Agent Skills: AppFolio Cost Tuning

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UncategorizedID: jeremylongshore/claude-code-plugins-plus-skills/appfolio-cost-tuning

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plugins/saas-packs/appfolio-pack/skills/appfolio-cost-tuning/SKILL.md

Skill Metadata

Name
appfolio-cost-tuning
Description
'Optimize AppFolio API costs through efficient usage patterns.

AppFolio Cost Tuning

Overview

AppFolio Stack API pricing is partner-agreement based, with costs scaling by API call volume per managed property. Property management portfolios generate high-frequency reads for tenant lookups, lease status checks, and maintenance requests. Each redundant API call erodes margin on per-unit revenue. Optimizing call patterns directly impacts operational profitability, especially for portfolios managing hundreds or thousands of units where even small per-call costs compound rapidly.

Cost Breakdown

| Component | Cost Driver | Optimization | |-----------|------------|--------------| | Property/unit reads | Per-call pricing on tenant and unit endpoints | Cache with 10-15 min TTL; property data changes infrequently | | Lease operations | Bulk lease queries across entire portfolio | Fetch all leases once, filter locally instead of per-unit calls | | Maintenance requests | Polling for new work orders | Use webhooks to receive push notifications | | Reporting exports | Large payload downloads for financial reports | Schedule off-peak, cache results for 24h | | Vendor/owner lookups | Repeated lookups for the same contacts | Build a local lookup table, refresh daily |

API Call Reduction

class AppFolioCache {
  private cache = new Map<string, { data: any; expiry: number }>();

  get(key: string): any | null {
    const entry = this.cache.get(key);
    if (!entry || Date.now() > entry.expiry) return null;
    return entry.data;
  }

  set(key: string, data: any, ttlMs = 600_000): void {
    this.cache.set(key, { data, expiry: Date.now() + ttlMs });
  }

  async fetchWithCache(endpoint: string, ttlMs?: number): Promise<any> {
    const cached = this.get(endpoint);
    if (cached) return cached;
    const response = await fetch(endpoint);
    const data = await response.json();
    this.set(endpoint, data, ttlMs);
    return data;
  }
}

Usage Monitoring

class AppFolioUsageMonitor {
  private calls: Array<{ endpoint: string; timestamp: number }> = [];
  private budgetLimit = 10_000; // daily call budget

  record(endpoint: string): void {
    this.calls.push({ endpoint, timestamp: Date.now() });
    const todayCalls = this.getTodayCount();
    if (todayCalls > this.budgetLimit * 0.8) {
      console.warn(`AppFolio API budget 80% consumed: ${todayCalls}/${this.budgetLimit}`);
    }
  }

  getTodayCount(): number {
    const startOfDay = new Date().setHours(0, 0, 0, 0);
    return this.calls.filter(c => c.timestamp > startOfDay).length;
  }
}

Cost Optimization Checklist

  • [ ] Cache property and unit data with 10-15 min TTL
  • [ ] Replace polling loops with webhook-driven event handling
  • [ ] Batch lease queries — fetch all, filter locally
  • [ ] Use incremental sync with modified_since parameter
  • [ ] Schedule report exports during off-peak hours
  • [ ] Build local lookup tables for vendors and owners
  • [ ] Set daily API call budget alerts at 80% threshold
  • [ ] Audit unused integrations consuming API quota

Error Handling

| Issue | Cause | Fix | |-------|-------|-----| | 429 Too Many Requests | Exceeded rate limit | Implement exponential backoff with jitter | | Stale cache serving old data | TTL too long for volatile data | Reduce TTL for maintenance/lease endpoints to 2-5 min | | Budget alerts firing daily | Polling loop running on short interval | Switch to webhook-driven architecture | | Duplicate API calls | Multiple services fetching same data | Centralize through shared cache layer | | Large payload timeouts | Fetching full portfolio in single call | Paginate requests, process in batches of 100 |

Resources

Next Steps

See appfolio-performance-tuning.