Claude Skills by HolobiomicsLab

Use when you have a feature table from untargeted metabolomics (with m/z, retention time, and p-values from differential abundance testing) but lack or wish to bypass metabolite annotation.

Use when ingesting or validating project JSON documents against a schema (such as app/public/schema.json in the Pairing Omics Data Platform) that designates certain fields as URL type (e.

Use when when compiling or maintaining a catalog of web-accessible scientific tools (e.

Use when you have a USI accession (e.g., 'mzspec:MSV000082283:f07074:scan:5475' or 'mzspec:PXD000561:Adult_Frontalcortex_bRP_Elite_85_f09:scan:17555') pointing to a publicly deposited tandem mass spectrometry scan in a GNPS or ProteomeXchange repository, and you need to retrieve and instantiate.

Use when when you have a ranked list of GCF-MF (genomic cluster family–molecular feature) link predictions from one or more scoring functions, a curated set of known validated links for the same strain(s), and need to assess whether combining or filtering by percentile thresholds improves.

Use when when you have computed multiple independent scoring functions (e.

Use when when you have loaded a project JSON document from the Pairing Omics Data Platform and need to identify and document constraint violations (such as whitespace in URL fields) defined in the JSON schema.

Use when when implementing or auditing S4 replacement methods (e.

Use when when ingesting raw LC-MS/MS output from a mass spectrometry instrument and you need to prepare it for metabolite identification, fragmentation tree computation, or molecular formula annotation.

Use when you have one or more vendor mass spectrometry raw files (Thermo .raw, Agilent .d, Sciex .wiff2, or other MSConvert-supported formats) that must be converted to Aird format for batch processing, cloud deployment, or integration with downstream analysis tools.

Use when when you have modifications to propose for a shared codebase (e.g., bug fixes, new features, or documentation updates) and need to integrate them without disrupting the main development branch.

Use when you have a set of chemical compounds (with known retention times and intensities) loaded into a ViMMS IndependentMassSpectrometer and need to simulate a specific MS/MS fragmentation strategy (e.

Use when you need to create a synthetic chemical population for testing data-dependent acquisition (DDA) strategies in a simulation environment before committing to real mass spectrometry analysis.

Use when you have execution-time data for the same set of plotting operations (e.g., chromatogram, spectrum, peakmap rendering) across two or more backend implementations (e.

Use when you are composing multiple containerized services that have data dependencies—e.g., a web application that launches calculation jobs, a calculation engine that consumes a pre-built lookup database, and a data-processing service that generates that lookup.

Use when you have access to a project README or repository documentation (Zenodo deposit, GitHub, or local clone) describing multiple domain-specific web applications, and you need to produce a machine-readable inventory of those applications with verified live URLs and associated publications for.

Use when you have a user-submitted spectrum with associated domain context metadata (e.g., selected as 'microbial origin', 'plant tissue', 'food sample') and need to route that spectrum to the appropriate domain-specific MASST application for searching.

Use when when you have a parsed mass spectrum (precursor m/z, ionization mode, collision energy, and fragment peak list as m/z–intensity pairs) and need to obtain molecular fingerprint predictions, de-novo candidate structures, or chemical class annotations without maintaining local neural network.

Use when when you need to confirm that a publicly hosted academic web service (such as molDiscovery) is live and responding at a documented endpoint URL, or when troubleshooting access issues reported by end users.

Use when your annotation pipeline depends on multiple external web converters and you need to diagnose why annotation jobs are failing, slow, or incomplete. Use it if you observe missing metadata fields in output .

Use when validating project JSON documents against the platform's schema (app/public/schema.json) and you need to ensure all URL-type fields conform to URL syntax rules. Specifically, use it when the schema designates certain fields as URL type (e.

Use when use this skill after building a Docker image that installs Wine and .NET Framework 4.8 on a Ubuntu 22.04 base, but before running production conversion tasks or batch jobs with AirdPro.

Use when you are deploying a Windows .NET application (e.g., AirdPro CLI) inside a Docker container on a non-Windows host and need to understand whether Wine initialization completes, how long it takes (documented as >30 minutes), whether .

