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Claude Skills by mdbabumiamssm
github.com/mdbabumiamssm1,581 skills3 installs3,534 views
- Dia Analysis--> --- name: bio-proteomics-dia-analysis description: Data-independent acquisition (DIA) proteomics analysis with DIA-NN and other tools. Use when analyzing DIA mass spectrometry data with library-free or library-based workflows for deep proteome profiling. tool_type: cli primary_tool: diann measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Differential Abundance--> --- name: bio-proteomics-differential-abundance description: Statistical testing for differentially abundant proteins between conditions. Covers limma and MSstats workflows with multiple testing correction. Use when identifying proteins with significant abundance changes between experimental groups. tool_type: mixed primary_tool: MSstats measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Peptide Identification--> --- name: bio-proteomics-peptide-identification description: Peptide-spectrum matching and protein identification from MS/MS data. Use when identifying peptides from tandem mass spectra. Covers database searching, spectral library matching, and FDR estimation using target-decoy approaches. tool_type: mixed primary_tool: pyOpenMS measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Protein Inference--> --- name: bio-proteomics-protein-inference description: Protein grouping and inference from peptide identifications. Use when resolving protein ambiguity from shared peptides. Handles protein groups and protein-level FDR control using parsimony and probabilistic approaches. tool_type: mixed primary_tool: pyOpenMS measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Proteomics Qc--> --- name: bio-proteomics-proteomics-qc description: Quality control and assessment for proteomics data. Use when evaluating proteomics data quality before downstream analysis. Covers sample metrics, missing value patterns, replicate correlation, batch effects, and intensity distributions. tool_type: mixed primary_tool: pandas measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Ptm Analysis--> --- name: bio-proteomics-ptm-analysis description: Post-translational modification analysis including phosphorylation, acetylation, and ubiquitination. Covers site localization, motif analysis, and quantitative PTM analysis. Use when analyzing phosphoproteomic data or other modification-enriched samples. tool_type: mixed primary_tool: pyOpenMS measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Quantification--> --- name: bio-proteomics-quantification description: Protein quantification from mass spectrometry data including label-free (LFQ, intensity-based), isobaric labeling (TMT, iTRAQ), and metabolic labeling (SILAC) approaches. Use when extracting protein abundances from MS data for differential analysis. tool_type: mixed primary_tool: MSstats measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Spectral Libraries--> --- name: bio-proteomics-spectral-libraries description: Build, manage, and search spectral libraries for proteomics. Use when creating or working with spectral libraries for DIA analysis. Covers DDA-based library generation, predicted libraries (Prosit, DeepLC), and library formats. tool_type: mixed primary_tool: encyclopedia measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Arxiv Research Agent**Domain:** Research Tools / Academic Literature **Status:** ActiveVotes: 0GitHub stars: 6
- Biomni--> --- name: biomni-research-agent description: Bio-Research Generalist license: MIT metadata: author: Stanford (Snap Lab) source: "https://github.com/snap-stanford/Biomni" version: "1.0.0" compatibility: - system: Python 3.9+ allowed-tools: - run_shell_command - web_fetch - python_repl keywords: - biomni - automation - biomedical - reasoning - tools measurable_outcome: Execute complex research tasks with >95% success rate and validated tool usage. --- A general-purpose biomedical AI agent c...Votes: 0GitHub stars: 6
- Chemistry Agent--> --- name: chemistry-agent description: Autonomous chemical synthesis & analysis keywords: - chemistry - synthesis - molecules - reaction - lab-automation measurable_outcome: Successfully plans valid synthesis routes for 90% of target small molecules. license: MIT metadata: author: AI Agentic Skills Team version: "1.0.0" compatibility: - system: Python 3.10+ allowed-tools: - run_shell_command - read_file - write_file --- The Chemistry Agent is a specialized module for autonomous chemical r...Votes: 0GitHub stars: 6
- Data Analysis--> --- name: biomedical-data-analysis description: Omics data forge keywords: - pandas - R-tidyverse - SQL - visualization - reproducible measurable_outcome: Deliver a cleaned dataset + statistical summary + at least one visualization or dashboard spec for each request within 1 working session (≤30 minutes). license: MIT metadata: author: BioSkills Team version: "1.0.0" compatibility: - system: Python 3.9+ / R 4.0+ allowed-tools: - run_shell_command - read_file - python_repl --- Run the cros...Votes: 0GitHub stars: 6
- Batch Downloads--> --- name: bio-batch-downloads description: Download large datasets from NCBI efficiently using history server, batching, and rate limiting. Use when performing bulk sequence downloads, handling large query results, or production-scale data retrieval. tool_type: python primary_tool: Bio.Entrez measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- Download large numbers of records from NCBI efficiently...Votes: 0GitHub stars: 6
