Search Memory

nowledge-co/community/nowledge-mem-omp-plugin/skills/search-memory

by nowledge-co1f4d7eb61466dbfc93ce8d7a0a806c4d4a196dd0No licenseListed Oct 9, 2026Updated Oct 9, 2026

Search your knowledge base when past decisions, preferences, or procedures would improve the response. Covers memories from every AI tool you use.

Instructions onlyAI & Agents
AI-generated overview

Guides an agent to search a personal memory and past-conversation store before answering, using the nmem CLI.

What it does
This skill instructs an agent on when and how to query a memory system before responding. It describes strong and contextual signals for searching, routing between distilled memories and past conversation threads, key command flags, and how to interpret relevance scores. It also lists cases where searching should be skipped.
When to use it
Use when a request references prior work, resumes a named project, asks for rationale behind an earlier decision, resembles a past fix, or concerns a recurring theme. It is also meant for complex debugging, architecture discussions, and domain-specific questions where stored conventions may exist.
Requirements
Requires the nmem command-line tool to be installed and available, plus access to the user's memory and thread store. Network access may be needed depending on how that store is hosted. No scripts ship with the skill; it is instructions only.

Search Memory

When to Search

Strong signals:

  • References prior work: "the approach we used", "like last time"
  • Resumes a named feature, project, or migration
  • Review, regression, release, docs-alignment, or connector-behavior task
  • Debugging resembles a past fix or known root cause
  • Asks for rationale: "why did we choose X?"
  • Recurring theme discussed in earlier sessions

Contextual signals:

  • Complex debugging (may match past root causes)
  • Architecture discussion (choices may be documented)
  • Domain-specific question (conventions likely stored)
  • User mentions a timeframe: "last week", "back in January"

Skip when:

  • Fundamentally new topic with no prior context
  • Generic syntax or language questions
  • User explicitly requests a fresh perspective

Retrieval Routing

1. Search memories (distilled knowledge)

bash
nmem --json m search "3-7 word semantic query"

If the runtime already knows the active project or agent lane, add --space "<space name>".

2. Search threads (past conversations)

When the user asks about a prior session, discussion, or exact exchange:

bash
nmem --json t search "query" --limit 5

3. Progressive thread inspection

If a thread looks relevant, load it incrementally:

bash
nmem --json t show <thread_id> --limit 8 --offset 0 --content-limit 1200

Increase --offset only when more messages are actually needed.

For continuation-heavy engineering work, search near the start of the task rather than waiting for an explicit recall request.

Key Flags

FlagPurpose
--mode deepConceptual or weak first-pass results
-l labelFilter by label (multiple uses AND logic)
-n limitLimit number of results (default: 10)
--importance MINMinimum importance score (0.0-1.0)
--time RANGETime filter: today, week, month, year

Examples

bash
# Semantic search with importance filternmem --json m search "database optimization" --importance 0.7
# Filter by labelsnmem --json m search "React patterns" -l frontend -l react
# Recent memories onlynmem --json m search "deployment fix" --time week -n 5
# Deep mode for conceptual queriesnmem --json m search "auth architecture rationale" --mode deep

Interpreting Results

Scores: 0.6-1.0 direct match. 0.3-0.6 related. Below 0.3, skip.

Found: Synthesize and cite when helpful. None: State clearly. Suggest distilling if the current discussion is valuable.

When NOT to Search

Do not search for every message. Search when there is a reasonable expectation that prior knowledge exists and would improve the response. One well-targeted search is better than three speculative ones.

Links

Source and attribution

Source:nowledge-co/communityinnowledge-mem-omp-plugin/skills/search-memoryat commit1f4d7eb

License: No license

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