Use when when you have pre-processed MS/MS spectra and a pre-trained Word2Vec model, and need to compute fast, scalable similarity scores for library matching or molecular networking that correlate better with structural similarity than cosine-based methods.

Use when when comparing large numbers of MS/MS spectra against spectral libraries or in molecular networking, particularly when molecules differ by multiple structural modifications and cosine-based scores produce excessive false positives.

Use when you have a large collection of preprocessed MS/MS spectra (typically >10,000 spectra) with diverse chemical structures and you need to learn embeddings that capture fragmentation patterns and neutral loss relationships.

Use when when applying a pre-trained Word2Vec model to mass spectra at inference time (e.g., library matching or molecular networking), especially when the query spectra may contain fragment peaks or neutral losses not represented in the model's training vocabulary.

Use when converting MS/MS spectra into Spec2Vec embeddings using a pre-trained Word2Vec model that was trained on reference data (e.g., a subset of GNPS or MassBank).

Use when you need to understand how a complex MS/MS spectral search system routes query spectra through multiple parallel processing pipelines with different objectives (e.g., reliable exact matching vs. fast approximate matching).

Use when when preparing to execute the Nextflow4MS-DIAL workflow on raw LC-HRMS metabolomics data (.mzML or .

Use when you have located a workflow definition file (YAML or JSON) in a versioned release or commit and need to verify that it conforms to the schema specification for that release version (e.g., v1.0.0).

Use when after executing a Nextflow-based MS-DIAL workflow on .mzML LC-HRMS metabolomics data using Docker or Singularity container backends.

Use when you have prepared metabolomics input files (feature quantification table, MS/MS spectra in MGF format, sample metadata) and are about to execute the TIMA taxonomically informed annotation pipeline, or after pipeline execution to verify all outputs were generated correctly.

Use when when you have a partially documented or undocumented MS analysis pipeline and need to verify its correctness, trace data provenance through multiple processing stages, integrate tools via unified parameter handling (CTD scheme), or ensure the workflow adheres to community standards for.

Use when you need to verify that a GitHub Actions workflow (such as 'dev_build_release.

Use when you have raw LC-MS or GC-MS data files from a mass spectrometer (in mzML, NetCDF, or mzXML format) and need to detect chromatographic peaks, correct m/z bias via mass calibration (e.

Use when when you have raw LC-MS all-ion fragmentation (AIF) chromatograms in centroid mode and need to prepare them for metabolite annotation using fragment ion matching.

Use when you have raw LC-MS data files (mzML, netCDF, or raw vendor formats) from multiple samples and need to extract, align, and quantify chromatographic features across the cohort.

Use when you have spectrum or chromatogram data stored as XML strings (e.g., in a SQLite database indexed by spectrum ID) and need to access individual spectra by ID or iterate through them sequentially while working with a library like pymzML that expects Spectrum or Chromatogram objects.

Use when you have extracted a centroided MS/MS spectrum from a Thermo Orbitrap raw file (via rawrr::readSpectrum or equivalent) and need to verify that the observed y-ion fragments for a known peptide precursor exhibit signal-to-noise ratios consistent with high-quality fragmentation.

Use when you have a versioned workflow definition file (YAML or JSON) from a specific release commit and need to verify it conforms to the project's schema specification, validate the presence of all required metadata fields (name, version, inputs, outputs, steps), and detect syntax errors or.

Use when after feature detection has produced a feature table with zero and missing values (sparse abundance matrix) but before multivariate statistical analysis or annotation.

Use when when you need to generate 2D metabolomic NMR spectra (COSY for

Use when when you have raw GCxGC-MS data imported from NetCDF into a

Use when you have raw LC-IM-MS/MS data files from sterol lipid analysis

Use when when you have a neural network or machine learning model with

Use when when building a visualization library that must support multiple

Use when when you need to apply domain-specific filtering logic to compounds

Use when you have a tokenized sequence of domain-specific language tokens

Use when when you have a domain-specific query language (such as MassQL