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Read\u002Fwrite SAM\u002FBAM\u002FCRAM alignments, VCF\u002FBCF variants, FASTA\u002FFASTQ sequences, extract regions, calculate coverage, for NGS data processing pipelines.","henriquescastilho\u002Fmy-claude","henriquescastilho","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F153296945?v=4","01M6ESH7EXPXTH9CVQ4K16SRG8","Henrique Scheer","01M6ESH7JHEK2PTNNH4HEH787Z",0,"MIT","https:\u002F\u002Fgithub.com\u002Fhenriquescastilho\u002Fmy-claude\u002Fblob\u002Fmain\u002F.codex\u002Fvendor_imports\u002Fclaude\u002Fmarketplaces\u002Fclaude-scientific-skills\u002Fscientific-skills\u002Fpysam\u002FSKILL.md",[],[5,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35],"coverage","processing","vcf","sam","bam","FASTQ","NGS","pipelines","extract","toolkit","write","read","calculate","data processing pipelines","data processing","data","file","2026-11-10 10:12:30",false,"---\nname: pysam\ndescription: Genomic file toolkit. Read\u002Fwrite SAM\u002FBAM\u002FCRAM alignments, VCF\u002FBCF variants, FASTA\u002FFASTQ sequences, extract regions, calculate coverage, for NGS data processing pipelines.\nlicense: MIT license\nmetadata:\n    skill-author: K-Dense Inc.\n---\n\n# Pysam\n\n## Overview\n\nPysam is a Python module for reading, manipulating, and writing genomic datasets. Read\u002Fwrite SAM\u002FBAM\u002FCRAM alignment files, VCF\u002FBCF variant files, and FASTA\u002FFASTQ sequences with a Pythonic interface to htslib. Query tabix-indexed files, perform pileup analysis for coverage, and execute samtools\u002Fbcftools commands.\n\n## When to Use This Skill\n\nThis skill should be used when:\n- Working with sequencing alignment files (BAM\u002FCRAM)\n- Analyzing genetic variants (VCF\u002FBCF)\n- Extracting reference sequences or gene regions\n- Processing raw sequencing data (FASTQ)\n- Calculating coverage or read depth\n- Implementing bioinformatics analysis pipelines\n- Quality control of sequencing data\n- Variant calling and annotation workflows\n\n## Quick Start\n\n### Installation\n```bash\nuv pip install pysam\n```\n\n### Basic Examples\n\n**Read alignment file:**\n```python\nimport pysam\n\n# Open BAM file and fetch reads in region\nsamfile = pysam.AlignmentFile(\"example.bam\", \"rb\")\nfor read in samfile.fetch(\"chr1\", 1000, 2000):\n    print(f\"{read.query_name}: {read.reference_start}\")\nsamfile.close()\n```\n\n**Read variant file:**\n```python\n# Open VCF file and iterate variants\nvcf = pysam.VariantFile(\"variants.vcf\")\nfor variant in vcf:\n    print(f\"{variant.chrom}:{variant.pos} {variant.ref}>{variant.alts}\")\nvcf.close()\n```\n\n**Query reference sequence:**\n```python\n# Open FASTA and extract sequence\nfasta = pysam.FastaFile(\"reference.fasta\")\nsequence = fasta.fetch(\"chr1\", 1000, 2000)\nprint(sequence)\nfasta.close()\n```\n\n## Core Capabilities\n\n### 1. Alignment File Operations (SAM\u002FBAM\u002FCRAM)\n\nUse the `AlignmentFile` class to work with aligned sequencing reads. This is appropriate for analyzing mapping results, calculating coverage, extracting reads, or quality control.\n\n**Common operations:**\n- Open and read BAM\u002FSAM\u002FCRAM files\n- Fetch reads from specific genomic regions\n- Filter reads by mapping quality, flags, or other criteria\n- Write filtered or modified alignments\n- Calculate coverage statistics\n- Perform pileup analysis (base-by-base coverage)\n- Access read sequences, quality scores, and alignment information\n\n**Reference:** See `references\u002Falignment_files.md` for detailed documentation on:\n- Opening and reading alignment files\n- AlignedSegment attributes and methods\n- Region-based fetching with `fetch()`\n- Pileup analysis for coverage\n- Writing and creating BAM files\n- Coordinate systems and indexing\n- Performance optimization tips\n\n### 2. Variant File Operations (VCF\u002FBCF)\n\nUse the `VariantFile` class to work with genetic variants from variant calling pipelines. This is appropriate for variant analysis, filtering, annotation, or population genetics.