- Blast Searches--> --- name: bio-blast-searches description: Run remote BLAST searches against NCBI databases using Biopython Bio.Blast. Use when identifying unknown sequences, finding homologs, or searching for sequence similarity against NCBI's nr/nt databases. tool_type: python primary_tool: Bio.Blast.NCBIWWW measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- Run BLAST searches against NCBI databases using Biopyt...Votes: 0GitHub stars: 6
- Entrez Fetch--> --- name: bio-entrez-fetch description: Retrieve records from NCBI databases using Biopython Bio.Entrez. Use when downloading sequences, fetching GenBank records, getting document summaries, or parsing NCBI data into Biopython objects. tool_type: python primary_tool: Bio.Entrez measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- Retrieve records from NCBI databases using Biopython's Entrez module (...Votes: 0GitHub stars: 6
- Entrez Link--> --- name: bio-entrez-link description: Find cross-references between NCBI databases using Biopython Bio.Entrez. Use when navigating from genes to proteins, sequences to publications, finding related records, or discovering database relationships. tool_type: python primary_tool: Bio.Entrez measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- Navigate between NCBI databases using Biopython's Entrez mo...Votes: 0GitHub stars: 6
- Entrez Search--> --- name: bio-entrez-search description: Search NCBI databases using Biopython Bio.Entrez. Use when finding records by keyword, building complex search queries, discovering database structure, or getting global query counts across databases. tool_type: python primary_tool: Bio.Entrez measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- Search NCBI databases using Biopython's Entrez module (ESearch, ...Votes: 0GitHub stars: 6
- Geo Data--> --- name: bio-geo-data description: Query NCBI Gene Expression Omnibus (GEO) for expression datasets using Biopython Bio.Entrez. Use when finding microarray/RNA-seq datasets, downloading expression data, or linking GEO series to SRA runs. tool_type: python primary_tool: Bio.Entrez measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- Query and access Gene Expression Omnibus datasets using Biopython's...Votes: 0GitHub stars: 6
- Local Blast--> --- name: bio-local-blast description: Run local BLAST searches using BLAST+ command-line tools. Use when running fast unlimited searches, building custom databases, performing large-scale analysis, or when NCBI servers are slow or unavailable. tool_type: cli primary_tool: BLAST+ measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- Run BLAST searches locally using NCBI BLAST+ command-line tools.Votes: 0GitHub stars: 6
- Sequence Similarity--> --- name: bio-sequence-similarity description: Find homologous sequences using iterative BLAST (PSI-BLAST), profile HMMs (HMMER), and reciprocal best hit analysis. Use when identifying orthologs, distant homologs, or protein family members where standard BLAST is not sensitive enough. tool_type: mixed primary_tool: BLAST+ measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- Advanced methods for find...Votes: 0GitHub stars: 6
- Sra Data--> --- name: bio-sra-data description: Download sequencing data from NCBI SRA using the SRA toolkit. Use when downloading FASTQ files from SRA accessions, prefetching large datasets, or validating SRA downloads. tool_type: cli primary_tool: sra-tools measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- Download raw sequencing data from the Sequence Read Archive using the SRA toolkit.Votes: 0GitHub stars: 6
- Uniprot Access--> --- name: bio-uniprot-access description: Access UniProt protein database for sequences, annotations, and functional information. Use when retrieving protein data, GO terms, domain annotations, or protein-protein interactions. tool_type: python primary_tool: requests measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- Query UniProt for protein sequences, functional annotations, and cross-references.Votes: 0GitHub stars: 6
- Knowledge Synthesis--> --- name: knowledge-synthesis description: Combines search results from multiple sources into coherent, deduplicated answers with source attribution. Handles confidence scoring based on freshness and authority, and summarizes large result sets effectively. keywords: - synthesis - deduplication - summarization - answers - reporting measurable_outcome: Produces a single coherent answer from >5 diverse sources with clear attribution and <10% duplication. allowed-tools: - read_file - run_shel...Votes: 0GitHub stars: 6
- Search Strategy--> --- name: search-strategy description: Query decomposition and multi-source search orchestration. Breaks natural language questions into targeted searches per source, translates queries into source-specific syntax, ranks results by relevance, and handles ambiguity and fallback strategies. keywords: - search - query-decomposition - ranking - multi-source - strategy measurable_outcome: Successfully decomposes 100% of complex queries into source-specific sub-queries targeting relevant databa...Votes: 0GitHub stars: 6
