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