\n\n**Common operations:**\n- Read and write VCF\u002FBCF files\n- Query variants in specific regions\n- Access variant information (position, alleles, quality)\n- Extract genotype data for samples\n- Filter variants by quality, allele frequency, or other criteria\n- Annotate variants with additional information\n- Subset samples or regions\n\n**Reference:** See `references\u002Fvariant_files.md` for detailed documentation on:\n- Opening and reading variant files\n- VariantRecord attributes and methods\n- Accessing INFO and FORMAT fields\n- Working with genotypes and samples\n- Creating and writing VCF files\n- Filtering and subsetting variants\n- Multi-sample VCF operations\n\n### 3. Sequence File Operations (FASTA\u002FFASTQ)\n\nUse `FastaFile` for random access to reference sequences and `FastxFile` for reading raw sequencing data. This is appropriate for extracting gene sequences, validating variants against reference, or processing raw reads.\n\n**Common operations:**\n- Query reference sequences by genomic coordinates\n- Extract sequences for genes or regions of interest\n- Read FASTQ files with quality scores\n- Validate variant reference alleles\n- Calculate sequence statistics\n- Filter reads by quality or length\n- Convert between FASTA and FASTQ formats\n\n**Reference:** See `references\u002Fsequence_files.md` for detailed documentation on:\n- FASTA file access and indexing\n- Extracting sequences by region\n- Handling reverse complement for genes\n- Reading FASTQ files sequentially\n- Quality score conversion and filtering\n- Working with tabix-indexed files (BED, GTF, GFF)\n- Common sequence processing patterns\n\n### 4. Integrated Bioinformatics Workflows\n\nPysam excels at integrating multiple file types for comprehensive genomic analyses. Common workflows combine alignment files, variant files, and reference sequences.\n\n**Common workflows:**\n- Calculate coverage statistics for specific regions\n- Validate variants against aligned reads\n- Annotate variants with coverage information\n- Extract sequences around variant positions\n- Filter alignments or variants based on multiple criteria\n- Generate coverage tracks for visualization\n- Quality control across multiple data types\n\n**Reference:** See `references\u002Fcommon_workflows.md` for detailed examples of:\n- Quality control workflows (BAM statistics, reference consistency)\n- Coverage analysis (per-base coverage, low coverage detection)\n- Variant analysis (annotation, filtering by read support)\n- Sequence extraction (variant contexts, gene sequences)\n- Read filtering and subsetting\n- Integration patterns (BAM+VCF, VCF+BED, etc.)\n- Performance optimization for complex workflows\n\n## Key Concepts\n\n### Coordinate Systems\n\n**Critical:** Pysam uses **0-based, half-open** coordinates (Python convention):\n- Start positions are 0-based (first base is position 0)\n- End positions are exclusive (not included in the range)\n- Region 1000-2000 includes bases 1000-1999 (1000 bases total)\n\n**Exception:** Region strings in `fetch()` follow samtools convention (1-based):\n```python\nsamfile.fetch(\"chr1\", 999, 2000)      # 0-based: positions 999-1999\nsamfile.fetch(\"chr1:1000-2000\")       # 1-based string: positions 1000-2000\n```\n\n**VCF files:** Use 1-based coordinates in the file format, but `VariantRecord.start` is 0-based.\n\n### Indexing Requirements\n\nRandom access to specific genomic regions requires index files:\n- **BAM files**: Require `.bai` index (create with `pysam.index()`)\n- **CRAM files**: Require `.crai` index\n- **FASTA files**: Require `.fai` index (create with `pysam.faidx()`)\n- **VCF.gz files**: Require `.tbi` tabix index (create with `pysam.tabix_index()`)\n- **BCF files**: Require `.csi` index\n\nWithout an index, use `fetch(until_eof=True)` for sequential reading.