Engram Memory Retrieval FAQs

Question 1

When should I use semantic query construction?

Accepted Answer

Use it when you need to capture the conceptual meaning of a request, such as 'user preferences for error handling,' rather than using generic or temporal keywords like 'error handling' or 'what we did yesterday.'

Question 2

What are the different memory types supported?

Accepted Answer

The skill categorizes memories into 'episodic' for raw observations, 'semantic' for synthesized insights, and 'procedural' for specific workflows and how-to knowledge.

Question 3

How does the weight tuning work in Engram?

Accepted Answer

It uses a three-factor scoring system based on Recency, Importance, and Relevance, which can be dynamically adjusted depending on whether the intent is to find recent context or long-term best practices.

Question 4

What is the purpose of the Memory Retrieval skill?

Accepted Answer

It provides specialized patterns for searching an AI's memory graph to ensure Claude retrieves the most relevant and useful historical context for its current tasks.

Question 5

How does the skill handle insufficient search results?

Accepted Answer

It provides strategies to broaden the query semantically, reduce relevance weights to boost other factors, or remove specific type filters to find the next best matches.

Engram Memory Retrieval

주요 기능

사용 사례

Engram Memory Retrieval

주요 기능

사용 사례