← Back to list

gamma-cost-tuning
by jeremylongshore
Hundreds of Claude Code plugins with embedded AI skills. Learn via interactive Jupyter tutorials.
⭐ 1,042🍴 135📅 Jan 23, 2026
SKILL.md
name: gamma-cost-tuning description: | Optimize Gamma usage costs and manage API spending. Use when reducing API costs, implementing usage quotas, or planning for scale with budget constraints. Trigger with phrases like "gamma cost", "gamma billing", "gamma budget", "gamma expensive", "gamma pricing". allowed-tools: Read, Write, Edit version: 1.0.0 license: MIT author: Jeremy Longshore jeremy@intentsolutions.io
Gamma Cost Tuning
Overview
Optimize Gamma API usage to minimize costs while maintaining functionality.
Prerequisites
- Active Gamma subscription
- Access to usage dashboard
- Understanding of pricing tiers
Gamma Pricing Model
| Resource | Free | Pro | Team | Enterprise |
|---|---|---|---|---|
| Presentations/mo | 10 | 100 | 500 | Custom |
| AI generations | 5 | 50 | 200 | Unlimited |
| Exports/mo | 10 | 100 | 500 | Unlimited |
| API calls/min | 10 | 60 | 200 | Custom |
| Storage | 1GB | 10GB | 100GB | Custom |
Instructions
Step 1: Usage Monitoring
// Track usage per operation
interface UsageTracker {
presentations: number;
generations: number;
exports: number;
apiCalls: number;
}
const dailyUsage: UsageTracker = {
presentations: 0,
generations: 0,
exports: 0,
apiCalls: 0,
};
function trackUsage(operation: keyof UsageTracker) {
dailyUsage[operation]++;
// Check if approaching limits
const limits = { presentations: 100, generations: 50, exports: 100, apiCalls: 60 };
const percentage = (dailyUsage[operation] / limits[operation]) * 100;
if (percentage >= 80) {
console.warn(`Warning: ${operation} usage at ${percentage}%`);
alertOps(`Gamma ${operation} usage high: ${percentage}%`);
}
}
// Wrap API calls
async function createPresentation(opts: object) {
trackUsage('apiCalls');
trackUsage('presentations');
if (opts.generateAI) trackUsage('generations');
return gamma.presentations.create(opts);
}
Step 2: Implement Usage Quotas
interface UserQuota {
userId: string;
presentationsRemaining: number;
generationsRemaining: number;
exportsRemaining: number;
resetsAt: Date;
}
async function checkQuota(userId: string, operation: string): Promise<boolean> {
const quota = await getQuota(userId);
const quotaField = `${operation}Remaining` as keyof UserQuota;
if (typeof quota[quotaField] === 'number' && quota[quotaField] <= 0) {
throw new QuotaExceededError(`${operation} quota exceeded`);
}
return true;
}
async function consumeQuota(userId: string, operation: string) {
await db.quotas.update({
where: { userId },
data: { [`${operation}Remaining`]: { decrement: 1 } },
});
}
// Usage in API route
app.post('/api/presentations', async (req, res) => {
await checkQuota(req.userId, 'presentations');
const result = await gamma.presentations.create(req.body);
await consumeQuota(req.userId, 'presentations');
res.json(result);
});
Step 3: Optimize AI Generation Usage
// Expensive: Full AI generation for each request
const expensive = await gamma.presentations.create({
prompt: 'Create 20 slides about AI',
generateAI: true,
slideCount: 20, // Uses lots of AI credits
});
// Cost-effective: Template + targeted AI
const costEffective = await gamma.presentations.create({
template: 'business-pitch', // Pre-made structure
title: 'Our AI Solution',
slides: [
{ title: 'Introduction', content: predefinedContent },
{ title: 'Problem', generateAI: true }, // AI only where needed
{ title: 'Solution', generateAI: true },
{ title: 'Team', content: teamData }, // No AI needed
{ title: 'Contact', content: contactInfo },
],
});
Step 4: Caching to Reduce API Calls
import Redis from 'ioredis';
const redis = new Redis(process.env.REDIS_URL);
const CACHE_TTL = 3600; // 1 hour
async function getCachedOrFetch<T>(
key: string,
fetchFn: () => Promise<T>
): Promise<T> {
// Check cache
const cached = await redis.get(key);
if (cached) {
return JSON.parse(cached);
}
// Fetch and cache
const data = await fetchFn();
await redis.setex(key, CACHE_TTL, JSON.stringify(data));
return data;
}
// Usage - reduces repeated API calls
const presentation = await getCachedOrFetch(
`presentation:${id}`,
() => gamma.presentations.get(id)
);
Step 5: Batch Operations
// Expensive: Individual operations
for (const item of items) {
await gamma.presentations.create(item); // N API calls
}
// Cost-effective: Batch operation
await gamma.presentations.createBatch(items); // 1 API call
// Or queue for off-peak processing
await queue.addBulk(items.map(item => ({
name: 'create-presentation',
data: item,
opts: { delay: calculateOffPeakDelay() },
})));
Step 6: Cost Alerts and Budgets
// Set up budget alerts
const budget = {
monthly: 100, // $100/month
current: 0,
alertThresholds: [50, 75, 90, 100],
};
async function recordCost(operation: string, cost: number) {
budget.current += cost;
for (const threshold of budget.alertThresholds) {
const percentage = (budget.current / budget.monthly) * 100;
if (percentage >= threshold) {
await sendBudgetAlert(threshold, budget.current);
}
}
if (budget.current >= budget.monthly) {
await disableNonCriticalFeatures();
}
}
Cost Reduction Strategies
| Strategy | Savings | Implementation |
|---|---|---|
| Caching | 30-50% | Redis/in-memory cache |
| Batching | 20-40% | Batch API calls |
| Templates | 40-60% | Reduce AI usage |
| Off-peak | 10-20% | Queue for low-cost periods |
| Quotas | Variable | Per-user limits |
Resources
Next Steps
Proceed to gamma-reference-architecture for architecture patterns.
Score
Total Score
85/100
Based on repository quality metrics
✓SKILL.md
SKILL.mdファイルが含まれている
+20
✓LICENSE
ライセンスが設定されている
+10
○説明文
100文字以上の説明がある
0/10
✓人気
GitHub Stars 1000以上
+15
✓最近の活動
1ヶ月以内に更新
+10
✓フォーク
10回以上フォークされている
+5
✓Issue管理
オープンIssueが50未満
+5
✓言語
プログラミング言語が設定されている
+5
✓タグ
1つ以上のタグが設定されている
+5
Reviews
💬
Reviews coming soon

