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From nowledge-mem
Detects breakthrough moments, blocking resolutions, design decisions, and high-value insights in coding conversations. Suggests distilling them into atomic memories via nmem CLI for future reference.
npx claudepluginhub joshuarweaver/cascade-code-general-misc-2 --plugin nowledge-co-communityHow this skill is triggered — by the user, by Claude, or both
Slash command
/nowledge-mem:distill-memoryThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Save proactively when the conversation produces a decision, preference, plan, procedure, learning, or important context. Do not wait to be asked.
Captures decisions, learnings, patterns, and context as persistent memories organized by namespace across Claude Code sessions.
Stores important decisions, patterns, bug fixes, and lessons into Cortex persistent memory. Use after resolving bugs, making architecture choices, or when the user asks to remember something.
Manages persistent memory across Claude Code sessions via AutoMem. Recall project context, architectural decisions, bug fixes, user preferences, and patterns at session start or debugging.
Share bugs, ideas, or general feedback.
Save proactively when the conversation produces a decision, preference, plan, procedure, learning, or important context. Do not wait to be asked.
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
Good (atomic + actionable):
Poor: Vague "Fixed bugs", conversation transcript
Use nmem CLI to create memories:
nmem m add "Insight + context for future use" \
-t "Searchable title (50-60 chars)" \
-i 0.8
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:
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:
# 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
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
If nmem is not in PATH: pip install nmem-cli
For remote servers: create ~/.nowledge-mem/config.json with {"apiUrl": "...", "apiKey": "..."}.
Run /status to check server connection.