behavioral-memory

Your AI tools forget you every night. Engram watches how you work and gives them persistent memory. 100% local, zero deps, runs overnight.

Behavioral Memory for Tool Orchestration — Validated execution traces as memory for MCP-based agent systems. Based on IEEE paper.

Reasoning Ledger Protocol (RLP): an append-only protocol for auditable behavioral memory and reuse in AI agents.

Native-first, verifier-gated agent harness with a direct CLI, bounded recall, measurable policies, and privacy-safe behavioral memory.

Behavioral memory for LLM agents: compile corrections and tool failures into scoped RULE directives injected at the decision point. Five self-contained stages, 55% → 95% on DC-Bench.

DC-Bench: a benchmark for behavioral memory — does an agent apply a past correction to an unseen task, not just recall it? 71 scenarios across 9 dimensions, built from real agent traces, with control vs. treatment runs and LLM-judged lift. Approach- and provider-agnostic.

Binary behavioral learning system designed to refine AI responses through explicit human correction, output-level comparison, and trajectory-based memory.