- Source Management--> --- name: source-management description: Manages connected MCP sources for enterprise search. Detects available sources, guides users to connect new ones, handles source priority ordering, and manages rate limiting awareness. keywords: - sources - mcp - connections - priority - rate-limiting measurable_outcome: Accurately detects connected MCP tools and routes queries to appropriate sources based on query intent. allowed-tools: - read_file - run_shell_command --- > If you see unfamiliar p...Votes: 0GitHub stars: 6
- Biomni--> --- name: biomni-general-agent description: Use the local Biomni checkout to orchestrate its 150+ biomedical tools, databases, and know-how workflows for complex research questions. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- KRAGEN--> --- name: kragen-knowledge-graph description: Graph-RAG Solver keywords: - knowledge-graph - RAG - reasoning - graph-of-thoughts - biomedical-qa measurable_outcome: Return a reasoning path and an answer supported by ≥3 knowledge graph nodes for complex biomedical questions with <5s latency. license: MIT metadata: author: Bioinformatics Oxford version: "1.0.0" compatibility: - system: Python 3.9+ allowed-tools: - run_shell_command - web_fetch --- A knowledge graph-enhanced Retrieval-Augmen...Votes: 0GitHub stars: 6
- LangSmith Observability--> --- name: 'langsmith-observability-2026' description: 'End-to-end tracing, evaluation, and incident response for agent workflows using LangSmith + OpenTelemetry.' keywords: - observability - langsmith - tracing - open-telemetry - evals measurable_outcome: 100% of mission-critical agents emit traces + evals with <5 min MTTR for regressions. allowed-tools: - python - read_file - run_shell_command --- LangSmith unifies debugging, testing, deployment, monitoring, and evaluation for LLM+agent ...Votes: 0GitHub stars: 6
- LEADS--> --- name: leads-literature-mining description: Review Automator keywords: - literature-mining - systematic-review - meta-analysis - pubmed - evidence-synthesis measurable_outcome: Complete a systematic review screen of 100+ papers with >90% inclusion/exclusion accuracy compared to human baseline. license: CC-BY-4.0 metadata: author: Nature Communications 2025 version: "1.0.0" compatibility: - system: Python 3.9+ allowed-tools: - run_shell_command - web_fetch --- A specialized LLM agent fo...Votes: 0GitHub stars: 6
- NanoBanana--> --- name: nano-banana description: AI-powered reasoning image engine for generating and editing high-quality biomedical infographics and realistic images. license: Proprietary (Google) metadata: author: Google version: "Pro" compatibility: - system: Web Interface / API allowed-tools: - web_fetch measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. --- Nano Banana is a cutting-edge AI tool serving as a "reasoning image engine." It is particularly pow...Votes: 0GitHub stars: 6
- PaperBanana--> --- name: paper-banana description: Agentic framework for automating the generation of publication-ready academic illustrations and statistical plots. license: CC-BY-SA-4.0 metadata: author: Peking University & Google Cloud AI Research version: "1.0.0" compatibility: - system: Python 3.9+ allowed-tools: - run_shell_command - read_file measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. --- PaperBanana is an advanced agentic framework designed to au...Votes: 0GitHub stars: 6
- Enrichment Visualization--> --- name: bio-pathway-enrichment-visualization description: 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. tool_type: r primary_tool: enrichplot measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Go Enrichment--> --- name: bio-pathway-go-enrichment description: Gene Ontology over-representation analysis using clusterProfiler enrichGO. Use when identifying biological functions enriched in a gene list from differential expression or other analyses. Supports all three ontologies (BP, MF, CC), multiple ID types, and customizable statistical thresholds. tool_type: r primary_tool: clusterProfiler measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: ...Votes: 0GitHub stars: 6
- Gsea--> --- name: bio-pathway-gsea description: Gene Set Enrichment Analysis using clusterProfiler gseGO and gseKEGG. Use when analyzing ranked gene lists to find coordinated expression changes in gene sets without arbitrary significance cutoffs. Detects subtle but coordinated expression changes. tool_type: r primary_tool: clusterProfiler measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Kegg Pathways--> --- name: bio-pathway-kegg-pathways description: KEGG pathway and module enrichment analysis using clusterProfiler enrichKEGG and enrichMKEGG. Use when identifying metabolic and signaling pathways over-represented in a gene list. Supports 4000+ organisms via KEGG online database. tool_type: r primary_tool: clusterProfiler measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Reactome Pathways--> --- name: bio-pathway-reactome description: Reactome pathway enrichment using ReactomePA package. Use when analyzing gene lists against Reactome's curated peer-reviewed pathway database. Performs over-representation analysis and GSEA with visualization and pathway hierarchy exploration. tool_type: r primary_tool: ReactomePA measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Wikipathways--> --- name: bio-pathway-wikipathways description: WikiPathways enrichment using clusterProfiler and rWikiPathways. Use when analyzing gene lists against community-curated open-source pathways. Performs over-representation analysis and GSEA for 30+ species. tool_type: r primary_tool: clusterProfiler measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Automated Qc Reports--> --- name: