Where is the cache data stored?

Each cache entry is stored as an individual JSON file named after its hash (e.g., {hash}.json) in a dedicated cache directory, enabling O(1) lookups without a central index.

Why use content hashes instead of file paths for caching?

Content hashes allow cache hits even if files are renamed or moved, and they ensure the cache invalidates automatically if the file content changes, preventing stale data.

How does this pattern handle large files?

The pattern employs chunked reading (typically 64KB chunks) to compute SHA-256 hashes, ensuring high performance without loading entire large files into memory.

Does this require modifying my existing processing logic?

No, the pattern uses a service layer wrapper approach that keeps your core processing functions pure and unaware of the caching mechanism.

Content-Hash Cache Pattern

Name: Content-Hash Cache Pattern
Author: flatrick

byflatrick

0•

개발자 도구

Implements high-performance, content-based caching for expensive file processing tasks using SHA-256 hashing.

This skill provides a robust pattern for caching results of computationally expensive file operations like PDF parsing, OCR, and image analysis. By using SHA-256 hashes of file contents as cache keys rather than file paths, it ensures that moved or renamed files still result in cache hits while any content modification triggers automatic invalidation. It emphasizes clean architecture through service layer separation and O(1) file-based lookups, making it ideal for CLI tools and batch processing pipelines where performance, reliability, and pure function maintenance are critical.

주요 기능

01SHA-256 content-based hashing for path-independent cache hits

02Automatic cache invalidation upon file content changes

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

04Service layer separation to maintain pure processing functions

05Graceful corruption handling with automatic re-processing on cache misses

060 GitHub stars

사용 사례

01Building CLI tools that require robust --cache and --no-cache functionality

02Developing PDF or image processing pipelines with high computational overhead

03Optimizing batch data extraction where identical files appear across different directories

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

주요 기능

01SHA-256 content-based hashing for path-independent cache hits

02Automatic cache invalidation upon file content changes

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

04Service layer separation to maintain pure processing functions

05Graceful corruption handling with automatic re-processing on cache misses

060 GitHub stars

사용 사례

01Building CLI tools that require robust --cache and --no-cache functionality

02Developing PDF or image processing pipelines with high computational overhead

03Optimizing batch data extraction where identical files appear across different directories

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