Perform pre-experiment calculations and generate step-by-step preparation protocols for dilutions, solution preparation, dissolution, and % concentrations when planning formulations and lab prep workflows.
Predict depletion time of critical lab reagents based on historical usage frequency, and automatically generate purchase alerts when stock falls below safety thresholds.
Track lab equipment calibration dates and send maintenance reminders for pipettes, balances, centrifuges, and other instruments. Validates date formats and supports update/delete operations.
IoT monitoring simulation to predict CO2 tank depletion and prevent weekend gas outages in cell culture facilities. Monitors cylinder pressure, calculates consumption rates, provides early warnings, and supports automated scheduling via cron.
Automatically summarize scientific podcasts like Huberman Lab and Nature.
Batch extraction of experimental methods from multiple papers for protocol.
Monitor and summarize competitor clinical trial status changes from ClinicalTrials.gov.
Use sanger chromatogram qa for data analysis workflows that need structured execution, explicit assumptions, and clear output boundaries.
Determine whether an incident in a clinical trial is a "major deviation.
Use when cleaning clinical trial data, preparing data for FDA/EMA submission, standardizing SDTM datasets, handling missing values in clinical studies, detecting outliers in lab results, or converting raw CRF data to CDISC format. Cleans and standardizes clinical trial data for regulatory compliance with audit trails.
Audit medical device technical files against EU MDR 2017/745 regulations.
Converts LabArchives notebook data, entry metadata, and authorized ELN exports into manuscript-ready academic writing outputs such as Methods sections, data-availability statements, reproducibility appendices, experiment timelines, and submission support notes. Optional bundled scripts can be used to collect or validate source notebook data before writing.
Generates a structured prompt framework for clinical study protocols. Supports Diagnostic, Efficacy, Etiology, and Prognosis studies. Calculates sample size and provides logic guides for LLMs.
Convert between IUPAC names, SMILES strings, molecular formulas, and common names for chemical compounds. Supports SMILES validation, batch processing, structure standardization, and cheminformatics database preparation for drug discovery workflows.
Generates comprehensive academic introductions for biological pathways, including signaling processes, markers, and inhibitors. Use when the user asks to introduce a pathway, molecule, or gene.
Access the Human Metabolome Database (HMDB) to search metabolites by name/structure/ID and extract chemical/biological/clinical fields when you need metabolomics research data or automated HMDB XML mining.
Search for gene expression DataSets and Profiles in the NCBI GEO database. Use this skill when the user wants to find microarray, RNA-seq, or other genomic data by keywords, organism, author, or specific fields.
Retrieves comprehensive gene information including PubMed publication counts, NCBI summaries, and Ensembl transcript data. Supports batch processing and file input. Invoke when the user asks for gene details, publication statistics, or needs to analyze a list of genes.
Use when identifying collaboration opportunities across fields, finding experts in complementary disciplines, translating methodologies between scientific domains, or building interdisciplinary research teams. Identifies synergies between scientific disciplines, matches researchers with complementary expertise, and facilitates cross-domain collaborations. Supports interdisciplinary grant applications and innovative research team formation.
Access Cellosaurus database for cell line information and release data. Invoke when user asks to search cell lines, get cell line details by accession, or check database release info.
Comprehensive tool for computational mass spectrometry using PyOpenMS; use when you need to read/write MS formats (mzML/mzXML/MGF), run signal processing (smoothing/peak picking), detect isotope features, or perform peptide identification in proteomics/metabolomics workflows.
Analyze data with `pseudotime-trajectory-viz` using a reproducible workflow, explicit validation, and structured outputs for review-ready interpretation.
