# posthog-cost-tuning

> Optimize PostHog costs through event sampling data retention policies and efficient querying

## Directory Structure

```
posthog-cost-tuning/
├── SKILL.md
└── examples/
    ├── sampling_strategy.md
    ├── retention_config.json
    ├── cost_analysis.py
    └── optimization_playbook.md
```

## File Descriptions

| File | Type | Purpose |
|------|------|---------|
| SKILL.md | Markdown | Core skill instructions for PostHog cost optimization |
| sampling_strategy.md | Markdown | Event sampling strategies without losing key insights |
| retention_config.json | JSON | Data retention policy configurations |
| cost_analysis.py | Python | Script to analyze PostHog usage and costs |
| optimization_playbook.md | Markdown | Step-by-step cost reduction playbook |

## Summary

**Category:** Enterprise
**Target Audience:** Platform engineers optimizing PostHog costs and efficiency
**Trigger Phrases:** "posthog cost optimization", "reduce posthog costs", "posthog billing", "posthog event sampling", "posthog data retention", "optimize posthog spend"

---

**Author:** Jeremy Longshore <jeremy@intentsolutions.io>
**License:** MIT
**Version:** 1.0.0
