Lore
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Concepts

Understand the model Lore uses for long-term memory: durable paths, disclosure triggers, recall, and Dream maintenance.

Path-native memoryDurable context that agents can return to.

Every memory has an address, a trigger, a priority, and recall evidence.

core://agent project://lore_integration recall query_id

Lore gives AI agents one shared long-term memory system.

It replaces the pattern of copying rules into every local CLAUDE.md, AGENTS.md, and plugin file. Instead, agents read and write a single memory graph that survives sessions, runtimes, and machines.

The short version

  • Boot memory provides stable startup context such as shared agent rules, user preferences, and runtime-specific constraints.
  • Recall provides task-specific candidate memories for the current prompt.
  • Agents should open recalled nodes before treating them as facts.
  • Durable changes should be written back into Lore, not copied into every local agent file.
  • Dream helps review and improve memory quality, but important changes still need human review.

How agents use Lore

*.txt
Plaintext
Startup  →  Load boot context (core rules, preferences, channel rules)
Prompt   →  Receive recall candidates for the current task
Work     →  Open relevant nodes, use them as context
Write    →  Save durable facts, decisions, and rules back to Lore
Review   →  Dream checks memory quality, suggests improvements

Start with the three concept pages if you are new to Lore:

  1. What Lore is for
  2. How Lore works
  3. When to use it

Then read the memory model pages when you are ready to write better memories: paths, disclosure triggers, priority, and glossary terms.

What Lore is forLearn which facts, preferences, decisions, and rules should become durable memory.How Lore worksUnderstand the loop: boot context, recall, reading memories, writing durable changes, and review.When to use itDecide which information is worth saving and which short-lived notes can stay out of memory.Memory modelLearn the core memory shape: paths, domains, priority, disclosure, glossary terms, and generated views.