bio-reporting-automated-qc-reports description: Generates standardized quality control reports by aggregating metrics from FastQC, alignment, and other tools using MultiQC. Use when summarizing QC metrics across samples, creating shareable quality reports, or building automated QC pipelines. tool_type: cli primary_tool: multiqc measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Figure Export--> --- name: bio-reporting-figure-export description: Exports publication-ready figures in various formats with proper resolution, sizing, and typography. Use when preparing figures for journal submission, creating vector graphics for presentations, or ensuring consistent figure styling across analyses. tool_type: mixed primary_tool: matplotlib measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Jupyter Reports--> --- name: bio-reporting-jupyter-reports description: Creates reproducible Jupyter notebooks for bioinformatics analysis with parameterization using papermill. Use when generating automated analysis reports, running notebook-based pipelines, or creating shareable computational notebooks. tool_type: python primary_tool: papermill measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Quarto Reports--> --- name: bio-reporting-quarto-reports description: Build reproducible scientific documents, presentations, and websites with Quarto supporting R, Python, Julia, and Observable JS. Use when creating reproducible reports with Quarto. tool_type: mixed primary_tool: Quarto measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Rmarkdown Reports--> --- name: bio-reporting-rmarkdown-reports description: Create reproducible bioinformatics analysis reports with R Markdown including code, results, and visualizations in HTML, PDF, or Word format. Use when generating analysis reports with RMarkdown. tool_type: r primary_tool: rmarkdown measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command ---Votes: 0GitHub stars: 6
- Alignment Filtering--> --- name: bio-alignment-filtering description: Filter alignments by flags, mapping quality, and regions using samtools view and pysam. Use when extracting specific reads, removing low-quality alignments, or subsetting to target regions. tool_type: cli primary_tool: samtools measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- Filter alignments by flags, quality, and regions using samtools and pysam.Votes: 0GitHub stars: 6
- Alignment Indexing--> --- name: bio-alignment-indexing description: Create and use BAI/CSI indices for BAM/CRAM files using samtools and pysam. Use when enabling random access to alignment files or fetching specific genomic regions. tool_type: cli primary_tool: samtools measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- Create indices for random access to alignment files using samtools and pysam.Votes: 0GitHub stars: 6
- Alignment Sorting--> --- name: bio-alignment-sorting description: Sort alignment files by coordinate or read name using samtools and pysam. Use when preparing BAM files for indexing, variant calling, or paired-end analysis. tool_type: cli primary_tool: samtools measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- Sort alignment files by coordinate or read name using samtools and pysam.Votes: 0GitHub stars: 6
- Alignment Validation--> --- name: bio-alignment-validation description: Validate alignment quality with insert size distribution, proper pairing rates, GC bias, strand balance, and other post-alignment metrics. Use when verifying alignment data quality before variant calling or quantification. tool_type: mixed primary_tool: samtools measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- Post-alignment quality control to veri...Votes: 0GitHub stars: 6
- Bam Statistics--> --- name: bio-alignment-files-bam-statistics description: Generate alignment statistics using samtools flagstat, stats, depth, and coverage. Use when assessing alignment quality, calculating coverage, or generating QC reports. tool_type: cli primary_tool: samtools measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- Generate alignment statistics using samtools and pysam.Votes: 0GitHub stars: 6
- Duplicate Handling--> --- name: bio-duplicate-handling description: Mark and remove PCR/optical duplicates using samtools fixmate and markdup. Use when preparing alignments for variant calling or when duplicate reads would bias analysis. tool_type: cli primary_tool: samtools measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- Mark and remove PCR/optical duplicates using samtools.Votes: 0GitHub stars: 6
- Pileup Generation--> --- name: bio-pileup-generation description: Generate pileup data for variant calling using samtools mpileup and pysam. Use when preparing data for variant calling, analyzing per-position read data, or calculating allele frequencies. tool_type: cli primary_tool: samtools measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- Generate pileup data for variant calling and position-level analysis.Votes: 0GitHub stars: 6
- Reference Operations--> --- name: bio-reference-operations description: Generate consensus sequences and manage reference files using samtools. Use when creating consensus from alignments, indexing references, or creating sequence dictionaries. tool_type: cli primary_tool: samtools measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools: - read_file - run_shell_command --- Generate consensus sequences and manage reference files using samtools.Votes: 0GitHub stars: 6