K-Dense

Plan and review PufferLib reinforcement learning workflows, where agents learn through rewards. Covers version-specific environment checks, parallel execution, training and evaluation plans, plus checkpoint inspection before loading saved models.

• Choose APIs for a specific PufferLib version
• Check environment behavior before training
• Create training and evaluation plans with separate seeds

Combine laboratory animal welfare measurements into reference-relative RELSA severity scores. Analyze individual trajectories, explore forecasts for specified observation times, and derive candidate score zones, with explicit checks on normalization, reference selection, prediction intervals, and evaluation limits.

• Combine animal welfare measurements into daily scores
• Compare group severity using a shared reference
• Explore severity forecasts at specified observation times

Process mass spectrometry data using scripts for format conversion, signal cleanup, peak detection, and quantification across samples. Prepare protein and metabolite analyses with identification filtering, candidate annotations, data tables, and plots.

• Inspect, convert, and preprocess mass spectrometry files
• Build quantitative tables across multiple samples
• Find metabolite candidates from accurate mass

Prepare constructive review drafts for scientific manuscripts, protocols, preprints, and proposals. Organize checks of claims, evidence, methods, statistics, reproducibility, ethics, figures, and citations into specific comments that a responsible human reviewer can verify and revise.

• Draft evidence-based comments on a scientific manuscript
• Check methods, statistics, and reproducibility reporting
• Choose reporting guidelines and identify missing information

Read, analyze, modify, and visualize molecular structures with RDKit in Python. Calculate molecular properties, search for similar structures or specific structural patterns, apply reaction rules, and generate 2D or 3D coordinates with detailed control over processing.

• Calculating properties for a collection of molecules
• Searching for molecules with similar structures
• Filtering molecules by specific structural patterns

Look up biomedical relationships in ARAX using explicit entity types and tightly bounded paths. Inspect direct links or paths through one intermediate entity, along with returned publications and source records, to identify candidates for further research.

• Checking recorded drug–gene relationships
• Exploring paths between a drug and a disease
• Inspecting publications and original data sources

Prepare and launch nf-core/pacsomatic workflows for matched tumor and normal PacBio HiFi samples. Generate sample sheets and launch files from unaligned BAM inputs, run local checks, submit cluster launchers, and troubleshoot startup failures.

• Prepare sample sheets for matched tumor and normal samples
• Review generated launch files with a dry run
• Submit a Nextflow launcher to a computing cluster

Plan and write literature reviews using multiple scholarly databases. Document searches, screen papers, synthesize findings, and check citations, then prepare Markdown or PDF reports with transparent selection counts, evidence limitations, and reproducible search records.

• Prepare a literature review for a thesis or research paper
• Record reproducible searches across scholarly databases
• Track screening decisions and exclusion reasons

Process calibrated one-dimensional NMR signals into spectra, candidate peaks, and signed integration results. Supports manual phase adjustment, baseline correction, and recorded processing settings so results can be reviewed and reproduced.

• Convert raw one-dimensional NMR signals into spectra
• Check peak positions against reference signals
• Review phase and baseline corrections

Prepare experiments for Ginkgo Cloud Lab by choosing a protocol, organizing required inputs, checking configured pricing, and navigating browser ordering. Covers protein expression, RNA synthesis, stability assays, and setup of measurement methods.

• Choosing a protein expression and purification protocol
• Preparing inputs for mRNA or circRNA synthesis
• Reviewing stability assays and measurement method setup

Convert PDF, Office, and other documents into Markdown that preserves useful text structure. Use batch conversion and literature organization to prepare files for search, text analysis, or AI systems that retrieve information from documents.

• Convert PDF and Office files to Markdown
• Batch-convert a document folder
• Organize research papers with source metadata

Helps build and review NeuroKit2 research workflows for physiological recordings such as ECG, respiration, and skin conductance. Covers preprocessing, time alignment, event analysis, heart rate variability, and complexity measures, while recording methods and checking data quality.

