\n- **Academic users**: Free access with registration at https:\u002F\u002Fcancer.sanger.ac.uk\u002Fcosmic\u002Fregister\n- **Commercial users**: License required (contact QIAGEN)\n\n### Python Requirements\n```bash\nuv pip install requests pandas\n```\n\n## Quick Start\n\n### 1. Basic File Download\n\nUse the `scripts\u002Fdownload_cosmic.py` script to download COSMIC data files:\n\n```python\nfrom scripts.download_cosmic import download_cosmic_file\n\n# Download mutation data\ndownload_cosmic_file(\n    email=\"your_email@institution.edu\",\n    password=\"your_password\",\n    filepath=\"GRCh38\u002Fcosmic\u002Flatest\u002FCosmicMutantExport.tsv.gz\",\n    output_filename=\"cosmic_mutations.tsv.gz\"\n)\n```\n\n### 2. Command-Line Usage\n\n```bash\n# Download using shorthand data type\npython scripts\u002Fdownload_cosmic.py user@email.com --data-type mutations\n\n# Download specific file\npython scripts\u002Fdownload_cosmic.py user@email.com \\\n    --filepath GRCh38\u002Fcosmic\u002Flatest\u002Fcancer_gene_census.csv\n\n# Download for specific genome assembly\npython scripts\u002Fdownload_cosmic.py user@email.com \\\n    --data-type gene_census --assembly GRCh37 -o cancer_genes.csv\n```\n\n### 3. Working with Downloaded Data\n\n```python\nimport pandas as pd\n\n# Read mutation data\nmutations = pd.read_csv('cosmic_mutations.tsv.gz', sep='\\t', compression='gzip')\n\n# Read Cancer Gene Census\ngene_census = pd.read_csv('cancer_gene_census.csv')\n\n# Read VCF format\nimport pysam\nvcf = pysam.VariantFile('CosmicCodingMuts.vcf.gz')\n```\n\n## Available Data Types\n\n### Core Mutations\nDownload comprehensive mutation data including point mutations, indels, and genomic annotations.\n\n**Common data types**:\n- `mutations` - Complete coding mutations (TSV format)\n- `mutations_vcf` - Coding mutations in VCF format\n- `sample_info` - Sample metadata and tumor information\n\n```python\n# Download all coding mutations\ndownload_cosmic_file(\n    email=\"user@email.com\",\n    password=\"password\",\n    filepath=\"GRCh38\u002Fcosmic\u002Flatest\u002FCosmicMutantExport.tsv.gz\"\n)\n```\n\n### Cancer Gene Census\nAccess the expert-curated list of ~700+ cancer genes with substantial evidence of cancer involvement.\n\n```python\n# Download Cancer Gene Census\ndownload_cosmic_file(\n    email=\"user@email.com\",\n    password=\"password\",\n    filepath=\"GRCh38\u002Fcosmic\u002Flatest\u002Fcancer_gene_census.csv\"\n)\n```\n\n**Use cases**:\n- Identifying known cancer genes\n- Filtering variants by cancer relevance\n- Understanding gene roles (oncogene vs tumor suppressor)\n- Target gene selection for research\n\n### Mutational Signatures\nDownload signature profiles for mutational signature analysis.\n\n```python\n# Download signature definitions\ndownload_cosmic_file(\n    email=\"user@email.com\",\n    password=\"password\",\n    filepath=\"signatures\u002Fsignatures.tsv\"\n)\n```\n\n**Signature types**:\n- Single Base Substitution (SBS) signatures\n- Doublet Base Substitution (DBS) signatures\n- Insertion\u002FDeletion (ID) signatures\n\n### Structural Variants and Fusions\nAccess gene fusion data and structural rearrangements.\n\n**Available data types**:\n- `structural_variants` - Structural breakpoints\n- `fusion_genes` - Gene fusion events\n\n```python\n# Download gene fusions\ndownload_cosmic_file(\n    email=\"user@email.com\",\n    password=\"password\",\n    filepath=\"GRCh38\u002Fcosmic\u002Flatest\u002FCosmicFusionExport.tsv.gz\"\n)\n```\n\n### Copy Number and Expression\nRetrieve copy number alterations and gene expression data.