recall

# 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 1. Runs semantic search against stored learnings (PostgreSQL + BGE embeddings) 2. Returns top 5 results with full content 3. 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: ``` ## 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`