ecommerce
93
amazon-shipping-calculator
Calculate Amazon shipping and fulfillment costs for FBA and FBM. Dimensional weight, storage fees, removal fees, and long-term storage cost estimation.
nexscope-ai
business
запрос активен
Поиск skills
Найдите подходящую возможность для вашего агента.
Популярные запросы
Результаты
53,183
skills, соответствующие запросу
Страница
997
из 2660
Запрос
ai
ищите по названию, тегу или описанию
payment
93
invoice-organizer
Organize, categorize, track, and manage invoices systematically with automated extraction of invoice data, payment tracking, and financial organization. Use when processing invoice uploads, extracting invoice details (date, amount, vendor), categorizing expenses, tracking payment status, organizing receipts, generating financial reports, or building accounting and bookkeeping systems.
korallis
business
payment
93
messari-x402
Access Messari's full API via x402 pay-per-request — no API key needed. Asset data, market metrics, signals, news, fundraising, token unlocks, on-chain networks, and AI chat, all paid with USDC on Base.
moonpay
business
real-estate-legal
93
amazon-suspension-appeal
Account suspension prevention and appeal — policy violations, Plan of Action writing, reinstatement process
nexscope-ai
business
design
93
diagram
专业图表生成技能：根据需求自动选择合适的图表类型，生成符合设计规范的 PNG 图表。 覆盖 29 种图表：结构图（流程图、泳道图、时序图、架构图、状态图、ER图、类图、思维导图、甘特图、Kanban、Git Graph 等） 和统计图（柱状图、折线图、饼图、雷达图、热力图、散点图、桑基图、漏斗图、瀑布图、矩形树图、柱线混合图等）。 统一工具：HTML/SVG + 内联 JS 布局计算。ER/类图使用 ELKjs 布局引擎。 所有图表遵循统一的设计规范（配色/字体/组件/间距），风格现代简洁。 支持三种输出：PNG（默认）、HTML（富文档嵌入）、DSL（Mermaid 文本，嵌入 MD 文档）。 触发词：画图、画一个、生成图表、流程图、架构图、时序图、柱状图、对比图、关系图。 即使用户没有说"画图"，只要需求中涉及可视化展示（流程、架构、数据对比、关系），都应触发此技能。 被 deep-research 等其他技能调用时，同样遵循本规范生成图表。
312362115
content-media
data-analysis
93
statistical-significance-annotation
Guide for annotating statistical significance (p-value asterisk notation) on comparison plots. Covers standard notation conventions (ns, *, **, ***, ****), when to annotate, matplotlib bracket+asterisk implementation, and integration with seaborn box/violin/bar plots. Use when generating publication-ready comparison figures that need significance markers to support statistical claims made in the analysis.
jaechang-hits
data-ai
data-analysis
93
shap-model-explainability
Model interpretability using SHAP (SHapley Additive exPlanations) based on Shapley values from game theory. Covers explainer selection (Tree, Deep, Linear, Kernel, Gradient, Permutation), computing feature attributions, and visualization (waterfall, beeswarm, bar, scatter, force, heatmap). Use when explaining ML model predictions, computing feature importance, debugging model behavior, analyzing fairness/bias, or comparing models. Works with tree-based, deep learning, linear, and black-box models.
jaechang-hits
data-ai
data-analysis
93
matplotlib-scientific-plotting
Low-level Python plotting library for full customization of scientific figures. Use for publication-quality plots (line, scatter, bar, heatmap, contour, 3D), multi-panel subplot layouts, and fine-grained control over every visual element. Export to PNG/PDF/SVG. For quick statistical plots use seaborn; for interactive plots use plotly.
jaechang-hits
data-ai
data-analysis
93
nan-safe-correlation
Per-feature NaN-safe Spearman/Pearson correlation computation. Use when computing correlations across many features (genes, proteins, variants) with missing values. Covers why bulk matrix shortcuts fail with missing data, correct pairwise deletion, degenerate input filtering, and performance optimization for large datasets. For general statistical test selection use statistical-analysis; for model explainability use shap-model-explainability.
jaechang-hits
data-ai
data-analysis
93
plotly-interactive-plots
Interactive scientific visualization with Plotly. Two-layer API: plotly.express (px) for one-liner DataFrame plots and plotly.graph_objects (go) for full trace-level control. 40+ chart types with hover, zoom, pan, and animation. Exports to interactive HTML or static PNG/SVG/PDF via kaleido. Use for interactive web figures, volcano plots with gene hover info, dose-response dashboards, gene expression heatmaps, and 3D molecular visualizations. Use seaborn for statistical summaries with automatic aggregation; use matplotlib for fine-grained publication figures; use plotly for interactive or web-embedded output.
