| name | recall |
| description | Query the memory system for relevant learnings from past sessions using semantic search. |
Recall - Semantic Memory Retrieval
Query the memory system for relevant learnings from past sessions.
Usage
/recall <query>
Examples
/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:
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:
## 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
