Agent skill · software engineering · jeremylongshore
exa-load-scale
Validate Exa capacity with synthetic workload models, endpoint-specific budgets, bounded queues, and stop conditions. Use when operating or reviewing this Exa boundary. Trigger with "Exa load scale", "review Exa load scale", or "fix Exa load scale".
Why this skill is useful
Adds specific k6 load testing scripts and scaling strategies for Exa integrations that the AI wouldn't reliably generate on its own.
What it needs
Requires k6, redis installed locally. Requires exa account access. About 3k tokens when loaded. Last updated 2026-08-07. 2,604 stars on the source repository.
What this skill does
Exa Load and Capacity Verification Overview Validate Exa capacity with synthetic workload models, endpoint-specific budgets, bounded queues, and stop conditions. Treat credentials, queries, retrieved content, generated output, spend, and destructive state as separately governed boundaries. Prerequisites The target repository, environment, Exa team, product surface, and accountable owner. The workload's data classification, latency and freshness promise, cost ceiling, and retention policy. Current first-party documentation plus credentials only for a narrowly approved live check. Current Contract Published QPS differs by endpoint and enterprise limits can differ by team. Search, Contents, and Answer have distinct ceilings; asynchronous Agent or Batch is not equivalent to synchronous load. Enterprise Batch is beta, must be enabled, and requires the current first-party Exa-Beta header documented for that feature. Authentication For normal REST work, inject EXAAPIKEY from an approved server-side secret manager and send it only as Authorization: Bearer to the configured first-party Exa API host. Team Management service keys, hosted MCP OAuth or enterprise managed authorization, and payment-protocol calls are separate trust models. Never print, commit, place in a URL, or expose a credential to an untrusted client. Instructions 1. Obtain vendor and service-owner approval for the environment, volume, duration, and spend. 2. Model endpoint mix, result sizes, content modes, freshness, and asynchronous work. 3. Use synthetic non-sensitive inputs and shared limiters across workers. 4. Ramp gradually with hard stop conditions for errors, latency, cost, and backlog. 5. Measure 429 separately from 503, partial crawl status, and downstream saturation. 6. Drain queues, reconcile runs or batches, and delete test artifacts after the evidence window. Tool Discipline Use Read, Glob, and Grep to inspect repository code, configuration, fixtures, and evidence. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills jeremylongshore/exa-load-scale