Why use content hashing instead of file paths for caching?

File paths are unreliable as they change when files are moved or renamed. Content hashing ensures the cache remains valid based on the actual data, providing a more robust hit rate and automatic invalidation if the file is edited.

Can this pattern handle large files?

Yes, the implementation uses chunked reading (64KB blocks) to compute SHA-256 hashes, ensuring that even multi-gigabyte files can be hashed without causing memory overflow errors.

Will I need to rewrite my existing processing functions?

No. This skill advocates for a service-layer wrapper pattern, meaning your original functions stay 'pure' and focus only on processing, while the wrapper handles the cache checking and writing logic separately.

How does the O(1) lookup work?

Each cached result is stored in a file named after its hash (e.g., {hash}.json). This allows the system to check for the existence of a specific cache entry directly via the filesystem without needing to scan a large index file.

Content-Hash File Caching Pattern

Name: Content-Hash File Caching Pattern
Author: oabdelmaksoud

byoabdelmaksoud

0•

개발자 도구

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

This skill implements a robust caching mechanism for AI agents and developers handling computationally expensive file tasks like PDF parsing, OCR, and image analysis. By using SHA-256 hashes of file contents rather than file paths as keys, it ensures that moved or renamed files still hit the cache while any modification to the content automatically triggers a re-process. The pattern promotes clean architecture through a service-layer wrapper that separates caching logic from core processing functions, significantly reducing latency and API costs for repetitive document processing tasks.

주요 기능

01High-performance O(1) lookups via hash-based file storage

02Memory-efficient chunked file reading for large document handling

03Automatic cache invalidation upon any file content change

04Service-layer abstraction to maintain pure processing functions

05SHA-256 content-based hashing for path-independent cache hits

060 GitHub stars

사용 사례

01Optimizing batch processing pipelines where identical assets appear across different runs

02Reducing costs and time for recurring PDF text extraction and OCR tasks

03Building CLI tools with persistent caching options for local file analysis

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add oabdelmaksoud/agention content-hash-cache-pattern

For use in Claude.ai and ChatGPT

주요 기능

01High-performance O(1) lookups via hash-based file storage

02Memory-efficient chunked file reading for large document handling

03Automatic cache invalidation upon any file content change

04Service-layer abstraction to maintain pure processing functions

05SHA-256 content-based hashing for path-independent cache hits

060 GitHub stars

사용 사례

01Optimizing batch processing pipelines where identical assets appear across different runs

02Reducing costs and time for recurring PDF text extraction and OCR tasks

03Building CLI tools with persistent caching options for local file analysis

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add oabdelmaksoud/agention content-hash-cache-pattern

For use in Claude.ai and ChatGPT