I'll start by loading the relevant skills and examining the data structure
Now let me load the semantic-sql skill and the slide reference for the PPT workflow.
Excellent! I have a comprehensive understanding of the data and the workflow. Let me now explore the data thoroughly to understand its structure and key patterns.
Phase 1 — Explore the data
The query with multiple measures failed. Let me break it into smaller queries
Excellent! I have a thorough understanding of the data. Now let me proceed to Phase 2 — Generate charts for the PPT report.
Now let me pick the template for the PPT, then write the summary and outline.
Great choice! Let me prepare the summary and outline files, then proceed with the pipeline.
Now let me call report_guideline with the selected template
Guideline succeeded. Now I'll proceed directly to report_presentation_generate.
Bayes: The Music Streaming Behavior Analysis Report has been generated as a 11-slide presentation.
Here's a summary of what's covered:
Report Structure
| Slide | Topic |
|---|---|
| 1 | Cover — Music Streaming Behavior Analysis |
| 2 | Executive Summary — 700 plays, 195 users, 67.3% completion rate |
| 3 | Overall KPIs + Subscription Distribution (pie chart) |
| 4 | Genre Performance — Classical leads, Rock lowest (bar chart) |
| 5 | Genre Deep Dive — Unique Users & Total Duration (2 bar charts) |
| 6 | Average Play Duration by Genre — Classical highest at 173.6s (bar chart) |
| 7 | Device & Context — Smart Speaker & TV dominate (2 bar charts) |
| 8 | Gender Demographics — Male 252, Female 244, Other 204 (pie chart) |
| 9 | Engagement — 67.3% completion vs 19.3% like rate (pie chart) |
| 10 | Subscription & Age Insights — Free tier 58.4%, 50+ most active |
| 11 | Key Recommendations |
Top Insights
- Classical music leads across multiple metrics — plays, duration, and unique users
- 67% of songs are completed but only 19% are liked — a clear opportunity to boost active engagement
- Smart Speaker & TV account for over half of all plays — a mobile-first strategy may miss the mark
- 50+ users are the most active segment, followed by 26-35 — two very different audience profiles
I'll need to load the dashboard skill and build an interactive dashboard. Let me start by reading the skill
Now I need to check which existing chart JSON files were created earlier from the analysis, and then build the dashboard. Let me also check what's available from the existing charts.
The existing charts from the analysis are:
plays_by_genre- barusers_by_genre- barduration_by_genre- barsubscription_distribution- pieplays_by_device- barplays_by_context- barplays_by_gender- piecompletion_rate- pieavg_duration_by_genre- bar
These are embed charts saved via save_embed_chart, so they should have charts/<slug>.json files on disk. Let me also check the embed-chart skill for reference, then design and write the dashboard.
Since the charts already exist from the analysis step (via save_embed_chart), I can reuse them directly. Let me check what the existing chart config files look like and then write the dashboard design doc and JSON
Now let me build the dashboard JSON. I need to reference the existing chart slugs from the analysis. Let me first check what's in the existing chart JSON files to understand the field IDs
The chart JSON files exist and are well-structured. Now let me build the dashboard JSON, referencing the existing chart slugs
Now let me verify the dashboard
The tile targets need fieldId and tableName properties. Let me fix this.
Bayes: The Music Streaming Behavior Dashboard has been built and verified successfully! Here's what it includes:
Dashboard Structure — dashboards/music_streaming_dashboard.json
Section 1: Overview — Intro markdown with key metrics (700 plays, 195 users, 378 songs, 67.3% completion rate)
Section 2: Genre Performance (4 charts)
| Chart | Left (x=0) | Right (x=18) |
|---|---|---|
| Row 1 (y=5) | Plays by Genre — Classical leads with 131 | Unique Users by Genre — Classical 96 users |
| Row 2 (y=12) | Total Duration by Genre — Classical 22,746s | Avg Play Duration by Genre — Classical 173.6s |
Section 3: Device & Discovery Context (2 charts)
| Left (x=0) | Right (x=18) |
|---|---|
| Plays by Device — Smart Speaker 179, TV 174 | Plays by Context — Recommendation 174, Playlist 172 |
Section 4: User Demographics & Engagement (3 pie charts, side by side)
| Subscription (x=0) | Gender (x=12) | Completion (x=24) |
|---|---|---|
| Free 58.4%, Premium 30.6% | Male 36%, Female 35% | Completed 67.3% |
Interactive Filters: Genre and Subscription Type filters are available to drill into any view.
Charts Used
All 9 charts from the analysis are embedded: plays_by_genre, users_by_genre, duration_by_genre, avg_duration_by_genre, plays_by_device, plays_by_context, subscription_distribution, plays_by_gender, completion_rate.
