By name: search-memory description: Search memory store when past insights would improve response. Recognize when user's stored breakthroughs, decisions, or solutions are relevant. Search proactively based on context, not just explicit requests.
Search Memory
When to Search (Autonomous Recognition)
Strong signals:
- Continuity: Current topic connects to prior work
- Pattern match: Problem resembles past solved issue
- Decision context: "Why/how we chose X" implies documented rationale
- Recurring theme: Topic discussed in past sessions
- Implicit recall: "that approach", "like before"
Contextual signals:
- Complex debugging (may match past root causes)
- Architecture discussion (choices may be documented)
- Domain-specific question (conventions likely stored)
Skip when:
- Fundamentally new topic
- Generic syntax questions
- Fresh perspective explicitly requested
Tool Usage
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
If the runtime already knows the active project or agent lane, add --space "<space name>".
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
Response
Found: Synthesize, cite when helpful None: State clearly, suggest distilling if current discussion valuable
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.