Query and manage RALPH's persistent memory stored in .ralph/memory/*.json files.
npx skills add https://github.com/doravidan/supreme-ralph --skill ralph-memory
Please help me install this Agent Skill. Skill: ralph-memory Source: https://github.com/doravidan/supreme-ralph/tree/main/templates/global/skills/ralph-memory Command: npx skills add https://github.com/doravidan/supreme-ralph --skill ralph-memory
Query and manage RALPH's persistent memory layer across sessions.
Run: /ralph-memory to view stats, or /ralph-memory query "term" to search memory.
High-intent search queries and answers about installing and using this skill.
To query persistent AI memory across sessions, use the /ralph-memory query "term" command to search stored insights, or run /ralph-memory to view recent stats and memory entries.
You can export and clean up old AI memory entries using /ralph-memory commands designed to export stored data and prune outdated entries, keeping your cross-session context retention optimized.
Yes, you can manage entities, insights, and relationships in cross-project AI workflows by running specific memory commands to inspect, update, and prune stored context.
Persistent memory data for AI development workflows is stored locally in .ralph/memory/*.json files, allowing you to inspect, export, and manage cross-session context directly.
The best way to retain context across AI development sessions is to use a persistent memory layer that automatically stores insights and relationships in local JSON files for later querying.
No specific dependencies are required to inspect memory and view stats, as the persistent memory layer operates independently and stores data locally in .ralph/memory/*.json files.
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