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    symbolic-memory

    Stateless symbolic memory effect for LLM agents

    By @th3hypn0tist
    View on GitHub
    SKILL.md
    ---
    name: symbolic-memory
    description: Stateless symbolic memory effect for LLM agents using SQL facts + canonical semantics, activated via symbols and JIT meaning (PostgreSQL + Ollama).
    metadata: {"openclaw":{"emoji":"🧠","homepage":"https://github.com/Th3Hypn0tist/random/blob/main/LLM-symbolic-memory.md","requires":{"bins":["psql","python3"],"env":["PG_DSN","OLLAMA_HOST","OLLAMA_MODEL"],"config":[]}}}
    user-invocable: true
    version: 1.0
    ---
    
    # symbolic-memory
    
    ## Purpose
    
    Provide a stateless symbolic memory workflow:
    - Store facts + canonical semantics in PostgreSQL
    - Expose references as symbols
    - Activate meaning just-in-time (budgeted)
    - Send only activated facts to the LLM (Ollama)
    
    Rule:
    Store semantics. Compute meaning. Never confuse the two.
    
    NOTE
    
    This skill does not rely on agent-local persistent memory for long-term state.
    
    Durable knowledge is stored in a shared, versioned symbolic memory substrate
    (as defined in the JIT Symbolic Memory design pattern).
    
    The skill may operate without symbolic memory, but long-term coherence
    and multi-agent consistency are only guaranteed when it is present.
    
    ## Design pattern
    
    https://github.com/Th3Hypn0tist/random/blob/main/jit-symbolic-memory-design-pattern