Search Memory

nowledge-co/community/nowledge-mem-copilot-cli-plugin/skills/search-memory

作者 nowledge-co1f4d7eb61466dbfc93ce8d7a0a806c4d4a196dd0无许可证收录于 2026年10月9日更新于 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.

AI 生成的概览

指导智能体主动检索记忆库,找出相关的过往洞见、决策与解决方案。

功能
该技能指导智能体在何时以及如何检索持久化记忆库,以获取与当前对话相关的过往突破、决策或解决方案。它定义了自主检索的识别信号,提供 nmem 命令行工具用于记忆与对话线程检索,并支持按重要性、标签和时间等条件过滤,同时说明如何解读相关性评分并作出回应。其产出是对过往上下文的综合回顾,必要时会引用来源;若未找到相关内容,则会明确说明。
适用场景
当当前话题与过往工作相关、与曾解决的问题相似,或涉及有记录的决策依据、反复出现的主题,以及“那个方法”之类的隐含指代时,适合使用。它也适用于复杂调试、架构讨论以及可能存有既定约定的领域特定问题。对于全新话题、通用语法问题,或用户明确要求全新视角的情况,则应跳过。
运行要求
需要安装 nmem 命令行工具并使其位于 PATH 中(pip install nmem-cli,Arch Linux 上可用 yay/paru)。连接远程服务器需配置 URL 和 API 密钥,可用 nmem status 检查连接。该技能不附带脚本,仅为说明性指令。

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

If the runtime already knows the active project or agent lane, add --space "<space 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 nmem status to check server connection.

来源与署名

来源:nowledge-co/community位于nowledge-mem-copilot-cli-plugin/skills/search-memory提交1f4d7eb

许可证: 无许可证

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