发现 documentation data analysis 相关 Skills，比较来源仓库和用途，查看适合你工作流的技能说明。
Use this skill when gathering requirements for new BigQuery data models OR when asked to edit existing queries in bqetl. For new models, guides structured requirements interviews. For existing queries, understa...
The core skill for working within the bigquery-etl repository. Use this skill when understanding project structure, conventions, and common patterns. Works with model-requirements, query-writer, metadata-manage...
Copilot agent that assists with database operations, performance tuning, backup/recovery, monitoring, and high availability configuration Trigger terms: database administration, DBA, database tuning, performan...
Copilot agent for database schema design, ER diagrams, normalization, DDL generation, and performance optimization Trigger terms: database design, schema design, ER diagram, normalization, DDL, database modeli...
Copilot agent that assists with performance analysis, bottleneck detection, optimization strategies, and benchmarking Trigger terms: performance optimization, performance tuning, profiling, benchmark, bottlene...
INVOKE for debugging and step-by-step problem solving. Produces visible reasoning trace with each step shown. Use when tracing logic, explaining reasoning, or debugging issues. Triggers: debugging, tracing exec...
INVOKE for calculations and data processing. Produces executable code instead of mental math. Use when precision matters or numbers are complex. Triggers: calculations, numerical analysis, data transformations,...
INVOKE for research tasks and multi-source understanding. Produces visible dependency graphs and contracted answers. Use during research phase of workflow. Triggers: researching topics, gathering information be...
Generates professional diagrams for educational flashcards using Python (matplotlib) or Mermaid syntax. Automatically selects the best visualization tool based on diagram type. Use when creating visual aids for...
Building and processing datasets - data quality, curation, deduplication, synthesis, annotation, formatting. Use when creating training data, improving data quality, or generating synthetic data.
AI agent creates structured implementation plans with task breakdown, dependency mapping, risk assessment, and file-level detail. Use when planning features, projects, or complex implementations.
Create beautiful infographics based on the given text content. Use this when users request creating infographics.
Common patterns and workflows for Azure DevOps and database queries. Use to avoid inefficient searches and tangents.
Analyze data files (CSV, JSON) and generate insights, summaries, and statistical analysis
Use this skill when designing database schemas for relational (SQL) or document (NoSQL) databases. Provides normalization guidelines, indexing strategies, migration patterns, and performance optimization techni...
Perform GO and KEGG functional enrichment using HOMER from genomic regions (BED/narrowPeak/broadPeak) or gene lists, and produce R-based barplot/dotplot visualizations. Use this skill when you want to perform G...
Calculates technical mapping statistics for any aligned BAM file (ChIP or ATAC). It assesses the performance of the aligner itself by generating metrics on read depth, mapping quality, error rates, and read gro...
This skill performs PCA-based A/B compartments calling on Hi-C .mcool datasets using pre-defined MCP tools from the cooler-tools, cooltools-tools, and plot-hic-tools servers.
Performs ChIP-specific biological validation. It calculates metrics unique to protein-binding assays, such as Cross-correlation (NSC/RSC) and FRiP. Use this when you have filtered the BAM file and called peaks...
This skill performs A/B compartment shift analysis between two Hi-C samples.
Data quality testing with dbt tests, Great Expectations, and monitoring.
Dimensional modeling, normalization, and schema design for analytics.
Create reactive Python notebooks for IMSA racing data analysis using marimo. Use for building interactive filtering UIs (seasons, classes, events), connecting to DuckDB databases, creating reactive visualizatio...
R 4.4+ best practices with testthat 3.2, lintr 3.2, and data analysis patterns.
默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库，同一仓库的多个技能可能共享相同数值；它反映仓库关注度，不代表单个技能的安装量或质量评分。