search-memory（搜索记忆）

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

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.