DevOps & Infra

holobiomicslab Skill

Use when when you have raw FASTQ files (from SRA or local storage) and need to produce normalized transcript quantification (quant.sf) files for a multi-sample RNA-seq cohort.

holobiomicslab Skill

Use when when you have access to source code or algorithmic documentation of a metabolite generation pipeline (such as MAGMa's job subproject) and need to understand, validate, or reconstruct the transformations that convert a parent compound into enumerated metabolite candidates.

holobiomicslab Skill

Use when a Python package has been relocated to a new repository location, reorganized to conform to new organizational standards (e.g., metabolomics-cloud conventions), or its dependencies, metadata, or CI/CD workflows have been modified.

holobiomicslab Skill

Use when initializing a chemical metadata annotation pipeline and you need to: (1) establish which identifier conversions are available across your installed converter suite (CIR, CTS, PubChem, IDSM, BridgeDb, RDKit, custom); (2) validate that each conversion route can actually be invoked;

holobiomicslab Skill

Use when you have adapted an ML pipeline (e.g., MSNovelist) to consume a non-standard fingerprint representation (Morgan 4096-bit instead of bundled SIRIUS 6 fingerprints) and need to verify that the model's input layer correctly reshapes and processes the new fingerprint format before committing.

holobiomicslab Skill

Use when you have raw TOF-MS or IM-MS data in Agilent MassHunter (.d) or UIMF format with jagged peaks and low-abundance ions that require signal enhancement, but you need to decide whether to apply smoothing, and at what strength, to avoid over-smoothing real signals or under-removing artifacts.

holobiomicslab Skill

Use when you have developed new scoring logic (e.g., average inchikey score, neighbourhood score) for an MS/MS spectral analogue search tool and need to embed these components into an existing production pipeline that uses a random forest to combine multiple features for candidate re-ranking.

holobiomicslab Skill

Use when when invoking Asari to process centroid mzML files for the first time in a PCPFM experiment, or when RT and m/z accuracy characteristics of your LC-MS instrument differ from the pipeline defaults (e.

holobiomicslab Skill

Use when you have a vendor mass spectrometry raw file (e.g., .raw format) that requires conversion to Aird format using AirdPro CLI, and you are running on macOS or Linux.

holobiomicslab Skill

Use when you have raw mass spectrometry data from an instrument not yet validated in your pipeline (e.

holobiomicslab Skill

Use when your analysis pipeline must ingest mass-spectrometry data from mixed vendor sources (e.g., Thermo RAW, Agilent .d, Waters .raw, and open mzML) without writing separate parser logic for each format.

holobiomicslab Skill

Use when you have a working R package or bioinformatics pipeline (e.g., IonFlow for ionomics analysis) and need to wrap it as a Galaxy tool so that users can invoke it through Galaxy's web interface without direct command-line access. The inputs are tabular datasets (e.

holobiomicslab Skill

Use when you have raw HPLC column metadata containing categorical fields (e.g., column manufacturer 'Waters', USP type 'L1', solvent identities 'H2O'/'MeOH'/'ACN') that must be converted into numerical representations before featurization for a machine learning pipeline.

holobiomicslab Skill

Use when you have a Docker image published to a registry (e.g., docker://stravsm/msnovelist6), need to run it on an HPC cluster with SLURM scheduling, and must allocate specific hardware resources (GPUs, RAM) per job.

holobiomicslab Skill

Use when when you have raw LC-MS data in mzML format (converted from .raw or acquired directly in that format) and need to invoke Asari for feature extraction, but the ionization mode is not explicitly specified in your experimental metadata or pipeline configuration.

holobiomicslab Skill

Use when before executing a complex bioinformatics pipeline (such as Hi-C data processing) that depends on multiple third-party tools with explicit version constraints.

holobiomicslab Skill

Use when when deploying a Java application in a Docker container and you need to adjust JVM heap memory settings (maximum and initial heap size) without modifying the container image.

holobiomicslab Skill

Use when your multi-class metabolomic peak table includes quality control samples (technical replicates) but no internal standards, and you need to compare the performance of multiple preprocessing workflows (normalization, imputation, transformation methods) to select the optimal pipeline for.

holobiomicslab Skill

Use when a Python-based metabolomics analysis package has been relocated to a new GitHub organization (e.g., metabolomics-cloud) and you need to confirm that the migration preserved package integrity, installation, and runtime correctness.

