majiayu000 Distill Memory
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
{
"content": "Insight + context for future use",
"title": "Searchable (50-60 chars)",
"importance": 0.8,
"labels": "tech,domain,topic"
}
Content: Outcome/insight focus, include "why", enough context
Importance: 0.8-1.0 major | 0.5-0.7 useful | 0.3-0.4 minor
Labels: 2-4 max, check existing first, lowercase-hyphenated
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 the MCP is not installed, you can install it with the following command:
claude mcp add --transport http nowledge-mem http://localhost:14242/mcp --scope user