Topic: openclaw
3,425 skills in this topic.
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bio-systems-biology-model-curation
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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markdown-mermaid-writing
Comprehensive markdown and Mermaid diagram writing skill. Use when creating any scientific document, report, analysis, or visualization. Establishes text-based diagrams as the default documentation standard with full style guides (markdown + mermaid), 24 diagram type references, and 9 document templates.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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microbiome-cancer-agent
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-spatial-transcriptomics-spatial-neighbors
Build spatial neighbor graphs for spatial transcriptomics data using Squidpy. Compute k-nearest neighbors, Delaunay triangulation, and radius-based connectivity for downstream spatial analyses. Use when building spatial neighborhood graphs.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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spatial-data-io
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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markitdown
Convert files and office documents to Markdown. Supports PDF, DOCX, PPTX, XLSX, images (with OCR), audio (with transcription), HTML, CSV, JSON, XML, ZIP, YouTube URLs, EPubs and more.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-crispr-screens-batch-correction
Batch effect correction for CRISPR screens. Covers normalization across batches, technical replicate handling, and batch-aware analysis. Use when combining screens from multiple batches or correcting systematic technical variation.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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agentd-drug-discovery
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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simulation-orchestrator
Orchestrate multi-simulation campaigns including parameter sweeps, batch jobs, and result aggregation. Use for running parameter studies, managing simulation batches, tracking job status, combining results from multiple runs, or automating simulation workflows.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-atac-seq-atac-qc
Quality control metrics for ATAC-seq data including fragment size distribution, TSS enrichment, FRiP, and library complexity. Use when assessing ATAC-seq library quality before or after peak calling to identify problematic samples.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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STAgent
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-pathway-enrichment-visualization
Visualize enrichment results using enrichplot package functions. Use when creating publication-quality figures from clusterProfiler results. Covers dotplot, barplot, cnetplot, emapplot, gseaplot2, ridgeplot, and treeplot.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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spatial-proteomics
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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opentargets-database
Query Open Targets Platform for target-disease associations, drug target discovery, tractability/safety data, genetics/omics evidence, known drugs, for therapeutic target identification.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-chipseq-motif-analysis
De novo motif discovery and known motif enrichment analysis using HOMER and MEME-ChIP. Identify transcription factor binding motifs in ChIP-seq, ATAC-seq, or other genomic peak data. Use when finding enriched DNA motifs in peak sequences.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-epitranscriptomics-merip-preprocessing
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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bio-single-cell-multimodal-integration
Analyze multi-modal single-cell data (CITE-seq, Multiome, spatial). Use when working with data that measures multiple modalities per cell like RNA + protein or RNA + ATAC. Use when analyzing CITE-seq, Multiome, or other multi-modal single-cell data.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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rna-velocity-agent
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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ipsae
Binder design ranking using ipSAE (interprotein Score from Aligned Errors). Use this skill when: (1) Ranking binder designs for experimental testing, (2) Filtering BindCraft or RFdiffusion outputs, (3) Comparing AF2/AF3/Boltz predictions, (4) Predicting binding success rates, (5) Need better ranking than ipTM or iPAE.
For structure prediction, use chai or alphafold. For QC thresholds, use protein-qc.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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differentiation-schemes
Select and apply numerical differentiation schemes for PDE/ODE discretization. Use when choosing finite difference/volume/spectral schemes, building stencils, handling boundaries, estimating truncation error, or analyzing dispersion and dissipation.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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transformers
This skill should be used when working with pre-trained transformer models for natural language processing, computer vision, audio, or multimodal tasks. Use for text generation, classification, question answering, translation, summarization, image classification, object detection, speech recognition, and fine-tuning models on custom datasets.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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diffdock
Diffusion-based molecular docking. Predict protein-ligand binding poses from PDB/SMILES, confidence scores, virtual screening, for structure-based drug design. Not for affinity prediction.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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datacommons-client
Work with Data Commons, a platform providing programmatic access to public statistical data from global sources. Use this skill when working with demographic data, economic indicators, health statistics, environmental data, or any public datasets available through Data Commons. Applicable for querying population statistics, GDP figures, unemployment rates, disease prevalence, geographic entity resolution, and exploring relationships between statistical entities.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009
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fda-database
Query openFDA API for drugs, devices, adverse events, recalls, regulatory submissions (510k, PMA), substance identification (UNII), for FDA regulatory data analysis and safety research.
FreedomIntelligence/OpenClaw-Medical-Skills 2,009