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Agent skills
claude-code

Topic: claude-code

35,830 skills in this topic.

bio-flow-cytometry-cytometry-qc Comprehensive quality control for flow cytometry and CyTOF data. Covers flow rate stability, signal drift, margin events, dead cell exclusion, and batch QC. Use when assessing acquisition quality or identifying problematic samples before analysis.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-entrez-fetch
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-orchestrator Meta-agent that routes bioinformatics requests to specialised sub-skills. Handles file type detection, analysis planning, report generation, and reproducibility export.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-experimental-design-multiple-testing
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-phylo-distance-calculations
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-flow-cytometry-clustering-phenotyping Unsupervised clustering and cell type identification for flow/mass cytometry. Covers FlowSOM, Phenograph, and CATALYST workflows. Use when discovering cell populations in high-dimensional cytometry data without predefined gates.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-data-visualization-volcano-customization
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-filter-sequences Filter and select sequences by criteria (length, ID, GC content, patterns) using Biopython. Use when subsetting sequences, removing unwanted records, or selecting by specific criteria.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-fastq-quality Work with FASTQ quality scores using Biopython. Use when analyzing read quality, filtering by quality, trimming low-quality bases, or generating quality reports.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-microbiome-differential-abundance Differential abundance testing for microbiome data using compositionally-aware methods like ALDEx2, ANCOM-BC2, and MaAsLin2. Use when identifying taxa that differ between experimental groups while accounting for the compositional nature of microbiome data.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-flow-cytometry-gating-analysis Manual and automated gating for defining cell populations in flow cytometry. Covers rectangular, polygon, and data-driven gates. Use when identifying cell populations through hierarchical gating strategies.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-comparative-genomics-ortholog-inference
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
antibody-design-agent
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-gatk-variant-calling Variant calling with GATK HaplotypeCaller following best practices. Covers germline SNP/indel calling, GVCF workflow for cohorts, joint genotyping, and variant quality score recalibration (VQSR). Use when calling variants with GATK HaplotypeCaller.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-metabolomics-targeted-analysis Targeted metabolomics analysis using MRM/SRM with standard curves. Covers absolute quantification, method validation, and quality assessment. Use when quantifying specific metabolites using calibration curves and internal standards.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
MAGE
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-pdb-structure-io Parse and write protein structure files using Biopython Bio.PDB. Use when reading PDB, mmCIF, and MMTF files, downloading structures from RCSB PDB, or writing structures to various formats.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-fragment-analysis Analyzes cfDNA fragment size distributions and fragmentomics features using FinaleToolkit or Griffin. Extracts nucleosome positioning patterns, fragment ratios, and DELFI-style fragmentation profiles for cancer detection. Use when leveraging fragment patterns for tumor detection or tissue-of-origin analysis.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-differential-expression-timeseries-de Analyze time-series RNA-seq data using limma voom with splines, maSigPro, and ImpulseDE2. Identify genes with dynamic expression patterns. Use when analyzing time-series or longitudinal expression data.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-atac-seq-footprinting Detect transcription factor binding sites through footprinting analysis in ATAC-seq data using TOBIAS. Use when identifying TF occupancy patterns within accessible regions, as TF binding protects DNA from Tn5 cutting.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-alignment-filtering
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-data-visualization-genome-browser-tracks
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-chipseq-peak-calling ChIP-seq peak calling using MACS3 (or MACS2). Call narrow peaks for transcription factors or broad peaks for histone modifications. Supports input control, fragment size modeling, and various output formats including narrowPeak and broadPeak BED files. Use when calling peaks from ChIP-seq alignments.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
bio-atac-seq-atac-peak-calling Call accessible chromatin regions from ATAC-seq data using MACS3 with ATAC-specific parameters. Use when identifying open chromatin regions from aligned ATAC-seq BAM files, different from ChIP-seq peak calling.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009