\n\n**Available data types**:\n- `copy_number` - Copy number gains\u002Flosses\n- `gene_expression` - Over\u002Funder-expression data\n\n```python\n# Download copy number data\ndownload_cosmic_file(\n    email=\"user@email.com\",\n    password=\"password\",\n    filepath=\"GRCh38\u002Fcosmic\u002Flatest\u002FCosmicCompleteCNA.tsv.gz\"\n)\n```\n\n### Resistance Mutations\nAccess drug resistance mutation data with clinical annotations.\n\n```python\n# Download resistance mutations\ndownload_cosmic_file(\n    email=\"user@email.com\",\n    password=\"password\",\n    filepath=\"GRCh38\u002Fcosmic\u002Flatest\u002FCosmicResistanceMutations.tsv.gz\"\n)\n```\n\n## Working with COSMIC Data\n\n### Genome Assemblies\nCOSMIC provides data for two reference genomes:\n- **GRCh38** (recommended, current standard)\n- **GRCh37** (legacy, for older pipelines)\n\nSpecify the assembly in file paths:\n```python\n# GRCh38 (recommended)\nfilepath=\"GRCh38\u002Fcosmic\u002Flatest\u002FCosmicMutantExport.tsv.gz\"\n\n# GRCh37 (legacy)\nfilepath=\"GRCh37\u002Fcosmic\u002Flatest\u002FCosmicMutantExport.tsv.gz\"\n```\n\n### Versioning\n- Use `latest` in file paths to always get the most recent release\n- COSMIC is updated quarterly (current version: v102, May 2025)\n- Specific versions can be used for reproducibility: `v102`, `v101`, etc.\n\n### File Formats\n- **TSV\u002FCSV**: Tab\u002Fcomma-separated, gzip compressed, read with pandas\n- **VCF**: Standard variant format, use with pysam, bcftools, or GATK\n- All files include headers describing column contents\n\n### Common Analysis Patterns\n\n**Filter mutations by gene**:\n```python\nimport pandas as pd\n\nmutations = pd.read_csv('cosmic_mutations.tsv.gz', sep='\\t', compression='gzip')\ntp53_mutations = mutations[mutations['Gene name'] == 'TP53']\n```\n\n**Identify cancer genes by role**:\n```python\ngene_census = pd.read_csv('cancer_gene_census.csv')\noncogenes = gene_census[gene_census['Role in Cancer'].str.contains('oncogene', na=False)]\ntumor_suppressors = gene_census[gene_census['Role in Cancer'].str.contains('TSG', na=False)]\n```\n\n**Extract mutations by cancer type**:\n```python\nmutations = pd.read_csv('cosmic_mutations.tsv.gz', sep='\\t', compression='gzip')\nlung_mutations = mutations[mutations['Primary site'] == 'lung']\n```\n\n**Work with VCF files**:\n```python\nimport pysam\n\nvcf = pysam.VariantFile('CosmicCodingMuts.vcf.gz')\nfor record in vcf.fetch('17', 7577000, 7579000):  # TP53 region\n    print(record.id, record.ref, record.alts, record.info)\n```\n\n## Data Reference\n\nFor comprehensive information about COSMIC data structure, available files, and field descriptions, see `references\u002Fcosmic_data_reference.md`. This reference includes:\n\n- Complete list of available data types and files\n- Detailed field descriptions for each file type\n- File format specifications\n- Common file paths and naming conventions\n- Data update schedule and versioning\n- Citation information\n\nUse this reference when:\n- Exploring what data is available in COSMIC\n- Understanding specific field meanings\n- Determining the correct file path for a data type\n- Planning analysis workflows with COSMIC data\n\n## Helper Functions\n\nThe download script includes helper functions for common operations:\n\n### Get Common File Paths\n```python\nfrom scripts.download_cosmic import get_common_file_path\n\n# Get path for mutations file\npath = get_common_file_path('mutations', genome_assembly='GRCh38')\n# Returns: 'GRCh38\u002Fcosmic\u002Flatest\u002FCosmicMutantExport.tsv.gz'\n\n# Get path for gene census\npath = get_common_file_path('gene_census')\n# Returns: 