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knowledge-agent

by @thedotmackv
4.4(120)

该技能能从历史观察数据中构建并查询AI驱动的知识库,为AI智能体提供定制化的“大脑”。它允许用户根据项目、概念或时间范围筛选信息,快速创建专注于特定主题的知识集合,从而帮助智能体记住用户偏好、理解复杂情境并高效回答关于过去工作模式或专业领域的问题。

knowledge-managementinformation-retrievalai-agent-memorycontext-managementsemantic-searchGitHub
安装方式
npx skills add https://github.com/thedotmack/claude-mem --skill knowledge-agent
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Before / After 效果对比

1
使用前

在没有知识代理的情况下,手动筛选大量项目文档和历史观察记录,以收集特定信息或回答复杂问题。这通常需要数小时,且容易遗漏关键细节或获取过时信息。

使用后

使用知识代理,通过快速构建一个专注于相关主题的知识库,并进行对话式查询,即时获得精确且上下文感知的答案,大大减少了信息检索的时间和精力。

SKILL.md

Knowledge Agent

Build and query AI-powered knowledge bases from claude-mem observations.

What Are Knowledge Agents?

Knowledge agents are filtered corpora of observations compiled into a conversational AI session. Build a corpus from your observation history, prime it (loads the knowledge into an AI session), then ask it questions conversationally.

Think of them as custom "brains": "everything about hooks", "all decisions from the last month", "all bugfixes for the worker service".

Workflow

Step 1: Build a corpus

build_corpus name="hooks-expertise" description="Everything about the hooks lifecycle" project="claude-mem" concepts="hooks" limit=500

Filter options:

  • project — filter by project name
  • types — comma-separated: decision, bugfix, feature, refactor, discovery, change
  • concepts — comma-separated concept tags
  • files — comma-separated file paths (prefix match)
  • query — semantic search query
  • dateStart / dateEnd — ISO date range
  • limit — max observations (default 500)

Step 2: Prime the corpus

prime_corpus name="hooks-expertise"

This creates an AI session loaded with all the corpus knowledge. Takes a moment for large corpora.

Step 3: Query

query_corpus name="hooks-expertise" question="What are the 5 lifecycle hooks and when does each fire?"

The knowledge agent answers from its corpus. Follow-up questions maintain context.

Step 4: List corpora

list_corpora

Shows all corpora with stats and priming status.

Tips

  • Focused corpora work best — "hooks architecture" beats "everything ever"
  • Prime once, query many times — the session persists across queries
  • Reprime for fresh context — if the conversation drifts, reprime to reset
  • Rebuild to update — when new observations are added, rebuild then reprime

Maintenance

Rebuild a corpus (refresh with new observations)

rebuild_corpus name="hooks-expertise"

After rebuilding, reprime to load the updated knowledge:

Reprime (fresh session)

reprime_corpus name="hooks-expertise"

Clears prior Q&A context and reloads the corpus into a new session.

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统计数据

安装量5.2K
评分4.4 / 5.0
版本
更新日期2026年9月14日
对比案例1 组

用户评分

4.4(120)
5
37%
4
43%
3
13%
2
5%
1
2%

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🤖claude-code

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创建2026年5月28日
最后更新2026年9月14日
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