From engram
Searches preferences, conversations, and long-term memory files using grep to recall past discussions and context. Integrates results naturally. Auto-triggers on history references.
How this skill is triggered — by the user, by Claude, or both
Slash command
/engram:memory-recallThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Search and retrieve relevant memories from the memory files.
Search and retrieve relevant memories from the memory files.
This skill is auto-triggered by the Engram hook instructions. Use it when:
Do NOT guess or assume — search memory files first, then respond with confidence.
Read .claude/memory-settings.json to get the configured file names.
From the current conversation context, identify:
Execute searches across all three files simultaneously:
### YYYY-MM-DD entries and their contentCombine findings from all files into a coherent response:
Integrate recalled memories naturally into your response. Examples:
Good: "Based on our previous discussion, you decided to use PostgreSQL for this project. You also mentioned preferring connection pooling via PgBouncer."
Bad: "I searched memory_conversations.md and found an entry from 2025-01-15 that mentions PostgreSQL. I also found in memory_longterm.md under Architecture Decisions..."
The user should feel like you genuinely remember, not like you're reading from a database.
npx claudepluginhub legacybridge-tech/claude-plugins --plugin engramRetrieves relevant memories from past sessions using memsearch for historical context, decisions, debugging notes, and project knowledge. Activates on relevance or '[memsearch] Memory available' hints.
Recalls past context, decisions, and discussions from Memsy memory. Activates on retrieval-intent queries like "what did we decide" or "search past conversations."
Searches and surfaces relevant memories from past sessions to inform current work with decisions, patterns, and learnings. Supports hybrid, vector, and text search modes with namespace filtering.