klingai-usage-analyticsClaude Skill
Build usage analytics and reporting for Kling AI.
| name | klingai-usage-analytics |
| description | Build usage analytics and reporting for Kling AI. Use when tracking generation patterns, analyzing costs, or creating dashboards. Trigger with phrases like 'klingai analytics', 'kling ai usage report', 'klingai metrics', 'video generation stats'. |
| allowed-tools | Read, Write, Edit, Grep |
| version | 1.0.0 |
| license | MIT |
| author | Jeremy Longshore <jeremy@intentsolutions.io> |
Klingai Usage Analytics
Overview
This skill shows how to build comprehensive usage analytics including generation metrics, cost analysis, trend reporting, and visualization dashboards for Kling AI.
Prerequisites
- Kling AI API key configured
- Usage data collection in place
- Python 3.8+ with pandas/matplotlib (optional)
Instructions
Follow these steps for analytics:
- Collect Data: Capture usage events
- Aggregate Metrics: Calculate key metrics
- Generate Reports: Create usage reports
- Visualize Data: Build dashboards
- Set Up Alerts: Anomaly detection
Output
Successful execution produces:
- Usage summary statistics
- Daily breakdown reports
- Top user analysis
- Anomaly detection alerts
- Exportable CSV data
Error Handling
See {baseDir}/references/errors.md for comprehensive error handling.
Examples
See {baseDir}/references/examples.md for detailed examples.
Resources
Similar Claude Skills & Agent Workflows
google-analytics
Analyze Google Analytics data, review website performance metrics, identify traffic patterns, and suggest data-driven improvements.
docetl
Build and run LLM-powered data processing pipelines with DocETL.
pdf-extractor
Extract text, tables, and form data from PDF documents for analysis and processing.
schema-exploration
For discovering and understanding database structure, tables, columns, and relationships
query-writing
For writing and executing SQL queries - from simple single-table queries to complex multi-table JOINs and aggregations
whodb
Database operations including querying, schema exploration, and data analysis.