\n\n### File Modes\n\nSpecify format when opening files:\n- `\"rb\"` - Read BAM (binary)\n- `\"r\"` - Read SAM (text)\n- `\"rc\"` - Read CRAM\n- `\"wb\"` - Write BAM\n- `\"w\"` - Write SAM\n- `\"wc\"` - Write CRAM\n\n### Performance Considerations\n\n1. **Always use indexed files** for random access operations\n2. **Use `pileup()` for column-wise analysis** instead of repeated fetch operations\n3. **Use `count()` for counting** instead of iterating and counting manually\n4. **Process regions in parallel** when analyzing independent genomic regions\n5. **Close files explicitly** to free resources\n6. **Use `until_eof=True`** for sequential processing without index\n7. **Avoid multiple iterators** unless necessary (use `multiple_iterators=True` if needed)\n\n## Common Pitfalls\n\n1. **Coordinate confusion:** Remember 0-based vs 1-based systems in different contexts\n2. **Missing indices:** Many operations require index files—create them first\n3. **Partial overlaps:** `fetch()` returns reads overlapping region boundaries, not just those fully contained\n4. **Iterator scope:** Keep pileup iterator references alive to avoid \"PileupProxy accessed after iterator finished\" errors\n5. **Quality score editing:** Cannot modify `query_qualities` in place after changing `query_sequence`—create a copy first\n6. **Stream limitations:** Only stdin\u002Fstdout are supported for streaming, not arbitrary Python file objects\n7. **Thread safety:** While GIL is released during I\u002FO, comprehensive thread-safety hasn't been fully validated\n\n## Command-Line Tools\n\nPysam provides access to samtools and bcftools commands:\n\n```python\n# Sort BAM file\npysam.samtools.sort(\"-o\", \"sorted.bam\", \"input.bam\")\n\n# Index BAM\npysam.samtools.index(\"sorted.bam\")\n\n# View specific region\npysam.samtools.view(\"-b\", \"-o\", \"region.bam\", \"input.bam\", \"chr1:1000-2000\")\n\n# BCF tools\npysam.bcftools.view(\"-O\", \"z\", \"-o\", \"output.vcf.gz\", \"input.vcf\")\n```\n\n**Error handling:**\n```python\ntry:\n    pysam.samtools.sort(\"-o\", \"output.bam\", \"input.bam\")\nexcept pysam.SamtoolsError as e:\n    print(f\"Error: {e}\")\n```\n\n## Resources\n\n### references\u002F\n\nDetailed documentation for each major capability:\n\n- **alignment_files.md** - Complete guide to SAM\u002FBAM\u002FCRAM operations, including AlignmentFile class, AlignedSegment attributes, fetch operations, pileup analysis, and writing alignments\n\n- **variant_files.md** - Complete guide to VCF\u002FBCF operations, including VariantFile class, VariantRecord attributes, genotype handling, INFO\u002FFORMAT fields, and multi-sample operations\n\n- **sequence_files.md** - Complete guide to FASTA\u002FFASTQ operations, including FastaFile and FastxFile classes, sequence extraction, quality score handling, and tabix-indexed file access\n\n- **common_workflows.md** - Practical examples of integrated bioinformatics workflows combining multiple file types, including quality control, coverage analysis, variant validation, and sequence extraction\n\n## Getting Help\n\nFor detailed information on specific operations, refer to the appropriate reference document:\n\n- Working with BAM files or calculating coverage → `alignment_files.md`\n- Analyzing variants or genotypes → `variant_files.md`\n- Extracting sequences or processing FASTQ → `sequence_files.md`\n- Complex workflows integrating multiple file types → `common_workflows.md`\n\nOfficial documentation: https:\u002F\u002Fpysam.readthedocs.io\u002F\n\n","# Pysam\n\n## Overview\n\nPysam is a Python module for reading, manipulating, and writing genomic datasets. Read\u002Fwrite SAM\u002FBAM\u002FCRAM alignment files, VCF\u002FBCF variant files, and FASTA\u002FFASTQ sequences with a Pythonic interface to htslib. Query tabix-indexed files, perform pileup analysis for coverage, and execute samtools\u002Fbcftools commands.