holobiomicslab Skill

Use when after executing an end-to-end structure annotation pipeline (such as BAM) on a validation dataset with known reference annotations.

holobiomicslab Skill

Use when you are preparing to run the MetaboDirect pipeline for the first time on a new machine, or you need to reproduce a published benchmark or analysis on a different OS (Windows, Linux, MacOS) and want to guarantee that all six pipeline steps (data pre-processing, diagnostics, exploration.

holobiomicslab Skill

Use when when you have peak-abundance .csv files and assigned molecular formula data from FT-ICR MS preprocessing, and you need to verify that a published pipeline's runtime claims (e.g., '<1 min for 40 samples', '~2 min for 120 samples') hold true on your own datasets or reference datasets.

holobiomicslab Skill

Use when when you need to validate that a newly published bioinformatics pipeline meets stated performance claims, or when you must characterize how execution time scales with dataset size (sample count, peak count, or formula complexity) and optional analysis features (e.

holobiomicslab Skill

Use when running an LC-MS or GC-MS preprocessing and statistics pipeline on a Galaxy Workflow4Metabolomics instance, or when a collaborator must re-execute the analysis without installing the toolchain — the stage order is fixed by the wrappers' own datatypes, not by convention.

diegosouzapw Bundle

jq — JSON Querying and Transformation workflow skill. Use this skill when the user needs Expert jq usage for JSON querying, filtering, transformation, and pipeline integration. Practical patterns for real shell workflows and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

diegosouzapw Bundle

jq — JSON Querying and Transformation workflow skill. Use this skill when the user needs Expert jq usage for JSON querying, filtering, transformation, and pipeline integration. Practical patterns for real shell workflows and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

diegosouzapw Bundle

AI SDR Skill workflow skill. Use this skill when the user needs When the user wants to deploy AI sales development reps, automate sales qualification, build signal-to-action routing, or design AI agent architecture for sales. Also use when the user mentions 'AI SDR,' 'AI sales agent,' 'automated qualification,' 'signal routing,' 'sales automation,' '11x,' 'Artisan,' 'AiSDR,' 'AI BDR,' or 'autonomous sales.' This skill covers AI SDR deployment, qualification automation, and agent architecture for sales development. Do NOT use for technical implementation, code review, or software architecture and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

holobiomicslab Skill

Use when you have a published computational pipeline with deposited code and validation data, and you need to verify that the pipeline can be executed end-to-end to reproduce reported validation metrics (annotation accuracy, coverage, or equivalent performance benchmarks).

holobiomicslab Skill

Use when you have executed multiple database search pipelines (Dereplicator, VarQuest, and/or Dereplicator+) on centroided LC-MS/MS spectra (in MGF, mzXML, mzML, or mzData format) against a chemical structure database of known natural products, and you need to: (1) identify which pipeline(s).

holobiomicslab Skill

Use when you have raw Hi-C FASTQ files from a high-throughput chromatin conformation capture experiment and need to generate a normalized contact matrix (.hic file) for downstream genomic analysis.

holobiomicslab Skill

Use when you have a bioinformatics pipeline (like HiC-Pro) with mixed Python, R, and compiled tool dependencies, and you need to ensure consistent reproducibility across machines and team members without manual per-tool installation. Use this when dependencies include version-pinned libraries (e.

holobiomicslab Skill

Use when when you need to reproduce a computational workflow described in a GitHub repository, validate CI/CD pipeline definitions (e.g., GitHub Actions workflows), inspect source code structure, or execute local versions of automated tests.

holobiomicslab Skill

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.

holobiomicslab Skill

Use when when you have a multi-platform Qt5 C++ project (Windows, macOS, Linux) that requires automated compilation and executable packaging across different operating systems.

holobiomicslab Skill

Use when when integrating edited Modular.r scripts into the LipidMatch-4.2 distribution and you need to switch between Modular mode (standalone R execution with manual or CSV inputs) and Flow mode (integrated pipeline execution).

holobiomicslab Skill

Use when you have completed differential expression analysis (DEA) on genes, miRNA, proteins, or lipids and need to identify significantly enriched biological pathways. The multiOmicsIntegrator pipeline requires explicit tool selection via the pea_genes parameter in params.