diegosouzapw 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>