1999 Perplexity Caching Strategy A0f32e21

# perplexity-caching-strategy

> Implement caching strategies to reduce API calls and costs

## Directory Structure

```
perplexity-caching-strategy/
├── SKILL.md                    # Main skill definition with YAML frontmatter
└── examples/                   # Optional examples directory
    ├── cache_manager.py        # Cache management implementation
    ├── redis_cache.py          # Redis-based caching
    ├── cache_key_strategy.py   # Cache key generation
    └── cache_config.yaml       # Cache configuration options
```

## File Descriptions

| File | Type | Purpose |
|------|------|---------|
| `SKILL.md` | Markdown | Skill definition with caching patterns |
| `cache_manager.py` | Python | Cache management with TTL and invalidation |
| `redis_cache.py` | Python | Redis integration for distributed caching |
| `cache_key_strategy.py` | Python | Generate consistent cache keys |
| `cache_config.yaml` | YAML | Cache configuration and TTL settings |

## Summary

**Category:** cicd
**Target Audience:** Developer optimizing performance
**Trigger Phrases:** `perplexity cache`, `perplexity caching`, `cache perplexity`, `reduce perplexity calls`

### What This Skill Does

This skill teaches caching strategies for Perplexity:

- Query normalization for cache keys
- TTL configuration based on content freshness needs
- Cache invalidation strategies
- Distributed caching with Redis
- Cache hit rate monitoring

### Technical Success Criteria

- Significant cache hit rate achieved
- Cache keys properly normalized
- TTL appropriate for content freshness

### Business Success Criteria

- Lower operational costs through reduced API calls
- Improved response times for cached queries
- Predictable API usage patterns

## Related Skills

- `perplexity-pricing-usage` - Cost implications of caching
- `perplexity-rate-limits` - Caching reduces rate limit pressure
- `perplexity-monitoring-alerts` - Monitor cache performance