Agent skill

search-memory

Search past decisions, procedures, learnings, or context relevant to the current task. Trigger when work connects to prior decisions, a debugging pattern resembles a past issue, the user asks about rationale, or uses recall language like "that approach" or "like before".

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Install this agent skill to your Project

npx add-skill https://github.com/nowledge-co/community/tree/main/nowledge-mem-codex-plugin/skills/search-memory

SKILL.md

Find what the user already knows. Search their memories and past conversations for decisions, procedures, and context that make the current task sharper.

For continuation-style engineering work, search near the start of the task. Do not wait for the user to literally say "search memory".

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
  • The task is a review, regression, release, docs-alignment, or integration-behavior question
  • 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

When NOT to search:

  • Fundamentally new topic with no prior history
  • Generic syntax or API questions answerable from documentation
  • User explicitly asks for a fresh perspective without prior context

Retrieval routing

  1. Start with nmem --json m search "query" for durable knowledge (decisions, insights, procedures).
  2. Use nmem --json t search "query" --limit 5 when the user is 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 that answers the question. Do not over-fetch.

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

Deep mode

If results are weak or the need is conceptual/historical, try deeper matching:

bash
nmem --json m search "query" --mode deep

Filters

Add filters only when the task clearly implies them:

  • By label: -l "label-name"
  • By importance: --importance 0.7
  • By date range: --event-from 2026-01-01 / --event-to 2026-03-01
  • By source: -s codex
  • Limit results: -n 10

Summarize only the strongest matches and clearly say when nothing relevant was found.

Links

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