Will it bloat my project with large files?

The skill includes pruning guidelines and token-aware loading strategies to keep memory files concise, typically moving older data to progress summaries once files exceed 200 lines.

Does it require manual permissions to update memory files?

No, it is specifically designed to use permission-free tool operations, such as the Edit tool for updates and the Read tool for retrieval, ensuring an uninterrupted workflow.

How does it handle switching between different projects?

The skill includes an auto-reset strategy that validates the stored project path against your current working directory, automatically refreshing the context when you switch projects.

Can I manually view or edit the stored memory?

Yes, all memory is stored in human-readable Markdown files within the .claude/pseudo-code-prompting/ directory of your project.

What does the Session Memory skill do?

It creates a persistent storage layer within your project directory that allows Claude to remember transformation patterns, user preferences, and previous architectural decisions across different sessions.

Session Memory for Pseudo-Code Prompting

Name: Session Memory for Pseudo-Code Prompting
Author: EladAriel

byEladAriel

•

生产力与工作流

Maintains transformation context and learned patterns across sessions to ensure consistent and optimized pseudo-code generation.

关于

Session Memory is a specialized persistence layer designed to solve the context reset problem in AI-driven development. By maintaining a dedicated directory of active context, learned transformation patterns, and quality metrics, it allows Claude to remember user preferences, security standards, and naming conventions across multiple sessions. This skill ensures that every pseudo-code transformation builds upon previous successes, eliminating redundant corrections and accelerating the transition from natural language requirements to structured, production-ready code implementations.

主要功能

Project-aware context resets to prevent data pollution when switching repositories
Automated loading and updating of transformation context at session boundaries
Permission-free memory management using optimized tool selection strategies
2 GitHub stars
Dynamic pattern learning for REST APIs, Authentication, and Database logic
Persistent storage of user-specific naming, security, and architectural preferences

使用场景

Maintaining consistent naming conventions and verbosity levels during large-scale refactoring
Ensuring security-first code generation by persisting custom validation rules and OWASP standards
Standardizing architectural patterns across a multi-session backend migration project

关于

主要功能

Project-aware context resets to prevent data pollution when switching repositories
Automated loading and updating of transformation context at session boundaries
Permission-free memory management using optimized tool selection strategies
2 GitHub stars
Dynamic pattern learning for REST APIs, Authentication, and Database logic
Persistent storage of user-specific naming, security, and architectural preferences

使用场景

Maintaining consistent naming conventions and verbosity levels during large-scale refactoring
Ensuring security-first code generation by persisting custom validation rules and OWASP standards
Standardizing architectural patterns across a multi-session backend migration project