'agent-skill' 검색 결과

Build and optimize quantum circuits with PennyLane, including models that combine quantum circuits with PyTorch or JAX. Explore molecular energy estimation and optimization problems, validate values and gradients in simulation, and prepare tested circuits for provider plugins.

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• Check quantum circuit values and gradients in simulation
• Train hybrid quantum and PyTorch or JAX models
• Estimate molecular energies with VQE

Explore gene, drug, disease, and phenotype associations in a downloaded PrimeKG CSV. Retrieve direct relationships, disease summaries, and paths through one intermediate node while preserving relationship types and data provenance for reproducible research and hypothesis generation.

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• Checking associations between genes, drugs, and diseases
• Summarizing genes, drugs, and phenotypes linked to a disease
• Exploring short paths between two entities

Inspect and transform local DICOM medical imaging files, including metadata, image frames, and compression formats. Generate technical inventories and preview images, check installed codecs, and review pseudonymized derivatives without treating those checks as proof of de-identification.

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• Create a technical inventory of local DICOM files
• Check compression support and frame memory needs
• Export a frame as a non-diagnostic preview

Simulate lithium-ion battery charging, discharging, and rest with PyBaMM. Track voltage and capacity, record parameter sources, check how numerical settings affect predictions, and compare simulated curves with measured cycling data.

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• Predicting voltage changes during charge, discharge, and rest
• Comparing simulation results with measured cycling data
• Checking how numerical settings affect predictions

Use PathML for local pathology image research, from loading whole-slide images and splitting them into tiles to preprocessing and quality checks. Plan multiplex measurements, analyze spatial relationships between cells, and run model inference in bounded batches.

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• Planning tile extraction from whole-slide images
• Reviewing preprocessing and image quality
• Validating multiplex measurements and spatial graphs

Analyze biological sequences and microbial communities in Python. Process and align DNA, RNA, or proteins, build evolutionary trees, calculate diversity, visualize sample differences, test group differences, and convert common biological file formats.

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• Calculate and compare microbiome diversity
• Align DNA, RNA, or protein sequences
• Build and compare evolutionary trees

Validate particle data and run RELION refinement for single-particle cryo-electron microscopy. Check independently refined half maps, calculate diagnostic map correlations, and perform soft-mask postprocessing while preserving execution logs and restart information.

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• Check particle metadata and image-stack consistency
• Run refinement on a selected particle population
• Inspect agreement between independent half maps

Validate and convert crystal and molecular structures, compare symmetry assignments, and build phase diagrams showing relative stability from local calculation data. Preserve sources and parameters while analyzing materials data or planning limited Materials Project queries.

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• Validating crystal structures in CIF files
• Comparing symmetry assignments across tolerances
• Converting structure files and checking information loss

Use PyTDC to discover therapeutic machine-learning datasets, create task-appropriate training and test splits, and evaluate predictions against curated benchmarks. Also score selected molecules with supported scoring functions, with explicit download plans and bounded outputs.

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• Find datasets for therapeutic machine-learning tasks
• Plan and create task-appropriate data splits
• Evaluate predictions with benchmark-specific metrics

Review papers, drafts, and research ideas with evidence-linked feedback focused on improvement. Audit low-stakes assessment rubrics, trace supporting evidence, and check rater agreement and uncertainty without ranking people or recommending consequential decisions.

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• Prepare evidence-linked feedback on a paper draft
• Review strengths and limitations of a research idea
• Check assessment criteria and evidence traceability

Find biological pathways and functions enriched in gene lists or ranked gene data. Choose an appropriate statistical method, align gene identifiers, define comparison backgrounds, and turn results into interpretable tables and plots with multiple-testing corrections.

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• Finding enriched pathways among differentially expressed genes
• Running GSEA on a complete ranked gene list
• Calculating gene-set scores for individual samples or cells

Gather scholarly evidence for a scientific manuscript or research brief. Organize supporting and conflicting findings into references, study comparison tables, and claim-to-source maps, with search records and coverage reports that help identify gaps requiring further review.

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• Gather background literature for a manuscript
• Compare supporting, conflicting, and null findings
• Build study comparison tables and claim-to-source maps

Simulate quantum dynamics, steady states, and spectra with QuTiP 5. The skill guides solver selection and checks physical assumptions, units, state validity, and numerical convergence so local simulation results can be reviewed with their limitations.

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• Simulating quantum dynamics with environmental dissipation
• Choosing a solver for a quantum model
• Checking numerical convergence and state validity

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.

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

Manage Zotero reference libraries through Python: search, create, update, and delete references, organize collections and tags, upload PDF attachments, and export citation data. Guidance covers both remote libraries and access through a running local Zotero app.

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• Searching references in a Zotero library
• Organizing references with collections and tags
• Uploading PDF attachments to references

Run molecular property predictions, explore molecular shapes, and estimate how compounds bind to proteins through a cloud Python API. Process compound batches and connect modeling steps without maintaining local high-performance computing infrastructure.

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• Predicting properties across a compound library
• Exploring molecular shapes and tautomeric forms
• Estimating how compounds bind to proteins

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.

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

Retrieve, validate, and export protocols.io experimental procedures while preserving version and attribution details. Check saved JSON offline, save protocol PDFs, or prepare reviewable plans for updates and publication; bundled scripts do not execute changes.

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• Retrieve a specific version of an experimental protocol
• Validate saved protocol JSON offline
• Export a protocol as a PDF

Analyze gene-expression differences in bulk RNA-seq data using PyDESeq2. Validate count tables and experimental designs, test explicit comparisons, adjust for multiple testing, shrink effect estimates, and export statistical results with volcano and MA plots.

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• Compare gene expression between treatment and control groups
• Analyze expression differences while accounting for batch effects
• Validate count tables against sample metadata

Create and review scientific figures with Matplotlib, Seaborn, or Plotly. The skill covers panel layouts, uncertainty, missing data, accessible color choices, and exported file checks, helping prepare figures for papers, presentations, or web publication.

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• Create multi-panel figures for a paper
• Show uncertainty and missing observations clearly
• Review palette contrast and color-independent cues

Prepare and review research funding proposals for NSF, NIH, DOE, DARPA, and Taiwan NSTC. Maps application requirements to draft sections, identifies gaps, and helps refine research aims, budgets, impact statements, and responses to reviewers.

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• Map funding-call requirements to proposal sections
• Review research aims against evaluation criteria
• Align budgets and timelines with the research plan

Create an editable, single-slide PowerPoint research poster from author-approved local text and images. Check physical dimensions, image resolution, contrast, reading order, and file security, with reports to support manual review and printing.

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• Create an editable PowerPoint conference poster
• Check print dimensions and image resolution
• Review contrast, reading order, and alternative text

Build Bayesian models in PyMC to estimate effects and quantify uncertainty. Fit regression or hierarchical models, check sampling diagnostics, assess predictions against observed data, predict new groups, and compare models using predictive performance.

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• Estimate regression effects with uncertainty
• Model differences across patients or groups
• Inspect sampling diagnostics and predictive checks

Build and check clinical machine learning workflows with PyHealth, from loading electronic health records, signals, or images to training and evaluation. Includes patient-level data splits, prediction task checks, model checkpoints, and medical code mapping.

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• Prototype mortality and readmission prediction models
• Check patient splits and data leakage
• Train and evaluate sleep staging models