Cognitive memory layer for LLM agents — typed graph + bi-temporal substrate + curator API, reached through the kaeru MCP server. Use when the user wants to capture, recall, reason, or trace persistent thoughts across sessions; when re-entering a multi-session project; or when the user explicitly asks to "remember"…
How to query the INITE Brain knowledge graph across time — the asOf parameter, validFrom/validUntil semantics, reading retracted facts, and the memorydiff "what changed between two cursors" surface. Use when the user's question has a temporal dimension ("on X date", "before Y", "what's new since last conversation").
How to detect and resolve conflicting beliefs in the INITE Brain knowledge graph — the COMPETING fact status, getcompetingfacts, detectcontradiction preflight, and the human-in-the-loop adjudication workflow. Use when the timeline shows two facts disagreeing on the same predicate, or when an agent needs to decide what…
How to write to the INITE Brain knowledge graph from an agent loop — recordfact, linkentities, retractfact, and the detectcontradiction preflight. Covers confidence picking, retract vs forget semantics, identityof cycle-guards. Use when the user explicitly wants to record, merge, or revise structured knowledge from a…
Send, poll, wait for, and acknowledge durable addressed agent-to-agent messages in Aionforge Memory (messagesend, messagepoll, messagewait, messageack) and subscribe to room resources. Use to hand a brief to another agent, page a teammate, wait for a reply, coordinate a multi-agent workflow, or drain an inbox …
One-time setup that lays a foundational Aionforge Memory substrate for a fresh project — resolve identity, seed conventions and architecture decisions as captures, stand up a work-item backlog skeleton, and verify recall. Use when a project's memory is empty or new, or when the user asks to set up, bootstrap…
Capture durable Aionforge Memory records for decisions, user preferences, project facts, release outcomes, validation results, handoffs, corrections, and reusable failure patterns. Use proactively during substantial work and whenever the user asks to remember or update memory.
Wire Lians memory into an existing agent codebase, test-first and minimal-diff. Use when the user asks to add persistent/compliance memory to their agent, integrate Lians, or replace a vector store with bitemporal memory.
Use Lians financial-grade agent memory — store and recall facts with a bitemporal model so stale revisions never contaminate context. Use whenever an agent needs persistent memory in finance, healthcare, or legal work, or when a task asks "what did we know on/before ", needs an audit trail, or must erase a data…