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.

3installs

Sourcenowledge-co/community

Added on2026-02-16

NPX Install

npx skill4agent add nowledge-co/community search-memory

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

Flag	Description	Example
`--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

search-memory

NPX Install

Tags

SKILL.md Content

Search Memory

When to Use

Prerequisites

Usage

Query Guidelines

Available Filters

Understanding Results

Response Guidelines

Examples

Links