usage-analytics-collector

Privacy-respecting SDK usage analytics collection

509 stars

Best use case

usage-analytics-collector is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Privacy-respecting SDK usage analytics collection

Teams using usage-analytics-collector should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/usage-analytics-collector/SKILL.md --create-dirs "https://raw.githubusercontent.com/a5c-ai/babysitter/main/library/specializations/sdk-platform-development/skills/usage-analytics-collector/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/usage-analytics-collector/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How usage-analytics-collector Compares

Feature / Agentusage-analytics-collectorStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Privacy-respecting SDK usage analytics collection

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Usage Analytics Collector Skill

## Overview

This skill implements privacy-respecting SDK usage analytics that help understand feature adoption, usage patterns, and developer experience while maintaining user trust.

## Capabilities

- Track SDK feature usage patterns
- Implement configurable opt-in/opt-out mechanisms
- Anonymize collected data appropriately
- Generate usage dashboards and reports
- Support event batching and offline collection
- Implement differential privacy techniques
- Configure data retention policies
- Support multiple analytics backends

## Target Processes

- Telemetry and Analytics Integration
- Developer Portal Implementation
- Developer Experience Optimization

## Integration Points

- Segment for event routing
- Amplitude for product analytics
- Mixpanel for user analytics
- Custom analytics backends
- Data warehouses

## Input Requirements

- Events to track
- Privacy requirements
- Opt-in/opt-out mechanisms
- Anonymization rules
- Retention policies

## Output Artifacts

- Analytics collection module
- Opt-in/opt-out UI components
- Event schemas
- Anonymization utilities
- Dashboard configurations
- Privacy documentation

## Usage Example

```yaml
skill:
  name: usage-analytics-collector
  context:
    consentModel: opt-in
    events:
      - sdkInitialized
      - apiCallMade
      - errorOccurred
      - featureUsed
    anonymization:
      ipAddresses: hash
      userIds: pseudonymize
    batching:
      enabled: true
      maxBatchSize: 100
      flushInterval: 60s
    retention: 90d
    backend: segment
```

## Best Practices

1. Default to opt-out for sensitive data
2. Clearly document what is collected
3. Anonymize all personal identifiers
4. Implement data minimization
5. Provide easy opt-out mechanisms
6. Respect Do Not Track signals

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