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Explain AQL queries and their results, and provide data insights. Use this whenever the user asks what a query does, wants to understand results, or needs to dig deeper into why a metric changed.
Mit Codex oder Claude installieren Kopieren Sie diesen Prompt, fügen Sie ihn in Codex, Claude oder einen anderen Assistant ein und lassen Sie die Skill-Seite prüfen und installieren.
Create, update, or apply a Holistics dashboard theme (library/themes/) from any input: a brand name, website, screenshot, brand guidelines, explicit colors, or a mood description. Use when the user wants to theme, brand, restyle, or change a dashboard's look and feel. Typical phrasings: build a theme, match our brand, use these colors, make it dark, make it warm/minimal/premium/editorial, glow up this dashboard. Do NOT trigger for building a dashboard, authoring block content, or adding controls.
Create or refine a Holistics custom chart (CustomChartDef in library/custom_charts/) for a chart type the built-in viz can't cover. Use when the user wants to create a custom chart, convert a Vega/Vega-Lite spec into Holistics AML, or scaffold or refine a chart template — or when a dashboard needs a chart form with no built-in equivalent (heatmap matrix, sankey, waterfall, box plot, ...). Typical phrasings: create a custom chart for X, turn this Vega-Lite spec into a Holistics chart, we need a sankey of X. Do NOT trigger for a standard built-in chart or a dynamic content block.
Create, update, or apply a Holistics dashboard theme (library/themes/) from any input: a brand name, website, screenshot, brand guidelines, explicit colors, or a mood description. Use when the user wants to theme, brand, restyle, or change a dashboard's look and feel. Typical phrasings: build a theme, match our brand, use these colors, make it dark, make it warm/minimal/premium/editorial, glow up this dashboard. Do NOT trigger for building a dashboard, authoring block content, or adding controls.
Review a past conversation between a Holistics data-analyst AI agent and a user, then produce insight report with three sections (`Summary`, `Recap`, and `Suggestions`). Use this whenever the user wants to assess, grade, debrief, or critique how the agent performed on a chat, including phrasings like " this conversation", "how did the agent do", "grade this chat", "what could the AI have done better", or "what context should I add to improve the agent", even if they don't say the word "review".
Use this whenever working in a (Holistics) AMQL project (i.e. with AML files). It guides you to set up and review the AMQL development environment and tooling so that the development can be done accurately and efficiently. Tooling includes CLI, MCP, code synchronization, etc.
Address suggestions in a past conversation's insight by performing each suggestion's actionable fix. Use when the user asks to implement, apply, address, or act on the suggestions from a conversation insight. Requires a conversation ID. Do NOT use this to generate a new insight.
Basierend auf der SOC-Berufsklassifikation
| name | analyze-data |
| description | Explain AQL queries and their results, and provide data insights. Use this whenever the user asks what a query does, wants to understand results, or needs to dig deeper into why a metric changed. |
Always use explain_result tool to syntactically/descriptively explain AQLs and their results. It can understand AQL accurately and provide accurate answers.
Run additional queries to analyze and provide diagnostic and predictive answers. For example, break down further, break down by other dimensions, compare different periods, etc. to answer questions such as "why did this number drop", "what was the main contributing factor", etc.
explain_result to understand the query, then proceed to further diagnostic/predictive analysis.execute_aql, execute_viz) to verify.