• Inspect physiological recordings before preprocessing
• Analyze ECG and heart rate variability for research
• Plan event windows and baseline correction

Work with geographic points, lines, and areas in Python using GeoPandas. Guidance and local audit tools help check coordinate systems, geometry validity, spatial join matches, and export settings before trusting or sharing analysis results.

• Checking geographic data before analysis
• Reviewing coordinate systems and transformations
• Auditing matches between points and areas

Finds papers, preprints, citation links, and openly available full text through 18 scholarly APIs. Selects databases for the task and returns relevant records with search parameters, identifiers, and access dates so the retrieval can be repeated.

• Find papers and preprints on a research topic
• Look up a paper by DOI, PMID, or arXiv ID
• Find openly available full text or PDFs

Organize ISO evidence for medical devices and laboratories, including controlled documents, risk records, corrective actions, and supplier controls. Produce structured gap reports for authorized human review while keeping certification, accreditation, and regulatory processes distinct.

• Organize controlled documents and implementation records
• Check links in medical-device risk and design records
• Review corrective-action and supplier-control evidence

Turn observations or preliminary findings into testable research plans. The skill separates candidate hypotheses from evidence, develops competing explanations and distinguishing predictions, and helps specify measurements and analysis plans for preregistration, a research plan recorded before testing.

• Turn an observation into testable research hypotheses
• Compare competing explanations and distinguishing predictions
• Define measurements and review an analysis plan

Turn small-molecule structures into numerical features for similarity searches and models that predict activity or properties. Using Molfeat, the skill covers representation choices, invalid inputs, alignment with experimental labels, and saving feature-generation settings for reuse.

• Prepare molecular features for activity or property prediction
• Choose molecular representations for similarity searches
• Keep experimental labels aligned after rejecting invalid molecules

Clean and compare tandem mass spectra, measurements used to study molecular fragments, with matchms. Standardize metadata, filter peaks, search reference libraries, and export ranked candidate matches with similarity scores and matched-peak counts.

• Clean MS/MS spectra and standardize metadata
• Search reference libraries for compound candidates
• Compare spectra using similarity scores and matched peaks

Helps build LabArchives connections for electronic lab notebooks and laboratory inventory. Guides endpoint selection, request signing for authentication, and user authorization, with local tools to inspect container files and prepare redacted request plans before remote operations.

• Plan an electronic lab notebook API connection
• Check authentication for laboratory inventory requests
• Inspect an LA container file locally

Analyze pooled CRISPR screens from FASTQ reads or guide-count tables using MAGeCK. Validate inputs, assess library and replicate quality, and rank enriched or depleted genes with effect sizes and false discovery rates, which estimate false-positive proportions.

• Counting guide reads from FASTQ files
• Checking library representation and replicate consistency
• Comparing treatment and control screens

Build and review numerical workflows for MATLAB or GNU Octave, including arrays, tables, graphics, tests, and MAT files. Helps plan release migrations, reproducible projects, and Python integration while checking runtime, compatibility, and license requirements.

• Reviewing array operations and numerical tolerances
• Planning MATLAB release migrations and compatibility checks
• Preparing reproducible projects and unit test scaffolds

Turn supplied data or optional research into infographic drafts for reports, presentations, or social posts. Choose layouts and visual styles, generate PNG images, and use automated reviews to guide revisions while retaining review logs.

• Turning report statistics into an infographic
• Creating a timeline of project milestones
• Comparing product features visually

Helps organize biological datasets and models in LaminDB. Covers data registration, table validation, annotation with standardized biological terms, metadata searches, and tracking analysis inputs and outputs so researchers can preserve the context needed to repeat their work.

• Register and organize biological datasets
• Validate DataFrame or AnnData metadata
• Standardize annotations with biological vocabularies

Build, analyze, and visualize relationship data in Python with NetworkX. Find shortest routes, identify important nodes and groups, generate networks for simulations, and exchange graph data through tables and common file formats.

• Finding important people and groups in social networks
• Calculating shortest routes in transportation networks
• Visualizing relationships between research papers