testdriver:caching

Cache TestDriver test results using hash-based keys and perceptual screenshot hashing.

238|34|Updated Aug 25, 2024
One-click install
npx skills add https://github.com/testdriverai/testdriverai --skill testdriver-caching
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: testdriver:caching
Source: https://github.com/testdriverai/testdriverai/tree/main/ai/skills/testdriver%3Acaching
Command: npx skills add https://github.com/testdriverai/testdriverai --skill testdriver-caching

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Caches reduce redundant AI vision analysis by reusing prior results during TestDriver test runs, dramatically cutting execution time and resource usage.

Core Features & Use Cases

  • Automatic caching for test steps and AI vision prompts with zero configuration.
  • Cache keys derived from test file hash, prompt, screenshot perceptual hash, and platform to ensure correct invalidation across changes.
  • Use case: long-running Vitest test suites with repeated visual verifications can leverage cache to skip repeated AI analysis.

Quick Start

Run your Vitest suite to automatically leverage cached results across runs.

Frequently Asked Questions about testdriver:caching

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I speed up Vitest test suites with repeated AI vision analysis?

Caching AI vision analysis results in TestDriver reduces redundant processing by reusing prior outputs for repeated visual checks, cutting Vitest execution time and resource usage by up to 1.7x.

How does perceptual screenshot hashing work for cache invalidation?

Perceptual screenshot hashing generates cache keys from the test file hash, prompt, screenshot data, and platform, ensuring accurate cache hits while invalidating stale entries when visual inputs change.

Can I use cached test results across multiple runs with dynamic inputs?

Yes, cached test results can be served across multiple runs even with dynamic inputs, applying automatic hash-based cache keys to ensure correct invalidation when underlying test data changes.

Does TestDriver caching require manual configuration to cache AI vision prompts?

No, TestDriver caching applies automatic caching for test steps and AI vision prompts with zero configuration, immediately reducing redundant analysis workload when you run your Vitest suite.

What are the limitations of using cache thresholds for AI vision checks?

Cache thresholds require careful configuration to balance accuracy and performance, as overly aggressive caching may serve stale results if perceptual hashes do not detect significant visual changes.