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claude-codeproductivity

Claude-skill-registry klingai-usage-analytics

install
source · Clone the upstream repo
git clone https://github.com/majiayu000/claude-skill-registry
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/klingai-usage-analytics" ~/.claude/skills/majiayu000-claude-skill-registry-klingai-usage-analytics && rm -rf "$T"
manifest: skills/data/klingai-usage-analytics/SKILL.md
tags
#analytics#reporting#data-visualization#metrics#klingai#dashboarding
source content

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:

  1. Collect Data: Capture usage events
  2. Aggregate Metrics: Calculate key metrics
  3. Generate Reports: Create usage reports
  4. Visualize Data: Build dashboards
  5. 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