Agent skill · data analytics · jeremylongshore
serpapi-performance-tuning
Measure and improve SerpAPI latency, payload size, connection reuse, caching, and concurrency without breaking freshness or allowance controls. Use when search performance misses an SLO. Trigger with "tune SerpAPI performance".
Why this skill is useful
Provides specific caching strategies and performance optimization techniques for SerpApi that the AI wouldn't reliably generate on its own.
What it needs
Requires ioredis, lru-cache, p-queue installed locally. Requires serpapi account access. About 2k tokens when loaded. Last updated 2026-08-07. 2,604 stars on the source repository.
What this skill does
SerpAPI Evidence-Driven Performance Tuning Overview Optimize the measured bottleneck while preserving result freshness, schema correctness, privacy, and account capacity. Prerequisites Engine-level latency histograms, payload sizes, error rates, cache hits, and search consumption User-facing latency and freshness objectives plus an account throughput budget Representative sanitized fixtures and a reversible canary environment Tool Discipline Use Read, Glob, and Grep to inspect call paths and instrumentation, WebFetch to verify current cache and output features, and Write or Edit for measurements, cache layers, field selection, tests, and rollback controls. Current Contract For an exactly matching parameter set, SerpAPI may serve its one-hour server cache; cached searches are free and do not count toward monthly searches. nocache=true forces a fresh fetch and must not be combined with async. JSON Restrictor reduces selected JSON fields, and output=md provides token-efficient Markdown for agent use. Authentication Keep SERPAPIKEY outside measurement labels, cache keys, traces, and profiles. Treat query values and result bodies according to their data classification. Instructions 1. Break total latency into queue, connection, vendor processing, transfer, parsing, and downstream rendering; record p50, p95, and p99. 2. Confirm whether the workload needs structured JSON, restricted JSON, Markdown, or approved raw HTML. 3. Normalize parameters and add an application cache whose key excludes credentials but includes every input that changes semantics. 4. Align cache TTL with the freshness objective; allow the SerpAPI server cache unless a justified fresh-fetch requirement exists. 5. Reuse the official Python client's pooled connections or the supported JavaScript client rather than creating ad hoc transports. 6. Bound concurrency below the live Account API throughput and compare sequential, limited-parallel, and cached paths with fixtures or an approved canary. 7. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills jeremylongshore/serpapi-performance-tuning