FAVA Trails

Example Use Cases

• 1

  A version-controlled, federated memory system to track and audit their thoughts and decisions.

• 2

  LLM-based validation to ensure the coherence and safety of shared knowledge before promotion.

• 3

  Lifecycle hooks for advanced workflows like token-level compression, context engineering, and MapReduce orchestration.

Description

FAVA Trails provides a federated, version-controlled audit trail for AI agents, storing every thought, decision, and observation as markdown files tracked in a Jujutsu (JJ) monorepo. It features supersession tracking, draft isolation, LLM-based trust gate validation, and full lineage tracking to ensure coherent and crash-proof memory management. Agents interact through MCP tools without direct VCS exposure, enabling scalable and reliable multi-agent collaboration with optional lifecycle protocols for compression, reranking, and orchestration.