Recall - Semantic Memory Retrieval
SkillDocs & knowledgeLets your agent search its memory of past sessions for relevant learnings.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Recall - Semantic Memory Retrieval skill
About this capability
Query the memory system for relevant learnings from past sessions
What this skill tells your AI
The instructions your AI receives, as published by parcadei/continuous-claude-v3 in .claude/skills/recall/SKILL.md and read by ahel’s review.
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
Signals
- GitHub stars
- 4k
- Forks
- 300
- Last commit
- Jan 2026
Advanced
- Catalog kind
- skill
- Gateway key
recall-parcadei- Source
- github.com/parcadei/continuous-claude-v3