jaechang-hits
data-ai
data-analysis
93
plotly-interactive-visualization
Interactive visualization with Plotly. 40+ chart types (scatter, line, bar, heatmap, 3D, statistical, geographic) with hover, zoom, and pan. Use for exploratory analysis, dashboards, and presentations. Two APIs: Plotly Express (quick, DataFrame-oriented) and Graph Objects (fine-grained control). For static publication figures use matplotlib; for statistical grammar use seaborn.
jaechang-hits
data-ai
data-analysis
93
hypothesis-generation
Structured hypothesis formulation from observations. Use when you have experimental observations or data and need to formulate testable hypotheses with predictions, propose mechanisms, and design experiments to test them. Follows scientific method framework. For open-ended ideation use scientific-brainstorming; for automated LLM-driven hypothesis testing on datasets use hypogenic.
jaechang-hits
data-ai
data-analysis
93
seaborn-statistical-plots
Statistical visualization library built on matplotlib with native pandas DataFrame support. Automatic aggregation, confidence intervals, and grouping for distribution plots (histplot, kdeplot), categorical comparisons (boxplot, violinplot, stripplot), relational plots (scatterplot, lineplot), regression plots (regplot, lmplot), matrix plots (heatmap, clustermap), and multi-variable grids (pairplot, jointplot, FacetGrid). Use seaborn for statistical summaries with minimal code; use matplotlib for fine-grained figure control; use plotly for interactive HTML output.
jaechang-hits
data-ai
data-analysis
93
gwas-database
NHGRI-EBI GWAS Catalog REST API for SNP-trait associations from published genome-wide association studies. Query studies, associations, variants, traits, genes, and summary statistics. Build polygenic risk score candidates, analyze variant pleiotropy, download summary statistics for Manhattan plots. No authentication required.
jaechang-hits
data-ai
framework-internals
93
torch-geometric-graph-neural-networks
PyTorch Geometric (PyG) for graph neural networks. Node classification, graph classification, link prediction with GCN, GAT, GraphSAGE, GIN layers. Message passing framework, mini-batch processing, heterogeneous graphs, neighbor sampling for large-scale learning, model explainability. Supports molecular property prediction (QM9, MoleculeNet), social networks, knowledge graphs, 3D point clouds. For non-graph deep learning use PyTorch directly; for traditional graph algorithms use NetworkX.
jaechang-hits
development
framework-internals
93
pymoo
pymoo is a Python framework for single- and multi-objective optimization using evolutionary algorithms. Define problems as vectorized objective functions and constraints, then solve with NSGA-II, NSGA-III, MOEA/D, genetic algorithms, or differential evolution. Analyze Pareto fronts, visualize trade-off surfaces, and customize operators and callbacks. Ideal for engineering design, hyperparameter search, process optimization, and any problem with multiple conflicting objectives. Alternatives: scipy.optimize (single-objective, gradient-based), platypus (fewer algorithms), jMetalPy (Java-based, more algorithms).
jaechang-hits
development
scripting
93
snakemake-workflow-engine
Python-based workflow management system for reproducible, scalable pipelines. Define rules with file-based dependencies; Snakemake automatically determines the execution order and parallelism. Supports local, SLURM, LSF, AWS, and Google Cloud execution via profiles; per-rule conda/Singularity environments. Use for bioinformatics NGS pipelines, ML training workflows, and any multi-step file-processing analysis. Use Nextflow instead for Groovy-based dataflow pipelines or when nf-core ecosystem integration is required.
jaechang-hits
development
philosophy-ethics
93
gap
Gap surfacing before decisions. Raises procedural, consideration, assumption, and alternative gaps as questions when gaps go unnoticed, producing an audited decision. Type: (GapUnnoticed, AI, SURFACE, Decision) → AuditedDecision. Alias: Syneidesis(συνείδησις).
jongwony
lifestyle
philosophy-ethics
93
frame
Multi-perspective investigation. Recommends analytical lenses or assembles a team to analyze from selected viewpoints when the right framework is absent, producing a framed inquiry. Type: (FrameworkAbsent, AI, SELECT, Inquiry) → FramedInquiry. Alias: Prothesis(πρόθεσις).
jongwony
lifestyle
astronomy-physics
93
astropy-astronomy
Core Python library for astronomy and astrophysics. Units & quantities with dimensional analysis, celestial coordinate transformations (ICRS/Galactic/AltAz/FK5), FITS file handling, table operations (FITS/HDF5/VOTable/CSV), cosmological calculations (Planck18, distance/age/volume), precise time handling (UTC/TAI/TT/TDB, Julian dates, barycentric corrections), WCS pixel-world mapping, model fitting, image visualization. For general data tables use pandas/polars; for radio astronomy interferometry use CASA.
jaechang-hits
research