model-exploration
SolidUse when exploring Honeydew semantic layer, discovering entities/fields, setting up workspace and branch context, or running structured queries to spot-check field values. Any question about the data itself — "why", "how", trends, root cause, anything needing multiple steps — belongs to the query skill's deep analysis, including when already mid-exploration. For creating metrics use metric-creation skill. For creating attributes use attribute-creation skill.
Install
Quality Score: 82/100
Skill Content
Details
- Author
- honeydew-ai
- Repository
- honeydew-ai/honeydew-ai-coding-agents-plugins
- Created
- 7 months ago
- Last Updated
- 3 weeks ago
- Language
- Shell
- License
- Apache-2.0
Bundled in these plugins
Similar Skills
Semantically similar based on skill content — not just same category
query
Use when the user wants to query or analyze data through the Honeydew semantic layer — including natural language analysis questions, deep multi-step investigations, and structured queries. For model/field discovery use the model-exploration skill.
query-debugging
Use when the user wants to review or inspect past query executions in Honeydew — what ran, from which client (BI tools, SQL interface, MCP, deep analysis), the semantic definition or compiled SQL behind a run, who ran it and when — and to debug failures. Uses the list_query_history MCP tool. For running new queries or analysis use the query skill.
exploratory-data-analysis
Perform systematic exploratory data analysis to understand dataset structure, distributions, relationships, and anomalies before modeling. Use when a dataset is new, its quality is unknown, or the user requests open-ended profiling; use data-analysis instead for a defined hypothesis or decision question.