'GRCh38\u002Fcosmic\u002Flatest\u002Fcancer_gene_census.csv'\n```\n\n**Available shortcuts**:\n- `mutations` - Core coding mutations\n- `mutations_vcf` - VCF format mutations\n- `gene_census` - Cancer Gene Census\n- `resistance_mutations` - Drug resistance data\n- `structural_variants` - Structural variants\n- `gene_expression` - Expression data\n- `copy_number` - Copy number alterations\n- `fusion_genes` - Gene fusions\n- `signatures` - Mutational signatures\n- `sample_info` - Sample metadata\n\n## Troubleshooting\n\n### Authentication Errors\n- Verify email and password are correct\n- Ensure account is registered at cancer.sanger.ac.uk\u002Fcosmic\n- Check if commercial license is required for your use case\n\n### File Not Found\n- Verify the filepath is correct\n- Check that the requested version exists\n- Use `latest` for the most recent version\n- Confirm genome assembly (GRCh37 vs GRCh38) is correct\n\n### Large File Downloads\n- COSMIC files can be several GB in size\n- Ensure sufficient disk space\n- Download may take several minutes depending on connection\n- The script shows download progress for large files\n\n### Commercial Use\n- Commercial users must license COSMIC through QIAGEN\n- Contact: cosmic-translation@sanger.ac.uk\n- Academic access is free but requires registration\n\n## Integration with Other Tools\n\nCOSMIC data integrates well with:\n- **Variant annotation**: VEP, ANNOVAR, SnpEff\n- **Signature analysis**: SigProfiler, deconstructSigs, MuSiCa\n- **Cancer genomics**: cBioPortal, OncoKB, CIViC\n- **Bioinformatics**: Bioconductor, TCGA analysis tools\n- **Data science**: pandas, scikit-learn, PyTorch\n\n## Additional Resources\n\n- **COSMIC Website**: https:\u002F\u002Fcancer.sanger.ac.uk\u002Fcosmic\n- **Documentation**: https:\u002F\u002Fcancer.sanger.ac.uk\u002Fcosmic\u002Fhelp\n- **Release Notes**: https:\u002F\u002Fcancer.sanger.ac.uk\u002Fcosmic\u002Frelease_notes\n- **Contact**: cosmic@sanger.ac.uk\n\n## Citation\n\nWhen using COSMIC data, cite:\nTate JG, Bamford S, Jubb HC, et al. COSMIC: the Catalogue Of Somatic Mutations In Cancer. Nucleic Acids Research. 2019;47(D1):D941-D947.\n","# COSMIC Database\n\n## Overview\n\nCOSMIC (Catalogue of Somatic Mutations in Cancer) is the world's largest and most comprehensive database for exploring somatic mutations in human cancer. Access COSMIC's extensive collection of cancer genomics data, including millions of mutations across thousands of cancer types, curated gene lists, mutational signatures, and clinical annotations programmatically.\n\n## When to Use This Skill\n\nThis skill should be used when:\n- Downloading cancer mutation data from COSMIC\n- Accessing the Cancer Gene Census for curated cancer gene lists\n- Retrieving mutational signature profiles\n- Querying structural variants, copy number alterations, or gene fusions\n- Analyzing drug resistance mutations\n- Working with cancer cell line genomics data\n- Integrating cancer mutation data into bioinformatics pipelines\n- Researching specific genes or mutations in cancer contexts\n\n## Prerequisites\n\n### Account Registration\nCOSMIC requires authentication for data downloads:\n- **Academic users**: Free access with registration at https:\u002F\u002Fcancer.sanger.ac.uk\u002Fcosmic\u002Fregister\n- **Commercial users**: License required (contact QIAGEN)\n\n### Python Requirements\n```bash\nuv pip install requests pandas\n```\n\n## Quick Start\n\n### 1. Basic File Download\n\nUse the `scripts\u002Fdownload_cosmic.py` script to download COSMIC data files:\n\n```python\nfrom scripts.download_cosmic import download_cosmic_file\n\n# Download mutation data\ndownload_cosmic_file(\n    