Rigorous A/B test statistical analysis. Use when analyzing experiment results, calculating statistical significance, checking for sample ratio mismatch, or validating test design before launch.
日本語の概要は準備中です。原文の説明を表示しています。
Build structured semantic layer documentation for metrics, dimensions, and entities. Activate when you need to define a business metric, document a data model, or create YAML definitions compatible with dbt Semantic Layer or similar frameworks.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
references/metric_definition_framework.md for metrics and references/dimension_hierarchy_patterns.md for dimensions.scripts/metric_template_generator.py to scaffold the initial YAML structure for the object type. Fill in the generated template.scripts/model_yaml_validator.py to check required fields, type constraints, and reference integrity (referenced dimensions exist in the same file).references/dbt_semantic_layer_guide.md for the exact field names and constraints for your dbt version.assets/metric_definition.yaml, dimensions to assets/dimension_definition.yaml, entities to assets/entity_definition.yaml.assets/metric_definition.yaml — filled metric YAML definition(s)assets/dimension_definition.yaml — filled dimension YAML definition(s)assets/entity_definition.yaml — filled entity YAML definition(s)scripts/model_yaml_validator.py (inline output)まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Rigorous A/B test statistical analysis. Use when analyzing experiment results, calculating statistical significance, checking for sample ratio mismatch, or validating test design before launch.
日本語の概要は準備中です。原文の説明を表示しています。
Track and document analytical assumptions and decisions. Use when making analytical choices, documenting trade-offs, ensuring transparency, or creating audit trails for analytical work.
日本語の概要は準備中です。原文の説明を表示しています。
Structured, reproducible analysis documentation. Use when documenting analysis findings, creating analysis notebooks, ensuring reproducibility, or building analysis archives for future reference.
日本語の概要は準備中です。原文の説明を表示しています。
Structure analysis approach before starting work. Use when receiving new analysis requests, breaking down complex questions into steps, or planning iterative analysis workflows.
日本語の概要は準備中です。原文の説明を表示しています。
Pre-delivery quality assurance for analysis work. Use when reviewing analysis before sharing with stakeholders, checking for completeness, validating assumptions, or ensuring clarity of recommendations.
日本語の概要は準備中です。原文の説明を表示しています。
Post-analysis learning and process improvement. Use when completing major analysis projects, documenting lessons learned, or improving team analytical practices.
日本語の概要は準備中です。原文の説明を表示しています。