By name: nowledge-mem description: Search, save, and manage knowledge across all your AI tools through Nowledge Mem. license: Apache-2.0 compatibility: ">=3.12" metadata: {} allowed-tools: - mem.search - mem.save - mem.context - mem.connections - mem.timeline - mem.forget - mem.threads - mem.thread - mem.status
Nowledge Mem — Cross-Tool Knowledge for Bub
You have access to the user's personal knowledge graph through Nowledge Mem. This graph contains knowledge from all their AI tools — decisions from Claude Code, preferences from Cursor, insights from ChatGPT, and more — not just this Bub session. Knowledge you save here will be available in their other tools too.
When to search
Recognise these signals and call mem.search before answering:
- Continuity — the user references something from a previous session or another tool
- Decision recall — "what did we decide about…", "why did we choose…"
- Pattern match — the current topic overlaps with past work in any tool
- Implicit recall — the user assumes you know something you haven't seen this session
Search both memories and threads. When a memory has source_thread_id,
fetch the full conversation with mem.thread for deeper context.
When to save
Call mem.save when durable knowledge appears:
- Decisions — compared options and chose one
- Learnings — debugging revealed something non-obvious
- Preferences — user stated how they want things done
- Plans — concrete next steps agreed on
- Procedures — repeatable workflow documented
Skip: routine fixes, work-in-progress, simple Q&A, generic info.
Guidelines:
- Atomic and actionable — one idea per memory
- Title is a short summary, content is the detail
- 0–3 labels per memory (project names, topics)
- Importance: 0.8–1.0 critical | 0.5–0.7 useful | 0.1–0.4 minor
- Save proactively when the value is durable; do not wait for the user to ask.
Context Bundle
mem.context returns Nowledge Mem's Context Bundle: owner identity, resolved
AI Identity, active scope, active rules, and Working Memory. Read it at the start
of a session when identity, scope, or rules matter. If the installed nmem
is older, the tool falls back to the lightweight Working Memory briefing.
Thread retrieval
Two paths into past conversations:
- From a memory:
mem.searchreturnssource_thread_id→mem.thread - Direct search:
mem.threadsfinds conversations by keyword →mem.thread
Use offset for pagination on long threads.
Graph exploration
mem.connections shows how a memory relates to other knowledge:
related topics, EVOLVES chains (how understanding changed over time),
and source document provenance.
mem.timeline shows recent activity grouped by day.