Why Use This This skill provides specialized capabilities for jeremylongshore's codebase.
Use Cases Developing new features in the jeremylongshore repository Refactoring existing code to follow jeremylongshore standards Understanding and working with jeremylongshore's codebase structure
Install Guide 2 steps 1 2 Install inside Ananke
Click Install Skill, paste the link below, then press Install.
https://github.com/jeremylongshore/claude-code-plugins-plus-skills/tree/main/plugins/saas-packs/apollo-pack/skills/apollo-performance-tuning Skill Snapshot Auto scan of skill assets. Informational only.
Valid SKILL.md Checks against SKILL.md specification
Source & Community
Updated At Mar 11, 2026, 05:33 AM
Skill Stats
SKILL.md 61 Lines
Total Files 2
Total Size 2.2 KB
License MIT
---
name: apollo-performance-tuning
description: |
Optimize Apollo.io API performance.
Use when improving API response times, reducing latency,
or optimizing bulk operations.
Trigger with phrases like "apollo performance", "optimize apollo",
"apollo slow", "apollo latency", "speed up apollo".
allowed-tools: Read, Write, Edit, Bash(gh:*), Bash(curl:*)
version: 1.0.0
license: MIT
author: Jeremy Longshore <jeremy@intentsolutions.io>
compatible-with: claude-code, codex, openclaw
---
# Apollo Performance Tuning
## Overview
Optimize Apollo.io API performance through caching, connection pooling, request optimization, and efficient data handling.
## Prerequisites
- Valid Apollo.io API credentials
- Node.js 18+ or Python 3.10+
- Completed `apollo-install-auth` setup
## Instructions
Follow these high-level steps to implement apollo-performance-tuning:
1. Review the prerequisites and ensure your environment is configured
2. Follow the detailed implementation guide for step-by-step code examples
3. Validate your implementation against the output checklist below
For full implementation details, load: `Read(plugins/saas-packs/apollo-pack/skills/apollo-performance-tuning/references/implementation-guide.md)`
## Output
- Connection pooling configuration
- LRU cache with TTL per endpoint
- Parallel request patterns
- Query optimization techniques
- Performance monitoring setup
## Error Handling
| Issue | Resolution |
|-------|------------|
| High latency | Check network, enable caching |
| Cache misses | Tune TTL, check key generation |
| Rate limits | Reduce concurrency, add delays |
| Memory issues | Limit cache size, stream results |
## Resources
- [Node.js HTTP Agent](https://nodejs.org/api/http.html#class-httpagent)
- [LRU Cache](https://github.com/isaacs/node-lru-cache)
- [Prometheus Metrics](https://prometheus.io/docs/concepts/metric_types/)
## Next Steps
Proceed to `apollo-cost-tuning` for cost optimization.
## Examples
**Basic usage**: Apply apollo performance tuning to a standard project setup with default configuration options.
**Advanced scenario**: Customize apollo performance tuning for production environments with multiple constraints and team-specific requirements.