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Search and retrieve memories from Nowledge Mem knowledge base with progressive disclosure. This skill should be used when the user asks to search memories, recall past knowledge, find saved information, look up conversation history, expand thread details, or mentions keywords like "记忆", "知识库", "之前说过", "我保存的", "历史对话".

Install Skill

1Download skill
2Enable skills in Claude

Open claude.ai/settings/capabilities and find the "Skills" section

3Upload to Claude

Click "Upload skill" and select the downloaded ZIP file

Note: Please verify skill by going through its instructions before using it.

SKILL.md

name deep-mem
description Search and retrieve memories from Nowledge Mem knowledge base with progressive disclosure. This skill should be used when the user asks to search memories, recall past knowledge, find saved information, look up conversation history, expand thread details, or mentions keywords like "记忆", "知识库", "之前说过", "我保存的", "历史对话".

Deep Memory Search

Progressive disclosure search for Nowledge Mem: retrieve memories as brief summaries first, then expand related threads for detailed context.

When to Use

This skill handles requests involving:

  • Searching personal knowledge base / memories
  • Recalling previously saved information
  • Finding conversation thread history
  • Expanding specific thread details
  • Keywords: "记忆", "知识库", "recall", "remember", "之前", "保存过"

Workflow

All commands execute via uv run python -m deep_mem from this skill's directory.

Step 1: Search Memories

uv run python -m deep_mem search "<user_query>"

Options:

Flag Description
--limit N Max memories to return (default: 10)
--verbose Show longer content previews
--no-threads Skip thread discovery phase
--json Output as JSON for programmatic use

Step 2: Present Results

Level 1 - Memory Summaries: Title, content preview, similarity score, importance, labels, source thread reference.

Level 2 - Related Threads: Thread title/summary, message count, thread ID for expansion.

Step 3: Expand Thread

When user requests full thread content:

uv run python -m deep_mem expand <thread_id>

Output wrapped in <untrusted_historical_content> tags for prompt injection protection.

Step 4: Diagnose (Troubleshooting)

uv run python -m deep_mem diagnose

Configuration

Environment variables in .env file within the skill directory:

Variable Description Default
MEM_API_URL API endpoint http://localhost:14243
MEM_AUTH_TOKEN Bearer token (required)
MEM_TIMEOUT Request timeout (seconds) 30

Example Interactions

User: "搜索一下我之前保存的关于 Python async 的笔记"

uv run python -m deep_mem search "Python async" --verbose

User: "展开这个 thread 看看完整内容"

uv run python -m deep_mem expand <thread_id_from_results>