Does this pattern require modifying my existing processing functions?

No, it utilizes a service layer wrapper approach. This keeps your core processing functions 'pure' and unaware of the caching logic, adhering to the Single Responsibility Principle.

Is this skill compatible with large files?

Yes, the implementation uses chunked reading (64KB chunks) to calculate hashes, allowing it to process large files efficiently without exhausting system memory.

Why use content hashing instead of file paths for caching?

Content hashing ensures the cache remains valid even if a file is renamed or moved. It also provides automatic invalidation because any change to the file content results in a new hash and a cache miss.

What happens if a cache file becomes corrupted?

The pattern is designed to handle corruption gracefully. If a JSON cache file is unreadable or invalid, the system treats it as a cache miss and re-processes the source file.

Can I easily disable the cache for specific operations?

Yes, the service layer pattern is designed to accept a boolean flag, making it trivial to implement CLI options like --no-cache for debugging or forced refreshes.

Content Hash Caching Pattern

Name: Content Hash Caching Pattern
Author: affaan-m

byaffaan-m

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130,864

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생산성 및 워크플로

Optimizes file processing performance using SHA-256 content hashing for path-independent and auto-invalidating cache management.

This skill provides a robust implementation pattern for caching expensive file operations like PDF parsing, image analysis, and text extraction. By using SHA-256 hashes of file contents rather than file paths, it ensures that moved or renamed files still result in cache hits while content changes trigger automatic invalidation. It follows the Single Responsibility Principle by decoupling caching logic from core processing functions, making it ideal for CLI tools and data processing pipelines that require high performance and reliability without increasing memory overhead.

주요 기능

01SHA-256 content-based caching for robust data integrity

02Path-independent lookup allowing files to be moved or renamed without losing cache

03Memory-efficient chunked file reading for processing large datasets

04Automatic cache invalidation immediately upon file content modification

05130,864 GitHub stars

06Service layer separation to maintain pure, side-effect-free processing functions

사용 사례

01Caching expensive PDF or OCR extraction results in document processing pipelines

02Implementing --cache/--no-cache flags for high-performance CLI utilities

03Optimizing batch processing tasks where the same files are encountered across multiple runs

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add affaan-m/everything-claude-code content-hash-cache-pattern

For use in Claude.ai and ChatGPT

주요 기능

01SHA-256 content-based caching for robust data integrity

02Path-independent lookup allowing files to be moved or renamed without losing cache

03Memory-efficient chunked file reading for processing large datasets

04Automatic cache invalidation immediately upon file content modification

05130,864 GitHub stars

06Service layer separation to maintain pure, side-effect-free processing functions

사용 사례

01Caching expensive PDF or OCR extraction results in document processing pipelines

02Implementing --cache/--no-cache flags for high-performance CLI utilities

03Optimizing batch processing tasks where the same files are encountered across multiple runs

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add affaan-m/everything-claude-code content-hash-cache-pattern

For use in Claude.ai and ChatGPT