email=\"your_email@institution.edu\",\n    password=\"your_password\",\n    filepath=\"GRCh38\u002Fcosmic\u002Flatest\u002FCosmicMutantExport.tsv.gz\",\n    output_filename=\"cosmic_mutations.tsv.gz\"\n)\n```\n\n### 2. Command-Line Usage\n\n```bash\n# Download using shorthand data type\npython scripts\u002Fdownload_cosmic.py user@email.com --data-type mutations\n\n# Download specific file\npython scripts\u002Fdownload_cosmic.py user@email.com \\\n    --filepath GRCh38\u002Fcosmic\u002Flatest\u002Fcancer_gene_census.csv\n\n# Download for specific genome assembly\npython scripts\u002Fdownload_cosmic.py user@email.com \\\n    --data-type gene_census --assembly GRCh37 -o cancer_genes.csv\n```\n\n### 3. Working with Downloaded Data\n\n```python\nimport pandas as pd\n\n# Read mutation data\nmutations = pd.read_csv('cosmic_mutations.tsv.gz', sep='\\t', compression='gzip')\n\n# Read Cancer Gene Census\ngene_census = pd.read_csv('cancer_gene_census.csv')\n\n# Read VCF format\nimport pysam\nvcf = pysam.VariantFile('CosmicCodingMuts.vcf.gz')\n```\n\n## Available Data Types\n\n### Core Mutations\nDownload comprehensive mutation data including point mutations, indels, and genomic annotations.\n\n**Common data types**:\n- `mutations` - Complete coding mutations (TSV format)\n- `mutations_vcf` - Coding mutations in VCF format\n- `sample_info` - Sample metadata and tumor information\n\n```python\n# Download all coding mutations\ndownload_cosmic_file(\n    email=\"user@email.com\",\n    password=\"password\",\n    filepath=\"GRCh38\u002Fcosmic\u002Flatest\u002FCosmicMutantExport.tsv.gz\"\n)\n```\n\n### Cancer Gene Census\nAccess the expert-curated list of ~700+ cancer genes with substantial evidence of cancer involvement.\n\n```python\n# Download Cancer Gene Census\ndownload_cosmic_file(\n    email=\"user@email.com\",\n    password=\"password\",\n    filepath=\"GRCh38\u002Fcosmic\u002Flatest\u002Fcancer_gene_census.csv\"\n)\n```\n\n**Use cases**:\n- Identifying known cancer genes\n- Filtering variants by cancer relevance\n- Understanding gene roles (oncogene vs tumor suppressor)\n- Target gene selection for research\n\n### Mutational Signatures\nDownload signature profiles for mutational signature analysis.\n\n```python\n# Download signature definitions\ndownload_cosmic_file(\n    email=\"user@email.com\",\n    password=\"password\",\n    filepath=\"signatures\u002Fsignatures.tsv\"\n)\n```\n\n**Signature types**:\n- Single Base Substitution (SBS) signatures\n- Doublet Base Substitution (DBS) signatures\n- Insertion\u002FDeletion (ID) signatures\n\n### Structural Variants and Fusions\nAccess gene fusion data and structural rearrangements.\n\n**Available data types**:\n- `structural_variants` - Structural breakpoints\n- `fusion_genes` - Gene fusion events\n\n```python\n# Download gene fusions\ndownload_cosmic_file(\n    email=\"user@email.com\",\n    password=\"password\",\n    filepath=\"GRCh38\u002Fcosmic\u002Flatest\u002FCosmicFusionExport.tsv.gz\"\n)\n```\n\n### Copy Number and Expression\nRetrieve copy number alterations and gene expression data.\n\n**Available data types**:\n- `copy_number` - Copy number gains\u002Flosses\n- `gene_expression` - Over\u002Funder-expression data\n\n```python\n# Download copy number data\ndownload_cosmic_file(\n    email=\"user@email.com\",\n    password=\"password\",\n    filepath=\"GRCh38\u002Fcosmic\u002Flatest\u002FCosmicCompleteCNA.tsv.gz\"\n)\n```\n\n### Resistance Mutations\nAccess drug resistance mutation data with clinical annotations.