\n\n## When to Use This Skill\n\nThis skill should be used when:\n- Working with sequencing alignment files (BAM\u002FCRAM)\n- Analyzing genetic variants (VCF\u002FBCF)\n- Extracting reference sequences or gene regions\n- Processing raw sequencing data (FASTQ)\n- Calculating coverage or read depth\n- Implementing bioinformatics analysis pipelines\n- Quality control of sequencing data\n- Variant calling and annotation workflows\n\n## Quick Start\n\n### Installation\n```bash\nuv pip install pysam\n```\n\n### Basic Examples\n\n**Read alignment file:**\n```python\nimport pysam\n\n# Open BAM file and fetch reads in region\nsamfile = pysam.AlignmentFile(\"example.bam\", \"rb\")\nfor read in samfile.fetch(\"chr1\", 1000, 2000):\n    print(f\"{read.query_name}: {read.reference_start}\")\nsamfile.close()\n```\n\n**Read variant file:**\n```python\n# Open VCF file and iterate variants\nvcf = pysam.VariantFile(\"variants.vcf\")\nfor variant in vcf:\n    print(f\"{variant.chrom}:{variant.pos} {variant.ref}>{variant.alts}\")\nvcf.close()\n```\n\n**Query reference sequence:**\n```python\n# Open FASTA and extract sequence\nfasta = pysam.FastaFile(\"reference.fasta\")\nsequence = fasta.fetch(\"chr1\", 1000, 2000)\nprint(sequence)\nfasta.close()\n```\n\n## Core Capabilities\n\n### 1. Alignment File Operations (SAM\u002FBAM\u002FCRAM)\n\nUse the `AlignmentFile` class to work with aligned sequencing reads. This is appropriate for analyzing mapping results, calculating coverage, extracting reads, or quality control.\n\n**Common operations:**\n- Open and read BAM\u002FSAM\u002FCRAM files\n- Fetch reads from specific genomic regions\n- Filter reads by mapping quality, flags, or other criteria\n- Write filtered or modified alignments\n- Calculate coverage statistics\n- Perform pileup analysis (base-by-base coverage)\n- Access read sequences, quality scores, and alignment information\n\n**Reference:** See `references\u002Falignment_files.md` for detailed documentation on:\n- Opening and reading alignment files\n- AlignedSegment attributes and methods\n- Region-based fetching with `fetch()`\n- Pileup analysis for coverage\n- Writing and creating BAM files\n- Coordinate systems and indexing\n- Performance optimization tips\n\n### 2. Variant File Operations (VCF\u002FBCF)\n\nUse the `VariantFile` class to work with genetic variants from variant calling pipelines. This is appropriate for variant analysis, filtering, annotation, or population genetics.\n\n**Common operations:**\n- Read and write VCF\u002FBCF files\n- Query variants in specific regions\n- Access variant information (position, alleles, quality)\n- Extract genotype data for samples\n- Filter variants by quality, allele frequency, or other criteria\n- Annotate variants with additional information\n- Subset samples or regions\n\n**Reference:** See `references\u002Fvariant_files.md` for detailed documentation on:\n- Opening and reading variant files\n- VariantRecord attributes and methods\n- Accessing INFO and FORMAT fields\n- Working with genotypes and samples\n- Creating and writing VCF files\n- Filtering and subsetting variants\n- Multi-sample VCF operations\n\n### 3. Sequence File Operations (FASTA\u002FFASTQ)\n\nUse `FastaFile` for random access to reference sequences and `FastxFile` for reading raw sequencing data. This is appropriate for extracting gene sequences, validating variants against reference, or processing raw reads.\n\n**Common operations:**\n- Query reference sequences by genomic coordinates\n- Extract sequences for genes or regions of interest\n- Read FASTQ files with quality scores\n- Validate variant reference alleles\n- Calculate sequence statistics\n- Filter reads by quality or length\n- Convert between FASTA and FASTQ formats\n\n**Reference:** See `references\u002Fsequence_files.md` for detailed documentation on:\n- FASTA file access and indexing\n- Extracting sequences by region\n- Handling reverse complement for genes\n- Reading FASTQ files sequentially\n- Quality score conversion and filtering\n- Working with tabix-indexed files (BED, GTF, GFF)\n- Common sequence processing patterns\n\n### 4. Integrated Bioinformatics Workflows\n\nPysam excels at integrating multiple file types for comprehensive genomic analyses. Common workflows combine alignment files, variant files, and reference sequences.