Recall - Semantic Memory Retrieval
Query the memory system for relevant learnings from past sessions.
Usage
code
/recall <query>
Examples
code
/recall hook development patterns /recall wizard installation /recall TypeScript errors
What It Does
- •Runs semantic search against stored learnings (PostgreSQL + BGE embeddings)
- •Returns top 5 results with full content
- •Shows learning type, confidence, and session context
Execution
When this skill is invoked, run:
bash
cd $CLAUDE_OPC_DIR && PYTHONPATH=. uv run python scripts/core/recall_learnings.py --query "<ARGS>" --k 5
Where <ARGS> is the query provided by the user.
Output Format
Present results as:
code
## Memory Recall: "<query>" ### 1. [TYPE] (confidence: high, id: abc123) <full content> ### 2. [TYPE] (confidence: medium, id: def456) <full content>
Options
The user can specify options after the query:
- •
--k N- Return N results (default: 5) - •
--vector-only- Use pure vector search (higher precision) - •
--text-only- Use text search only (faster)
Example: /recall hook patterns --k 10 --vector-only