\n\n```python\n# Download resistance mutations\ndownload_cosmic_file(\n    email=\"user@email.com\",\n    password=\"password\",\n    filepath=\"GRCh38\u002Fcosmic\u002Flatest\u002FCosmicResistanceMutations.tsv.gz\"\n)\n```\n\n## Working with COSMIC Data\n\n### Genome Assemblies\nCOSMIC provides data for two reference genomes:\n- **GRCh38** (recommended, current standard)\n- **GRCh37** (legacy, for older pipelines)\n\nSpecify the assembly in file paths:\n```python\n# GRCh38 (recommended)\nfilepath=\"GRCh38\u002Fcosmic\u002Flatest\u002FCosmicMutantExport.tsv.gz\"\n\n# GRCh37 (legacy)\nfilepath=\"GRCh37\u002Fcosmic\u002Flatest\u002FCosmicMutantExport.tsv.gz\"\n```\n\n### Versioning\n- Use `latest` in file paths to always get the most recent release\n- COSMIC is updated quarterly (current version: v102, May 2025)\n- Specific versions can be used for reproducibility: `v102`, `v101`, etc.\n\n### File Formats\n- **TSV\u002FCSV**: Tab\u002Fcomma-separated, gzip compressed, read with pandas\n- **VCF**: Standard variant format, use with pysam, bcftools, or GATK\n- All files include headers describing column contents\n\n### Common Analysis Patterns\n\n**Filter mutations by gene**:\n```python\nimport pandas as pd\n\nmutations = pd.read_csv('cosmic_mutations.tsv.gz', sep='\\t', compression='gzip')\ntp53_mutations = mutations[mutations['Gene name'] == 'TP53']\n```\n\n**Identify cancer genes by role**:\n```python\ngene_census = pd.read_csv('cancer_gene_census.csv')\noncogenes = gene_census[gene_census['Role in Cancer'].str.contains('oncogene', na=False)]\ntumor_suppressors = gene_census[gene_census['Role in Cancer'].str.contains('TSG', na=False)]\n```\n\n**Extract mutations by cancer type**:\n```python\nmutations = pd.read_csv('cosmic_mutations.tsv.gz', sep='\\t', compression='gzip')\nlung_mutations = mutations[mutations['Primary site'] == 'lung']\n```\n\n**Work with VCF files**:\n```python\nimport pysam\n\nvcf = pysam.VariantFile('CosmicCodingMuts.vcf.gz')\nfor record in vcf.fetch('17', 7577000, 7579000):  # TP53 region\n    print(record.id, record.ref, record.alts, record.info)\n```\n\n## Data Reference\n\nFor comprehensive information about COSMIC data structure, available files, and field descriptions, see `references\u002Fcosmic_data_reference.md`. This reference includes:\n\n- Complete list of available data types and files\n- Detailed field descriptions for each file type\n- File format specifications\n- Common file paths and naming conventions\n- Data update schedule and versioning\n- Citation information\n\nUse this reference when:\n- Exploring what data is available in COSMIC\n- Understanding specific field meanings\n- Determining the correct file path for a data type\n- Planning analysis workflows with COSMIC data\n\n## Helper Functions\n\nThe download script includes helper functions for common operations:\n\n### Get Common File Paths\n```python\nfrom scripts.download_cosmic import get_common_file_path\n\n# Get path for mutations file\npath = get_common_file_path('mutations', genome_assembly='GRCh38')\n# Returns: 'GRCh38\u002Fcosmic\u002Flatest\u002FCosmicMutantExport.tsv.gz'\n\n# Get path for gene census\npath = get_common_file_path('gene_census')\n# Returns: 'GRCh38\u002Fcosmic\u002Flatest\u002Fcancer_gene_census.csv'\n```\n\n**Available shortcuts**:\n- `mutations` - Core coding mutations\n- `mutations_vcf` - VCF format mutations\n- `gene_census` - Cancer Gene Census\n- `resistance_mutations` - Drug resistance data\n- `structural_variants` - Structural variants\n- `gene_expression` - Expression data\n- `copy_number` - Copy number alterations\n- `fusion_genes` - Gene fusions\n- `signatures` - Mutational signatures\n- `sample_info` - Sample metadata\n\n## Troubleshooting\n\n### Authentication