search-memory

Original：🇺🇸 English
Translated

Search your personal knowledge base when past insights would improve response. Recognize when stored breakthroughs, decisions, or solutions are relevant. Search proactively based on context, not just explicit requests.

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Sourcenowledge-co/community
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NPX Install

npx skill4agent add nowledge-co/community search-memory

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Translated version includes tags in frontmatter
semantic-searchpersonal-knowledge-basenowledge-memai-toolcli-usage

SKILL.md Content

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Search Memory

AI-powered semantic search across your personal knowledge base using Nowledge Mem.

When to Use

Strong signals to search:
  • 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

Prerequisites

nmem CLI - Choose one option:
Option 1: uvx (Recommended)
bash
# Install uv if needed
curl -LsSf https://astral.sh/uv/install.sh | sh

# Run nmem directly (auto-downloads)
uvx --from nmem-cli nmem --version
Option 2: pip
bash
pip install nmem-cli
nmem --version
Ensure Nowledge Mem server is running at 
http://localhost:14242

Usage

Use 
nmem
CLI with 
--json
flag for programmatic search:
bash
# Basic search
nmem --json m search "your query here"

# With importance filter
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

# Limit results
nmem --json m search "debugging tips" -n 5

Query Guidelines

  • Extract semantic core from user's request
  • Preserve domain terminology
  • Multi-language aware (works with any language)
  • Use 3-7 core concepts for best results

Available Filters

FlagDescriptionExample
--importance MIN
Minimum importance (0.0-1.0)
--importance 0.7
-l, --label LABEL
Filter by label (repeatable)
-l frontend -l react
-t, --time RANGE
Time filter
-t today
, 
-t week
, 
-t month
-n NUM
Limit results
-n 5

Understanding Results

Parse the 
memories
array from JSON response. Check 
score
field:
  • 0.6-1.0: Directly relevant - include in response
  • 0.3-0.6: Related context - may be useful
  • < 0.3: Skip - not relevant enough

Response Guidelines

Found relevant memories: Synthesize insights, cite when helpful
No results: State clearly, suggest distilling current discussion if valuable

Examples

bash
# Search for React patterns
nmem --json m search "React hooks patterns" -l frontend

# Find debugging solutions
nmem --json m search "memory leak debugging" --importance 0.6

# Recent project decisions
nmem --json m search "architecture decision" -t month -n 10

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