---
name: Distill Memory
slug: distill-memory-2
category: AI Engineering
description: Distill Memory captures durable facts, decisions, preferences, and lessons from a conversation when they are likely to save time later. It suggests saving insights after breakthroughs, resolutions, or other high-value moments.
github: "https://github.com/nowledge-co/community/tree/main/nowledge-mem-claude-code-plugin/skills/distill-memory"
language: Python
stars: 166
forks: 35
install: "npx degit https://github.com/nowledge-co/community/tree/main/nowledge-mem-claude-code-plugin/skills/distill-memory ~/.claude/skills/distill-memory"
installs_to: ~/.claude/skills/distill-memory
source_path: nowledge-mem-claude-code-plugin/skills/distill-memory/SKILL.md
collection_size: 25
category_size: 3670
collection_url: "https://dirskills.com/collections/nowledge-co/community"
added: 2026-09-08T05:34:51.466Z
last_synced: 2026-09-08T05:34:51.466Z
canonical_url: "https://dirskills.com/skills/distill-memory-2"
---

# Distill Memory

Distill Memory captures durable facts, decisions, preferences, and lessons from a conversation when they are likely to save time later. It suggests saving insights after breakthroughs, resolutions, or other high-value moments.

**Install:**

```bash
npx degit https://github.com/nowledge-co/community/tree/main/nowledge-mem-claude-code-plugin/skills/distill-memory ~/.claude/skills/distill-memory
```

## README

# Distill Memory

Save proactively when the conversation produces a durable fact, preference, decision, plan, procedure, learning, event, or important context. Do not wait to be asked.

## When to Suggest (Moment Detection)

**Breakthrough:** Extended debugging resolves, user relief ("Finally!", "Aha!"), root cause found

**Decision:** Compared options, chose with rationale, trade-off resolved

**Research:** Investigated multiple approaches, conclusion reached, optimal path determined

**Twist:** Unexpected cause-effect, counterintuitive solution, assumption challenged

**Lesson:** "Next time do X", preventive measure, pattern recognized

**Skip:** Routine fixes, work in progress, simple Q&A, generic info

## Memory Quality

**Good (atomic + actionable):**

- "React hooks cleanup must return function. Caused leaks."
- "PostgreSQL over MongoDB: ACID needed for transactions."

**Poor:** Vague "Fixed bugs", conversation transcript

## Tool Usage

Use `nmem` CLI to create memories:

```bash
nmem m add "Insight + context for future use" \
  -t "Searchable title (50-60 chars)" \
  -i 0.8
```

Add `--unit-type fact|preference|decision|plan|procedure|learning|context|event` when the type is clear.

If an existing memory already captures the same decision, workflow, or preference and the new information refines it, update that memory instead of creating a duplicate:

```bash
nmem m update <id> -t "Updated title"
```

**Content:** Outcome/insight focus, include "why", enough context

**Importance:** 0.8-1.0 major | 0.5-0.7 useful | 0.3-0.4 minor

**Note:** For programmatic use, add `--json` flag to get JSON response

**Examples:**

```bash
# High-value insight
nmem m add "React hooks cleanup must return function. Caused memory leaks in event listeners." \
  -t "React Hooks Cleanup Pattern" \
  -i 0.9

# Decision with context
nmem m add "Chose PostgreSQL over MongoDB for ACID compliance and complex queries" \
  -t "Database: PostgreSQL" \
  -i 0.9
```

## Suggestion

**Timing:** After resolution/decision, when user pauses

**Pattern:** "This [type] seems valuable - [essence]. Distill into memory?"

**Frequency:** 1-3 per session typical, quality over quantity

## Troubleshooting

If `nmem` is not in PATH: `pip install nmem-cli`, or on Arch Linux `yay -S nmem-cli` / `paru -S nmem-cli`

For remote servers: run `nmem config client set url https://...` and `nmem config client set api-key ...` once on this machine.

Run `/status` to check server connection.