Errors\n- Verify email and password are correct\n- Ensure account is registered at cancer.sanger.ac.uk\u002Fcosmic\n- Check if commercial license is required for your use case\n\n### File Not Found\n- Verify the filepath is correct\n- Check that the requested version exists\n- Use `latest` for the most recent version\n- Confirm genome assembly (GRCh37 vs GRCh38) is correct\n\n### Large File Downloads\n- COSMIC files can be several GB in size\n- Ensure sufficient disk space\n- Download may take several minutes depending on connection\n- The script shows download progress for large files\n\n### Commercial Use\n- Commercial users must license COSMIC through QIAGEN\n- Contact: cosmic-translation@sanger.ac.uk\n- Academic access is free but requires registration\n\n## Integration with Other Tools\n\nCOSMIC data integrates well with:\n- **Variant annotation**: VEP, ANNOVAR, SnpEff\n- **Signature analysis**: SigProfiler, deconstructSigs, MuSiCa\n- **Cancer genomics**: cBioPortal, OncoKB, CIViC\n- **Bioinformatics**: Bioconductor, TCGA analysis tools\n- **Data science**: pandas, scikit-learn, PyTorch\n\n## Additional Resources\n\n- **COSMIC Website**: https:\u002F\u002Fcancer.sanger.ac.uk\u002Fcosmic\n- **Documentation**: https:\u002F\u002Fcancer.sanger.ac.uk\u002Fcosmic\u002Fhelp\n- **Release Notes**: https:\u002F\u002Fcancer.sanger.ac.uk\u002Fcosmic\u002Frelease_notes\n- **Contact**: cosmic@sanger.ac.uk\n\n## Citation\n\nWhen using COSMIC data, cite:\nTate JG, Bamford S, Jubb HC, et al. COSMIC: the Catalogue Of Somatic Mutations In Cancer. Nucleic Acids Research. 2019;47(D1):D941-D947.\n",{"name":5,"description":7},"main","2b749c82b5d11fac39d9a6e021ce3f5b8a541bd1","cli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fcosmic-database",3931,"https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates","https:\u002F\u002Faitmpl.com","https:\u002F\u002Fgithub.com\u002Fdavila7","https:\u002F\u002Fdanielavila.me","Building AI dev tools with LLMs","2026-11-14 06:14:46",{"source":8,"skillName":5,"commands":54,"prompt":64,"zipAvailable":65},[55,58,61],{"tool":56,"command":57},"npx","npx skills add davila7\u002Fclaude-code-templates --skill cosmic-database",{"tool":59,"command":60},"bunx","bunx skills add davila7\u002Fclaude-code-templates --skill cosmic-database",{"tool":62,"command":63},"pnpm","pnpm dlx skills add davila7\u002Fclaude-code-templates --skill cosmic-database","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fcosmic-database\u002FSKILL.md",true,[67,73],{"path":68,"resourceType":69,"resourceTypeDesc":70,"sizeBytes":71,"sourceHtmlUrl":72},"references\u002Fcosmic_data_reference.md","REFERENCE","参考文档",6291,"https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fcosmic-database\u002Freferences\u002Fcosmic_data_reference.md",{"path":74,"resourceType":75,"resourceTypeDesc":76,"sizeBytes":77,"sourceHtmlUrl":78},"scripts\u002Fdownload_cosmic.py","SCRIPT","脚本",7974,"https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fcosmic-database\u002Fscripts\u002Fdownload_cosmic.py",[80,109,136,164,199,223],{"skillNo":81,"name":82,"nameZh":6,"description":83,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":84,"categories":85,"keywords":89,"publishedAt":38},"01M70NHBTQ8BV0A2SCAZXEPHCX","wealthville-pool-scoring","Score DeFi liquidity pools before providing liquidity. Returns a 0-100 pool score and an Enter\u002FHold\u002FExit\u002FReduce\u002FAvoid verdict with calibrated confidence for ~68,800 Solana pools and 575 EVM pools, plus a public miss-inclusive track record. Use when asked whether a pool is worth LPing into, which pools look best right now, or how accurate the scores have actually been.