How does this differ from standard chat history?

Unlike temporary chat history, this skill allows for the storage of specific, atomic facts that can be retrieved across different projects and sessions, ensuring Claude remembers key details long-term.

What is the best way to store information?

For optimal retrieval, store 'atomic' memories—one single fact per entry—and use descriptive, project-specific tags like 'database-schema' or 'auth-flow'.

What should I avoid storing in memory?

Avoid storing sensitive credentials, secrets, ephemeral session details, or information that is already easily accessible within your project's source code.

Can I search for memories based on when they were created?

Yes, the skill includes tools for natural language time queries, allowing you to ask for information stored 'yesterday', 'last week', or other relative timeframes.

Memory Management

Name: Memory Management
Author: channingwalton

bychanningwalton

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生産性とワークフロー

Persists project context and learnings across Claude sessions using semantic search and atomic fact storage.

概要

This skill integrates the Model Context Protocol (MCP) Memory Server into Claude Code, allowing the AI to maintain a persistent knowledge base across different sessions and projects. It provides a structured way to store atomic facts, search past learnings through semantic queries, and recall information using natural language time references. By bridging the context gap between tasks, it ensures that architectural decisions, unique project constraints, and specific developer preferences are never lost, making Claude a more effective long-term partner in the development lifecycle.

主な機能

Natural language time queries for historical recall
Atomic fact storage to ensure high-precision search results
3 GitHub stars
Tag-based organization for project-specific facts
Cross-session persistence of project-specific learnings
Semantic search for content-based memory retrieval

ユースケース

Maintaining a consistent list of coding standards across multiple repositories
Recalling complex architectural decisions made in previous weeks
Building a searchable repository of project-specific constraints and edge cases

概要

主な機能

Natural language time queries for historical recall
Atomic fact storage to ensure high-precision search results
3 GitHub stars
Tag-based organization for project-specific facts
Cross-session persistence of project-specific learnings
Semantic search for content-based memory retrieval

ユースケース

Maintaining a consistent list of coding standards across multiple repositories
Recalling complex architectural decisions made in previous weeks
Building a searchable repository of project-specific constraints and edge cases