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Search Memory

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

When to Use

Strong signals — search when:

• the user references previous work, a prior fix, or an earlier decision
• the task resumes a named feature, bug, refactor, incident, or subsystem
• a debugging pattern resembles something solved earlier
• the user asks for rationale, preferences, procedures, or recurring workflow details
• the user uses implicit recall language: "that approach", "like before", "the pattern we used"

Contextual signals — consider searching when:

• complex debugging where prior context would narrow the search space
• architecture discussion that may intersect with past decisions
• domain-specific conventions the user has established before
• the current result is ambiguous and past context would make the answer sharper

Retrieval Routing

1. Start with nmem --json m search for durable knowledge.
2. Use nmem --json t search when the user is really asking about a prior conversation or exact session history.
3. If a result includes source_thread, inspect it progressively with nmem --json t show <thread_id> --limit 8 --offset 0 --content-limit 1200.
4. Prefer the smallest retrieval surface that answers the question.

Native Plugin

These skills work in any agent via CLI. For auto-recall, auto-capture, and graph tools, check if your agent has a native Nowledge Mem plugin — run the check-integration skill or see https://mem.nowledge.co/docs/integrations

Weekly Installs

338

Repository

nowledge-co/community

GitHub Stars

61

First Seen

Feb 15, 2026

Security Audits

Gen Agent Trust HubPassSocketPassSnykPass

Installed on

codex319

opencode319

gemini-cli314

github-copilot309

kimi-cli304

amp302