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fweb-data\u002Fwealthville-pool-scoring\u002FSKILL.md",[86],{"categoryNo":87,"categoryName":88,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发",[90,91,92,93,94,35,95,96,97,98,99,100,101,102,103,104,105,106,107,108],"scoring","pool","wealthville pool scoring","liquidity","which","exit","now","use","when","reduce","with","record","track","verdict","evm","solana","how","public","look",{"skillNo":110,"name":111,"nameZh":6,"description":112,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":113,"categories":114,"keywords":116,"publishedAt":38},"01M70MB6VR8ERJ4EM8D5KHBMEV","technical-debt-auditor","Scans a codebase and produces a quantified technical debt report with a prioritized remediation plan. Analyzes dead code, TODO\u002FFIXME\u002FHACK markers, dependency staleness, complexity hotspots, code duplication signals, test coverage gaps, unused exports, and outdated patterns. Use this skill when the user asks to audit their codebase for tech debt, wants a health check of their code quality, says things like \"where should I focus refactoring\", \"find code smells\", \"audit my codebase\", \"what technical debt do we have\", \"prioritize cleanup work\", or asks about code quality metrics. Also trigger when the user mentions \"code rot\", \"legacy cleanup\", \"refactoring priorities\", or wants to understand the overall health of a project before a major effort. Trigger even if the user doesn't say \"technical debt\" explicitly — any request to systematically assess code quality and identify improvement priorities belongs here.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fdevelopment\u002Ftechnical-debt-auditor\u002FSKILL.md",[115],{"categoryNo":87,"categoryName":88,"taxonomyType":21,"taxonomyTypeDesc":22},[117,118,119,120,121,122,123,124,125,126,127,98,128,129,130,131,132,133,134,135],"technical debt","debt","technical","technical debt auditor","auditor","coverage","complexity","markers","project","cleanup","unused","code","todo","work","plan","focus","signals","audit","dependency",{"skillNo":137,"name":138,"nameZh":6,"description":139,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":140,"categories":141,"keywords":149,"publishedAt":38},"01M70KPYH9QNHCNME5GJQGE22K","readonly-sql-guard","Make an agent's database access provably read-only. Use when an agent runs caller-supplied SQL against a production\u002FERP\u002Fanalytics database (a \"query\" MCP tool, text-to-SQL, an admin console), or when reviewing DB-access code for write\u002FDDL\u002Fside-effect\u002Ftransaction-escape risks. Checks what a statement CALLS, not just its shape.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fdatabase\u002Freadonly-sql-guard\u002FSKILL.md",[142,143,144],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":87,"categoryName":88,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":145,"categoryName":146,"taxonomyType":147,"taxonomyTypeDesc":148},"01JBSEEDCAT000000000000033","数据分析师","PROFESSION","适用职业",[150,151,152,153,154,155,156,35,157,158,159,160,161,162,163,97,28,24,98,31],"readonly","guard","sql guard","sql","readonly sql guard","erp","effect","read-only","db","just","tool","calls","only","MCP",{"skillNo":165,"name":166,"nameZh":6,"description":167,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":168,"licenseFileUrl":169,"sourceHtmlUrl":170,"categories":171,"keywords":175,"publishedAt":38},"01M6AFY6F7CC2BBZP1QD6VTNVC","web-artifacts-builder","Suite of tools for creating elaborate, multi-component claude.ai HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn\u002Fui). Use for complex