\n\n**Common workflows:**\n- Calculate coverage statistics for specific regions\n- Validate variants against aligned reads\n- Annotate variants with coverage information\n- Extract sequences around variant positions\n- Filter alignments or variants based on multiple criteria\n- Generate coverage tracks for visualization\n- Quality control across multiple data types\n\n**Reference:** See `references\u002Fcommon_workflows.md` for detailed examples of:\n- Quality control workflows (BAM statistics, reference consistency)\n- Coverage analysis (per-base coverage, low coverage detection)\n- Variant analysis (annotation, filtering by read support)\n- Sequence extraction (variant contexts, gene sequences)\n- Read filtering and subsetting\n- Integration patterns (BAM+VCF, VCF+BED, etc.)\n- Performance optimization for complex workflows\n\n## Key Concepts\n\n### Coordinate Systems\n\n**Critical:** Pysam uses **0-based, half-open** coordinates (Python convention):\n- Start positions are 0-based (first base is position 0)\n- End positions are exclusive (not included in the range)\n- Region 1000-2000 includes bases 1000-1999 (1000 bases total)\n\n**Exception:** Region strings in `fetch()` follow samtools convention (1-based):\n```python\nsamfile.fetch(\"chr1\", 999, 2000)      # 0-based: positions 999-1999\nsamfile.fetch(\"chr1:1000-2000\")       # 1-based string: positions 1000-2000\n```\n\n**VCF files:** Use 1-based coordinates in the file format, but `VariantRecord.start` is 0-based.\n\n### Indexing Requirements\n\nRandom access to specific genomic regions requires index files:\n- **BAM files**: Require `.bai` index (create with `pysam.index()`)\n- **CRAM files**: Require `.crai` index\n- **FASTA files**: Require `.fai` index (create with `pysam.faidx()`)\n- **VCF.gz files**: Require `.tbi` tabix index (create with `pysam.tabix_index()`)\n- **BCF files**: Require `.csi` index\n\nWithout an index, use `fetch(until_eof=True)` for sequential reading.\n\n### File Modes\n\nSpecify format when opening files:\n- `\"rb\"` - Read BAM (binary)\n- `\"r\"` - Read SAM (text)\n- `\"rc\"` - Read CRAM\n- `\"wb\"` - Write BAM\n- `\"w\"` - Write SAM\n- `\"wc\"` - Write CRAM\n\n### Performance Considerations\n\n1. **Always use indexed files** for random access operations\n2. **Use `pileup()` for column-wise analysis** instead of repeated fetch operations\n3. **Use `count()` for counting** instead of iterating and counting manually\n4. **Process regions in parallel** when analyzing independent genomic regions\n5. **Close files explicitly** to free resources\n6. **Use `until_eof=True`** for sequential processing without index\n7. **Avoid multiple iterators** unless necessary (use `multiple_iterators=True` if needed)\n\n## Common Pitfalls\n\n1. **Coordinate confusion:** Remember 0-based vs 1-based systems in different contexts\n2. **Missing indices:** Many operations require index files—create them first\n3. **Partial overlaps:** `fetch()` returns reads overlapping region boundaries, not just those fully contained\n4. **Iterator scope:** Keep pileup iterator references alive to avoid \"PileupProxy accessed after iterator finished\" errors\n5. **Quality score editing:** Cannot modify `query_qualities` in place after changing `query_sequence`—create a copy first\n6. **Stream limitations:** Only stdin\u002Fstdout are supported for streaming, not arbitrary Python file objects\n7. **Thread safety:** While GIL is released during I\u002FO, comprehensive thread-safety hasn't been fully validated\n\n## Command-Line Tools\n\nPysam provides access to samtools and bcftools commands:\n\n```python\n# Sort BAM file\npysam.samtools.sort(\"-o\", \"sorted.bam\", \"input.bam\")\n\n# Index BAM\npysam.samtools.index(\"sorted.bam\")\n\n# View specific region\npysam.samtools.view(\"-b\", \"-o\", \"region.bam\", \"input.bam\", \"chr1:1000-2000\")\n\n# BCF tools\npysam.bcftools.view(\"-O\", \"z\", \"-o\", \"output.vcf.gz\", \"input.vcf\")\n```\n\n**Error handling:**\n```python\ntry:\n    pysam.samtools.sort(\"-o\", \"output.bam\", \"input.bam\")\nexcept pysam.SamtoolsError as e:\n    print(f\"Error: {e}\")\n```\n\n## Resources\n\n### references\u002F\n\nDetailed documentation for each major capability:\n\n- **alignment_files.md** - Complete guide to SAM\u002FBAM\u002FCRAM operations, including AlignmentFile class, AlignedSegment attributes, fetch operations, pileup analysis, and writing alignments\n\n- **variant_files.md** - Complete