Search Memory

nowledge-co/community/nowledge-mem-claude-code-plugin/skills/search-memory

作者 nowledge-co1f4d7eb61466dbfc93ce8d7a0a806c4d4a196dd0無授權條款收錄於 2026年10月9日更新於 2026年10月9日

Search memory store when past insights would improve response. Recognize when user's stored breakthroughs, decisions, or solutions are relevant. Search proactively based on context, not just explicit requests.

僅含說明AI & Agents
AI 產生的概覽

引導代理搜尋記憶庫,找出相關的過往見解、決策與解決方案。

功能
此技能引導代理何時以及如何使用帶 JSON 輸出的 nmem 命令列工具搜尋記憶庫。內容涵蓋辨識過往見解相關的情境訊號、建立語意查詢、套用重要性、標籤與時間篩選條件,以及解讀相關性分數。它也說明如何搜尋過往對話串並逐步檢視。
適用情境
適用於目前主題與過往工作相關、與已解決的問題相似,或涉及有記錄的決策與反覆出現的主題時。也適用於複雜除錯、架構討論,以及可能已有既定慣例的特定領域問題。
執行需求
需要 nmem 命令列工具,可透過 pip install nmem-cli 或 Arch Linux 套件管理員安裝。遠端使用需設定伺服器 URL 與 API 金鑰,並能連線至該伺服器。此技能不附帶指令碼,僅為說明性內容。

Search Memory

When to Search (Autonomous Recognition)

Strong signals:

  • 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

Tool Usage

Use nmem CLI with --json flag for programmatic search:

bash
# Basic searchnmem --json m search "3-7 core concepts"
# With filtersnmem --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 filternmem --json m search "meeting notes" -t week

Only add --space "<space name>" when the user or environment explicitly provided that existing Mem space (for example NMEM_SPACE). Never infer a space from the current folder, git repository, branch, or project name.

Query: Extract semantic core, preserve terminology, multi-language aware

Filters:

  • --importance MIN: Minimum importance score (0.0-1.0)
  • -l, --label LABEL: Filter by label (can specify multiple)
  • -t, --time RANGE: Time filter (today, week, month, year)
  • -n NUM: Limit number of results (default: 10)

JSON Response: Parse memories array, check score field for relevance

Use thread search when the user is really asking about a prior conversation, previous session, or exact discussion:

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

If a memory result includes source_thread or thread search finds the likely conversation, inspect it progressively instead of loading the whole thread at once:

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

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

Scores: 0.6-1.0 direct | 0.3-0.6 related | <0.3 skip

Examples:

bash
# Search with importance filternmem --json m search "database optimization" --importance 0.7
# Search with multiple labelsnmem --json m search "React patterns" -l frontend -l react
# Search recent memoriesnmem --json m search "bug fix" -t week -n 5

Response

Found: Synthesize, cite when helpful None: State clearly, suggest distilling if current discussion valuable

Troubleshooting

If nmem is not in PATH: pip install nmem-cli, or on Arch Linux yay -S nmem-cli / paru -S nmem-cli

For remote servers: run nmem config client set url https://... and nmem config client set api-key ... once on this machine.

Run /status to check server connection.

來源與署名

來源:nowledge-co/community位於nowledge-mem-claude-code-plugin/skills/search-memory提交1f4d7eb

授權條款: 無授權條款

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