memory-offload
SolidManages the agent's context overflow by offloading dense operational state to an Agent-Memory namespace in your knowledge graph and pulling it back when needed. This skill should ALWAYS be active as a background process. Auto-triggers when conversations get long or context-heavy. Also triggers on manual commands like "offload this", "save to memory", "dump context", "remember this for later", "store this in the graph", "memory dump", "context dump", "save state". On the PULL side, this skill triggers at the START of every conversation to check for relevant Agent-Memory pages, and mid-conversation when a topic matches stored context. Also triggers when the user says "pull my context", "load memory", "what do you have stored", "check your notes", "refresh context".
Install
Quality Score: 78/100
Skill Content
Details
- Author
- 0xUrsanomics
- Repository
- 0xUrsanomics/utopia-os
- Created
- 4 days ago
- Last Updated
- 3 days ago
- Language
- Python
- License
- MIT
Similar Skills
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memory-manager
Standardized workflow for discovering, reading, writing, and compacting the project's memory file (memory.instructions.md) to persist context across AI chat sessions, with a permanent Knowledge Base for cross-session decisions and lessons learned.
memory-load
Loads relevant entries from memory/ into the conversation context. Use at the start of any non-trivial conversation, and any time the topic might overlap with what is stored in memory (personal facts, habits, goals, relationships, work, health, hobbies, etc.). Hybrid strategy — always read memory/index.md and memory/tags.md as the map first, then pull full entry bodies by tag match and by semantic match on titles. No artificial cap on how many entries can be loaded.
memory-systems
This skill should be used for persistent semantic memory in agent systems: cross-session knowledge retention, entity tracking, temporal validity, graph or vector retrieval, memory consolidation, and memory benchmark selection. Route file-backed scratchpads to filesystem-context, handoff summaries to context-compression, and token-efficiency tactics to context-optimization.