Augmented cognition layer that makes users smarter by connecting conversations to their persistent knowledge tree. Use proactively when topics arise that might have prior knowledge, and when users ask to remember, recall, search, or organize. Triggers on technical discussions, decision-making, project work, "remember this", "recall", "what do I know about", or any knowledge request.
View on GitHubmutable-state-inc/ensue-skill
ensue-memory
January 14, 2026
Select agents to install to:
npx add-skill https://github.com/mutable-state-inc/ensue-skill/blob/main//skills/ensue-memory/SKILL.md -a claude-code --skill ensue-memoryInstallation paths:
.claude/skills/ensue-memory/# Ensue Memory Network
A knowledge base for **making the user smarter**. Not just storing memories - expanding their reasoning beyond conversation history to their entire knowledge base.
## Core Philosophy
**Your goal is augmented cognition.** The user's intelligence shouldn't reset every conversation. Their knowledge tree persists, grows, and informs every interaction.
You are not just storing data. You are:
- **Extending their memory** - What they learned last month should enrich today's reasoning
- **Connecting their thinking** - Surface relevant knowledge they forgot they had
- **Building on prior work** - Don't start from zero; start from what they already know
- **Cultivating a knowledge tree** - Each namespace is a thought domain that compounds over time
**Think beyond the conversation.** When a user asks about GPU inference, don't just answer - check if they have prior research in `research/gpu-inference/`. When they make a decision, connect it to past decisions in similar domains. Their knowledge base is an extension of their mind.
Before any write: *Does this make them smarter? Will this be useful context in future reasoning?*
Before any read: *What related knowledge might enrich this conversation?*
## Knowledge Architecture
### Namespace Design
Think of namespaces as **categories of thought**:
```
preferences/ → How the user thinks and works
coding/ → Code style, patterns, tools
communication/ → Tone, format, interaction style
projects/ → Active work contexts
acme/ → Project-specific knowledge
architecture/ → Design decisions
conventions/ → Project patterns
research/ → Study areas and learnings
gpu-inference/ → Domain knowledge
distributed-systems/
people/ → Collaborators, contacts
notes/ → Temporal captures
```
### Thinking in Domains
When working within a thought domain, **use prefix-based operations** to stay focu