Alchemy Cost Tuning
SkillDev toolsHelps your agent cut Alchemy API costs by budgeting compute units, setting up caching, and picking the right plan.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Alchemy Cost Tuning skill
About this capability
Govern Alchemy compute usage and spend with current account evidence, workload attribution, budgets, and reversible optimizations. Use when forecasting or reducing Alchemy cost. Trigger with "Alchemy cost", "Alchemy compute units", or "reduce Alchemy spend".
What this skill tells your AI
The instructions your AI receives, as published by jeremylongshore/tons-of-skills-marketplace in skills/.curated/alchemy-cost-tuning/SKILL.md and read by ahel’s review.
Overview
Alchemy pricing is based on Compute Units (CU). Different API methods have different CU costs. Optimize by caching, batching, choosing cheaper methods, and right-sizing your plan.
Plan Comparison
| Plan | CU/sec | Monthly CU | Price | Best For |
|---|---|---|---|---|
| Free | 330 | 300M | $0 | Dev/prototyping |
| Growth | 660 | 1.2B | $49/mo | Small dApps |
| Scale | Custom | Custom | Custom | High-traffic apps |
CU Cost Reference (Top Methods)
| Method | CU | Optimization |
|---|---|---|
eth_blockNumber | 10 | Cache 12s (1 block) |
eth_getBalance | 19 | Cache 30s |
eth_call | 26 | Cache based on use case |
getTokenBalances | 50 | Cache 60s; batch addresses |
getNftsForOwner | 50 | Cache 5 min |
getTokenMetadata | 50 | Cache 24h (rarely changes) |
getAssetTransfers | 150 | Cache aggressively; paginate |
getNftMetadataBatch | 50 | Use batch over individual calls |
Prerequisites
- An approved observation window with aggregate method counts and latency; do not record end-user wallet data merely to estimate API usage.
- Current plan and compute-unit limits confirmed in the organization’s Alchemy account, since commercial terms and method costs may change.
- A cache-invalidation policy that distinguishes safe metadata caching from time-sensitive balance, block, and transaction data.
Instructions
Step 1: CU Usage Monitor
// src/cost/cu-monitor.ts
const CU_COSTS: Record<string, number> = {
'eth_blockNumber': 10, 'eth_getBalance': 19, 'eth_call': 26,
'getTokenBalances': 50, 'getNftsForOwner': 50, 'getTokenMetadata': 50,
'getAssetTransfers': 150, 'getNftMetadataBatch': 50,
};
class CuMonitor {
private usage: Array<{ method: string; cu: number; timestamp: number }> = [];
record(method: string): void {
this.usage.push({ method, cu: CU_COSTS[method] || 26, timestamp: Date.now() });
}
getHourlyReport(): { totalCu: number; byMethod: Record<string, number> } {
const cutoff = Date.now() - 3600000;
const recent = this.usage.filter(u => u.timestamp > cutoff);
const byMethod: Record<string, number> = {};
let totalCu = 0;
for (const u of recent) {
byMethod[u.method] = (byMethod[u.method] || 0) + u.cu;
totalCu += u.cu;
}
return { totalCu, byMethod };
}
getMonthlyProjection(): { projectedMonthly: number; planRecommendation: string } {
const hourly = this.getHourlyReport();
const projectedMonthly = hourly.totalCu * 24 * 30;
let recommendation = 'Free';
if (projectedMonthly > 300_000_000) recommendation = 'Growth';
if (projectedMonthly > 1_200_000_000) recommendation = 'Scale';
return { projectedMonthly, planRecommendation: recommendation };
}
}
export { CuMonitor };
Step 2: Cost-Optimized Client Wrapper
// src/cost/optimized-client.ts
import { Alchemy, Network } from 'alchemy-sdk';
const cache = new Map<string, { data: any; expiry: number }>();
// Cache token metadata aggressively (rarely changes)
async function getTokenMetadataCached(alchemy: Alchemy, contract: string) {
const key = `metadata:${contract}`;
const cached = cache.get(key);
if (cached && cached.expiry > Date.now()) return cached.data;
const data = await alchemy.core.getTokenMetadata(contract);
cache.set(key, { data, expiry: Date.now() + 86400000 }); // 24h cache
return data;
}
// Use batch instead of individual NFT metadata calls
// 1 batch call (50 CU) vs 100 individual calls (5000 CU)
async function getNftMetadataOptimized(
alchemy: Alchemy,
tokens: Array<{ contractAddress: string; tokenId: string }>
) {
const BATCH_SIZE = 100;
const results = [];
for (let i = 0; i < tokens.length; i += BATCH_SIZE) {
const batch = tokens.slice(i, i + BATCH_SIZE);
const batchResults = await alchemy.nft.getNftMetadataBatch(batch);
results.push(...batchResults);
}
return results;
}
Step 3: Free Tier Optimization Checklist
// For staying within Free tier (330 CU/sec, 300M CU/month):
// 1. Cache eth_blockNumber (saves 10 CU per redundant call)
// 2. Cache token metadata (saves 50 CU per redundant call)
// 3. Use getNftMetadataBatch instead of getNftMetadata (100x savings)
// 4. Avoid getAssetTransfers loops (150 CU each — cache results)
// 5. Use WebSockets instead of polling (one connection vs repeated calls)
// 6. Rate-limit user-facing endpoints to prevent CU bursts
Output
- CU usage monitor with hourly reports and plan projections
- Cost-optimized client with aggressive caching
- Batch operations reducing CU consumption by 100x
- Free tier optimization checklist
Examples
Collect one hour of aggregate development traffic, feed the counts into
CuMonitor, and identify the three methods responsible for the highest CU
projection. Add a 24-hour metadata cache and batched NFT metadata requests in
the test environment, then compare request counts and response correctness
against uncached fixtures. Promote only after cache hits never serve stale
time-sensitive balance or transfer data. If observed use approaches the
account limit or the monitor’s input is incomplete, throttle the noncritical
feature and obtain an updated account-limit report rather than guessing a
budget or silently dropping user-facing requests.
Error Handling
| Failure | Response |
|---|---|
| Usage projection lacks complete observation data | Mark the estimate incomplete and collect a representative window before plan decisions. |
| Cache returns stale chain state | Invalidate the affected key and narrow its TTL or caching scope. |
| Account limit is approached | Apply bounded rate limiting and notify the account owner before service degradation. |
| Batch operation is partially rejected | Preserve successful items, retry only failed items within limits, and expose their unavailable state. |
Resources
Next Steps
For architecture design, see alchemy-reference-architecture.
Signals
- GitHub stars
- 3k
- Forks
- 396
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
alchemy-cost-tuning- Source
- github.com/jeremylongshore/tons-of-skills-marketplace