Why use content hashes instead of file paths for caching?

Content hashes allow the cache to persist even if files are renamed or moved. It also ensures the cache is automatically invalidated if the content changes, preventing stale data.

How does the system handle cache corruption?

The pattern is designed for graceful degradation; it treats corrupted or invalid JSON cache files as cache misses, triggering a re-process instead of crashing the application.

Does this pattern work efficiently with large files?

Yes, the implementation uses chunked reading to compute SHA-256 hashes without loading the entire file into memory, making it suitable for large PDFs, images, or datasets.

Can I add this to my existing code without refactoring?

Yes. This skill uses a service-layer wrapper approach, allowing you to wrap existing pure functions with caching logic without modifying the original function's code.

Content-Hash Cache Pattern

Name: Content-Hash Cache Pattern
Author: flatrick

byflatrick

0•

Developer Tools

Optimizes file processing performance by caching results based on SHA-256 content hashes rather than file paths.

This skill implements a robust caching mechanism for computationally expensive file-based operations like PDF parsing, text extraction, and image analysis. By using SHA-256 hashes of file contents as cache keys, the system ensures that moving or renaming files doesn't trigger unnecessary re-processing while automatically invalidating the cache the moment content changes. It promotes clean architecture through a service-layer wrapper that keeps your core processing functions pure and independent of caching logic.

Key Features

01Service-layer separation for clean, SRP-compliant architecture

020 GitHub stars

03O(1) lookups using hash-named JSON storage without index files

04Memory-efficient chunked hashing for large file support

05Path-independent caching using SHA-256 content fingerprints

06Automatic cache invalidation upon file content changes

Use Cases

01Optimizing CLI tools with --cache flags for repeated local runs

02Reducing API costs and latency in AI-driven text or image analysis

03Building efficient PDF and document parsing pipelines for AI agents

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add flatrick/mdt content-hash-cache-pattern

For use in Claude.ai and ChatGPT

Key Features

01Service-layer separation for clean, SRP-compliant architecture

020 GitHub stars

03O(1) lookups using hash-named JSON storage without index files

04Memory-efficient chunked hashing for large file support

05Path-independent caching using SHA-256 content fingerprints

06Automatic cache invalidation upon file content changes

Use Cases

01Optimizing CLI tools with --cache flags for repeated local runs

02Reducing API costs and latency in AI-driven text or image analysis

03Building efficient PDF and document parsing pipelines for AI agents

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add flatrick/mdt content-hash-cache-pattern

For use in Claude.ai and ChatGPT