crux-skill-memory-index

To build a prioritized memory index, scan configured memory directories and reference tracking data to extract metadata. The index ranks stored memories using type priority, strength, and reference counts to surface relevant information first for agent retrieval.

Memory index generation in CRUX-based agent systems is the process of scanning scattered memory files and reference data to produce a sorted, searchable index. This improves agent memory discovery by organizing files based on extracted metadata.

Yes, you need Python execution with the pyyaml dependency to generate a memory index. The Skill requires pyyaml specifically for parsing memory metadata and generating the validated YAML index output.

You should rebuild the agent memory index after memory updates, maintenance cycles, or REM cycles. Rebuilding refreshes memory visibility and ensures the agent discovers the most recently stored and prioritized information during retrieval.

Memories are prioritized in the generated index using type priority, strength values, and reference counts. This priority-based organization ranks memories so the most relevant and referenced information surfaces first for agent discovery.