How do I narrow down search results in Recall?

You can use advanced filters such as project names, specific tags (using AND logic), memory types, or time-based filters like 'created_max_age_days'.

Why are the relevance scores for memories so low?

The skill uses Reciprocal Rank Fusion (RRF) scores, where values between 0.01 and 0.05 are standard. You should judge results by their ranking order rather than the absolute score value.

What is the Erinra MCP server?

Erinra is a specialized Memory Context Provider server that allows Claude to store and retrieve persistent information, creating a long-term memory for your development projects.

How do I see the full text of a truncated memory?

If search results are truncated, the skill uses the 'get' command with the specific memory ID to fetch the complete content and all associated metadata.

Can I browse memories without a specific search query?

Yes, the skill includes a browsing function that lists memories filtered by project or type without requiring a keyword search.

Memory Recall

Name: Memory Recall
Author: alphaleonis

byalphaleonis

0•

Productivity & Workflow

Searches and retrieves stored memories, patterns, and architectural decisions from the Erinra MCP server.

Memory Recall is a sophisticated retrieval skill for the decaf-memory plugin that allows Claude to access persistent project context and historical knowledge. By interfacing with the Erinra MCP server, it enables developers to surface previously stored code patterns, configuration details, and user preferences using natural language queries. This skill is essential for maintaining continuity across development sessions, allowing the AI to leverage specific organizational knowledge such as retry policies, timeout settings, or project-specific implementation standards.

Key Features

01Full content retrieval for detailed viewing of stored entries

02Time-based retrieval for recently created or updated context

03Relationship mapping to explore incoming and outgoing memory links

04Advanced filtering by project, tags, and memory type

05Semantic search for stored memories and technical patterns

060 GitHub stars

Use Cases

01Browsing recent project updates and documented patterns during onboarding

02Retrieving previously documented architectural decisions or user preferences

03Finding specific implementation patterns like Polly retry policies or HttpClient configurations

Key Features

01Full content retrieval for detailed viewing of stored entries

02Time-based retrieval for recently created or updated context

03Relationship mapping to explore incoming and outgoing memory links

04Advanced filtering by project, tags, and memory type

05Semantic search for stored memories and technical patterns

060 GitHub stars

Use Cases

01Browsing recent project updates and documented patterns during onboarding

02Retrieving previously documented architectural decisions or user preferences

03Finding specific implementation patterns like Polly retry policies or HttpClient configurations