artifacts requiring state management, routing, or shadcn\u002Fui components - not for simple single-file HTML\u002FJSX artifacts.","Apache-2.0","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Futilities\u002Fweb-artifacts-builder\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Futilities\u002Fweb-artifacts-builder\u002FSKILL.md",[172],{"categoryNo":173,"categoryName":174,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000009","前端开发",[176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,35,198],"artifacts builder","web","web artifacts builder","artifacts","builder","state","routing","state management","component","css","frontend","ui","Tools","file","components","shadcn","react","Tailwind","suite","jsx","html","single-file","ui components",{"skillNo":200,"name":201,"nameZh":6,"description":202,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":168,"licenseFileUrl":203,"sourceHtmlUrl":204,"categories":205,"keywords":210,"publishedAt":38},"01M6AFWF33SFV9Z3SF4PEEE4BF","webapp-testing","Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fsecurity\u002Fwebapp-testing\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fsecurity\u002Fwebapp-testing\u002FSKILL.md",[206,209],{"categoryNo":207,"categoryName":208,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":173,"categoryName":174,"taxonomyType":21,"taxonomyTypeDesc":22},[211,212,213,214,215,177,216,186,187,217,218,219,220,35,221,100,222],"webapp testing","testing","webapp","browser","playwright","applications","debugging","toolkit","logs","screenshots","local","behavior",{"skillNo":224,"name":225,"nameZh":6,"description":226,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":168,"licenseFileUrl":227,"sourceHtmlUrl":228,"categories":229,"keywords":237,"publishedAt":38},"01M6AF67Q67JJJ5V51JR2P52KA","discernment-nudge","After you give a substantive answer or draft that the user may act on — advice or recommendations, drafted artifacts such as goals, plans, pitches, proposals, or emails, estimates or projections, analysis or interpretation of data, factual claims they may rely on, or a multi-step argument — invoke this skill BEFORE finalizing your reply and then, if it applies, append 2-3 short follow-up questions, each tied to something specific in what you just produced, that help the user check key facts, probe the reasoning or assumptions, and notice missing context. Do this at most once per conversation. Skip it when the user asked a trivial how-to or simple lookup, wants a purely educational explanation, asked you only to format, convert, or assemble a file from content they provided, is writing code they will run, is doing creative writing or casual chat, or already asked you to double-check, cite, or review — the skill file explains these boundaries and the exact output format.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fproductivity\u002Fdiscernment-nudge\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fproductivity\u002Fdiscernment-nudge\u002FSKILL.md",[230,233,234],{"categoryNo":231,"categoryName":232,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000018","写作与文案",{"categoryNo":87,"categoryName":88,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":235,"categoryName":236,"taxonomyType":147,"taxonomyTypeDesc":148},"01JBSEEDCAT000000000000036","内容创作者",[238,239,240,241,242,243,244,245,179,246,189,128,247,248,249,250,251,162,252,98,253,254,255,256,257,106,258],"discernment nudge","nudge","interpretation","help","run","reasoning","data","writing","lookup","content","review","conversation","short","up","invoke","you","analysis","claims","argument","assemble","recommendations"]