name: recall description: Semantic search for memory. Use to find solutions, patterns, or context from Chroma Cloud.

Recall Memory

This skill allows you to search your memory system using semantic queries.

Workflow

1. Formulate Your Query: Think about what you're trying to find:

   • A solution to a specific problem (e.g., "How do I fix CORS errors?")
   • A pattern or best practice (e.g., "Python async patterns")
   • Historical context (e.g., "What did we decide about routing?")

2. Run the Search: Execute the memory manager recall command:

   uv run python .fleet/context/scripts/memory_manager.py recall "<your query>"
   

   Example:

   uv run python .fleet/context/scripts/memory_manager.py recall "memory system implementation"
   

3. Review Results: The system will return:

   • Top matches from semantic memory (facts, decisions)
   • Relevant skills from procedural memory (how-tos)
   • Similarity scores to gauge relevance
   • Source metadata (file paths, timestamps)

4. Refine if Needed: If results aren't relevant, try:

   • More specific queries (add context/domain)
   • Different terminology (synonyms)
   • Breaking complex queries into simpler parts

Tips

• Use natural language - the system uses semantic search, not keyword matching
• Be specific - "fix DSPy routing errors" is better than "errors"
• Combine with other commands: recall → apply solution → learn new variation
• Check episodic memory separately if you need conversation history

Output Format

Results include:

• Matched text snippets
• Source file paths
• Relevance scores (0-1, higher = better match)
• Metadata (creation date, tags, etc.)