From fathom-pack
Optimizes Fathom meeting intelligence API performance with caching, batch processing, connection pooling, and rate-limit handling. Reduces transcript download latency and prevents 429 errors during bulk sync.
How this skill is triggered — by the user, by Claude, or both
Slash command
/fathom-pack:fathom-performance-tuningThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
Fathom's meeting intelligence API serves transcript downloads, bulk meeting sync, and action item aggregation. Transcript payloads are large (50-500KB each), making bulk sync of historical meetings a major latency bottleneck. The 60 req/min rate limit requires careful batching. Caching immutable transcripts aggressively while keeping action item data fresh reduces download latency by 70% and pr...
Fathom's meeting intelligence API serves transcript downloads, bulk meeting sync, and action item aggregation. Transcript payloads are large (50-500KB each), making bulk sync of historical meetings a major latency bottleneck. The 60 req/min rate limit requires careful batching. Caching immutable transcripts aggressively while keeping action item data fresh reduces download latency by 70% and prevents rate limit errors during bulk operations.
const cache = new Map<string, { data: any; expiry: number }>();
const TTL = { transcript: 3_600_000, actionItems: 120_000, meetings: 300_000 };
async function cached(key: string, ttlKey: keyof typeof TTL, fn: () => Promise<any>) {
const entry = cache.get(key);
if (entry && entry.expiry > Date.now()) return entry.data;
const data = await fn();
cache.set(key, { data, expiry: Date.now() + TTL[ttlKey] });
return data;
}
// Transcripts are immutable — cache 1hr. Action items change — cache 2min.
async function syncMeetingsBatch(client: any, ids: string[], batchSize = 50) {
const results = [];
for (let i = 0; i < ids.length; i += batchSize) {
const batch = ids.slice(i, i + batchSize);
const res = await Promise.all(batch.map(id => client.getTranscript(id)));
results.push(...res);
if (i + batchSize < ids.length) await new Promise(r => setTimeout(r, 61_000)); // 60 req/min
}
return results;
}
import { Agent } from 'https';
const agent = new Agent({ keepAlive: true, maxSockets: 6, maxFreeSockets: 3, timeout: 45_000 });
// Transcript downloads are large — longer timeout, fewer concurrent sockets
async function withFathomRateLimit(fn: () => Promise<any>): Promise<any> {
try { return await fn(); }
catch (err: any) {
if (err.status === 429) {
const retryAfter = parseInt(err.headers?.['retry-after'] || '60') * 1000;
await new Promise(r => setTimeout(r, retryAfter));
return fn();
}
throw err;
}
}
const metrics = { downloads: 0, cacheHits: 0, rateLimits: 0, avgLatencyMs: 0 };
function trackDownload(startMs: number, cached: boolean, rateLimited: boolean) {
metrics.downloads++;
metrics.avgLatencyMs = (metrics.avgLatencyMs * (metrics.downloads - 1) + (Date.now() - startMs)) / metrics.downloads;
if (cached) metrics.cacheHits++; if (rateLimited) metrics.rateLimits++;
}
| Issue | Cause | Fix |
|---|---|---|
| 429 Rate Limited | Exceeded 60 req/min | Parse Retry-After, batch with 61s delay between groups |
| Transcript timeout | Large payload on slow connection | Increase timeout to 45s, enable keep-alive |
| Stale action items | Cache TTL too aggressive | Reduce action item TTL to 2 min |
| Missing transcript | Meeting still processing | Check meeting status before download, retry after 30s |
| Partial sync failure | Network interruption mid-batch | Track progress, resume from last successful ID |
See fathom-reference-architecture.
2plugins reuse this skill
First indexed Jul 18, 2026
npx claudepluginhub jeremylongshore/claude-code-plugins-plus-skills --plugin fathom-packHandles Fathom API rate limits (60 req/min per user) with a token bucket limiter, retry strategy, and batch processing for meeting transcript syncs.
Optimizes Fireflies.ai GraphQL API performance with field selection, caching, and batching. Use when experiencing slow API responses or optimizing transcript processing throughput.
Guides collaborative design exploration before implementation: explores context, asks clarifying questions, proposes approaches, and writes a design doc for user approval.