guide to VCF\u002FBCF operations, including VariantFile class, VariantRecord attributes, genotype handling, INFO\u002FFORMAT fields, and multi-sample operations\n\n- **sequence_files.md** - Complete guide to FASTA\u002FFASTQ operations, including FastaFile and FastxFile classes, sequence extraction, quality score handling, and tabix-indexed file access\n\n- **common_workflows.md** - Practical examples of integrated bioinformatics workflows combining multiple file types, including quality control, coverage analysis, variant validation, and sequence extraction\n\n## Getting Help\n\nFor detailed information on specific operations, refer to the appropriate reference document:\n\n- Working with BAM files or calculating coverage → `alignment_files.md`\n- Analyzing variants or genotypes → `variant_files.md`\n- Extracting sequences or processing FASTQ → `sequence_files.md`\n- Complex workflows integrating multiple file types → `common_workflows.md`\n\nOfficial documentation: https:\u002F\u002Fpysam.readthedocs.io\u002F\n\n",{"name":5,"license":41,"metadata":42,"description":7},"MIT license",{"skill-author":43},"K-Dense Inc.","main","7925716f065257435fdb12e97f7e52842147d5ad",".codex\u002Fvendor_imports\u002Fclaude\u002Fmarketplaces\u002Fclaude-scientific-skills\u002Fscientific-skills\u002Fpysam","https:\u002F\u002Fgithub.com\u002Fhenriquescastilho\u002Fmy-claude","https:\u002F\u002Fclaude.com\u002Fclaude-code","https:\u002F\u002Fgithub.com\u002Fhenriquescastilho","Software · Applied AI · Quantitative Modeling · Building with Claude.","2026-06-10 12:24:46",{"source":8,"skillName":5,"commands":53,"prompt":63,"zipAvailable":64},[54,57,60],{"tool":55,"command":56},"npx","npx skills add henriquescastilho\u002Fmy-claude --skill pysam",{"tool":58,"command":59},"bunx","bunx skills add henriquescastilho\u002Fmy-claude --skill pysam",{"tool":61,"command":62},"pnpm","pnpm dlx skills add henriquescastilho\u002Fmy-claude --skill pysam","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fhenriquescastilho\u002Fmy-claude\u002Fblob\u002Fmain\u002F.codex\u002Fvendor_imports\u002Fclaude\u002Fmarketplaces\u002Fclaude-scientific-skills\u002Fscientific-skills\u002Fpysam\u002FSKILL.md",true,[66,72,76,80],{"path":67,"resourceType":68,"resourceTypeDesc":69,"sizeBytes":70,"sourceHtmlUrl":71},"references\u002Falignment_files.md","REFERENCE","参考文档",8560,"https:\u002F\u002Fgithub.com\u002Fhenriquescastilho\u002Fmy-claude\u002Fblob\u002Fmain\u002F.codex\u002Fvendor_imports\u002Fclaude\u002Fmarketplaces\u002Fclaude-scientific-skills\u002Fscientific-skills\u002Fpysam\u002Freferences\u002Falignment_files.md",{"path":73,"resourceType":68,"resourceTypeDesc":69,"sizeBytes":74,"sourceHtmlUrl":75},"references\u002Fcommon_workflows.md",15350,"https:\u002F\u002Fgithub.com\u002Fhenriquescastilho\u002Fmy-claude\u002Fblob\u002Fmain\u002F.codex\u002Fvendor_imports\u002Fclaude\u002Fmarketplaces\u002Fclaude-scientific-skills\u002Fscientific-skills\u002Fpysam\u002Freferences\u002Fcommon_workflows.md",{"path":77,"resourceType":68,"resourceTypeDesc":69,"sizeBytes":78,"sourceHtmlUrl":79},"references\u002Fsequence_files.md",11597,"https:\u002F\u002Fgithub.com\u002Fhenriquescastilho\u002Fmy-claude\u002Fblob\u002Fmain\u002F.codex\u002Fvendor_imports\u002Fclaude\u002Fmarketplaces\u002Fclaude-scientific-skills\u002Fscientific-skills\u002Fpysam\u002Freferences\u002Fsequence_files.md",{"path":81,"resourceType":68,"resourceTypeDesc":69,"sizeBytes":82,"sourceHtmlUrl":83},"references\u002Fvariant_files.md",9487,"https:\u002F\u002Fgithub.com\u002Fhenriquescastilho\u002Fmy-claude\u002Fblob\u002Fmain\u002F.codex\u002Fvendor_imports\u002Fclaude\u002Fmarketplaces\u002Fclaude-scientific-skills\u002Fscientific-skills\u002Fpysam\u002Freferences\u002Fvariant_files.md",[85,125,134,143,164,192],{"skillNo":86,"name":87,"nameZh":6,"description":88,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":89,"categories":90,"keywords":107,"publishedAt":36},"01M6F0B6XPQ65AX2X0DWK8KT3E","markitdown","Convert files and office documents to Markdown. 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