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
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/usage-analytics-collector/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How usage-analytics-collector Compares
| Feature / Agent | usage-analytics-collector | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/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 signalsRelated Skills
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