Agent skill · data analytics · jeremylongshore
hex-performance-tuning
Optimize Hex API performance with caching, batching, and connection
Why this skill is useful
Provides specific caching, batching, and polling strategies for optimizing Hex API performance that the AI wouldn't reliably generate on its own.
What it needs
About 2k tokens when loaded. Last updated 2026-08-07. 2,604 stars on the source repository.
What this skill does
Hex Performance Tuning Latency Benchmarks Operation Typical Duration ----------- ----------------- ListProjects 200-500ms RunProject (trigger) 500ms-2s Project execution 10s-30min (depends on queries) GetRunStatus (poll) 100-300ms Instructions Cache Project Lists Parallel Independent Runs Optimize Poll Interval Overview Tune run latency and throughput using safe sandbox projects and aggregate metrics. A gain is invalid if it expands data scope, compromises output correctness, exceeds quota, or makes rollback impossible. Prerequisites Baseline latency/run metrics, safe fixture revision, approved error budget, and a rollback revision for cache, concurrency, parameters, and retry policy. Output Return a tuning receipt with baseline/canary percentile bands, cache/concurrency/parameter revisions, quota/error outcomes, aggregate assertion, owner approval, and rollback reference. Use aggregates only. Error Handling Roll back for quota saturation, increased errors, changed output assertion, access drift, or duplicate runs. Do not raise concurrency or cache duration to hide a failing dependency. Examples env=sandbox; p95=420ms->310ms; concurrency=2; cache=r4; quota=within-budget; assertions=pass; rollback=perf-r3 documents a safe canary. Resources Hex API
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills jeremylongshore/hex-performance-tuning