data-analysis
101
occupancy-calculator
IBC occupancy load calculator — calculates maximum occupant loads per area from IBC Table 1004.5, with gross vs net area handling, use group classification, and exportable reports.
AlpacaLabsLLC
data-ai
sorting
stars
current ordering strategy
query
all entries
refine the visible subset
data-analysis
101
zoning-envelope
Generate interactive 3D zoning envelope viewers from zoning analysis reports. Requires a zoning analysis report as input.
AlpacaLabsLLC
data-ai
data-analysis
100
excel-parser
Smart Excel/CSV file parsing with intelligent routing based on file complexity analysis. Analyzes file structure (merged cells, row count, table layout) using lightweight metadata scanning, then recommends optimal processing strategy - either high-speed Pandas mode for standard tables or semantic HTML mode for complex reports. Use when processing Excel/CSV files with unknown or varying structure where optimization between speed and accuracy is needed.
Harryoung
data-ai
data-analysis
99
slm-build-graph
Build or rebuild the knowledge graph from existing memories using TF-IDF entity extraction and Leiden clustering. Use when search results seem poor, after bulk imports, or to optimize performance. Automatically discovers relationships between memories and creates topic clusters.
qualixar
data-ai
data-analysis
99
slm-recall
Search and retrieve memories using semantic similarity, knowledge graph relationships, and full-text search. Use when the user asks to recall information, search memories, find past decisions, or query stored knowledge. Returns ranked results with relevance scores.
qualixar
data-ai
data-analysis
98
tidyverse-patterns
Modern tidyverse patterns for R including pipes, joins, grouping, purrr, and stringr. Use when writing tidyverse R code.
ab604
data-ai
data-analysis
98
r-style-guide
R style guide covering naming conventions, spacing, layout, and function design best practices. Use when writing R code.
ab604
data-ai
data-analysis
98
stock-data-assistant
统一的股票数据助手 Skill，整合： (1) 数据查询 — 通过 MCP 协议查询历史 K 线、财务报表等（A 股/港股/ETF/指数）； (2) 实时搜索 — 通过 WebSocket 订阅实时行情推送（每 3~5 秒更新）； (3) 微信联动 — 通过 picoclaw + WeChat Channel 实现微信端操作数据库和订阅实时数据。 触发此 Skill 时会自动下载 picoclaw、复用项目 LLM 配置、启动微信登录。
Yourdaylight
data-ai
data-analysis
97
result-integrator
Integrate multiple plot point analysis results into comprehensive reports, generating high-quality analysis through deduplication, classification, sorting, and summarization. Suitable for integrating multiple analysis sources, generating unified reports
GongLingRui
data-ai
data-analysis
97
score-analyzer
Analyze multi-round evaluation result scoring data, calculate various metrics, calculate rating grades. Suitable for analyzing scoring trends, calculating S/A/B ratings
GongLingRui
data-ai
data-analysis
97
result-integrator
整合多情点分析结果为综合报告，通过去重、分类、排序、总结生成高质量分析。适用于整合多分析源、生成统一报告
GongLingRui
data-ai
data-analysis
94
find-relevant-case
Search for existing cases related to specific indicators or entities. Use to find correlation with other investigations before starting new analysis. Takes search terms and returns matching case IDs.
dandye
data-ai
data-analysis
94
generate-report
Save investigation findings to a markdown report file. Use after completing triage, enrichment, or investigation to create a permanent record. Generates timestamped files in ./reports/ directory.
dandye
data-ai
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
statistical-analysis
Guided statistical analysis: test selection, assumption checking, effect sizes, power analysis, and APA reporting. Use when choosing appropriate tests for your data, verifying assumptions, calculating effect sizes, or formatting results for publication. Covers frequentist (t-test, ANOVA, chi-square, regression, correlation, survival, count models, agreement/reliability) and Bayesian alternatives. For implementing specific models use statsmodels or pymc-bayesian-modeling.
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
degenerate-input-filtering
Mandatory filtering of degenerate and uninformative data points before statistical tests. Covers single-sequence alignments, empty files, constant-value features, zero-variance inputs, and all-NaN columns. For NaN-aware correlation computation, see the nan-safe-correlation skill. For broader statistical testing guidance, see the statistical-analysis skill.
jaechang-hits
data-ai