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From nowledge-mem
Searches memory store and threads via nmem CLI for relevant past insights on contextual signals like continuity or recurring themes. Filters by importance, labels, time.
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:search-memoryThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
**Strong signals:**
Searches and surfaces relevant memories from past sessions to inform current work with decisions, patterns, and learnings. Supports hybrid, vector, and text search modes with namespace filtering.
Retrieves relevant memories from past sessions using memsearch for historical context, decisions, debugging notes, and project knowledge. Activates on relevance or '[memsearch] Memory available' hints.
Searches mnemonic memory files by namespace, tag, type, date, title, confidence, or full-text using ripgrep and find, with progressive disclosure and optional semantic search via qmd.
Share bugs, ideas, or general feedback.
Strong signals:
Contextual signals:
Skip when:
Use nmem CLI with --json flag for programmatic search:
# Basic search
nmem --json m search "3-7 core concepts"
# With filters
nmem --json m search "API design" --importance 0.8
# With labels (multiple labels use AND logic)
nmem --json m search "authentication" -l backend -l security
# With time filter
nmem --json m search "meeting notes" -t week
Query: Extract semantic core, preserve terminology, multi-language aware
Filters:
--importance MIN: Minimum importance score (0.0-1.0)-l, --label LABEL: Filter by label (can specify multiple)-t, --time RANGE: Time filter (today, week, month, year)-n NUM: Limit number of results (default: 10)JSON Response: Parse memories array, check score field for relevance
Use thread search when the user is really asking about a prior conversation, previous session, or exact discussion:
nmem --json t search "query" --limit 5
If a memory result includes source_thread or thread search finds the likely conversation, inspect it progressively instead of loading the whole thread at once:
nmem --json t show <thread_id> --limit 8 --offset 0 --content-limit 1200
Increase --offset only when more messages are actually needed.
Scores: 0.6-1.0 direct | 0.3-0.6 related | <0.3 skip
Examples:
# Search with importance filter
nmem --json m search "database optimization" --importance 0.7
# Search with multiple labels
nmem --json m search "React patterns" -l frontend -l react
# Search recent memories
nmem --json m search "bug fix" -t week -n 5
Found: Synthesize, cite when helpful None: State clearly, suggest distilling if current discussion valuable
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.