Let AI save knowledge automatically
Three safeguards help preserve knowledge from every conversation.
Start with zero configuration, then add explicit project instructions and manual control.
Three layers of protection
Use the combination that matches how much control you need.
Before you begin: Connect KnowMine to your AI through MCP.Not connected yet? Open the connection guide →
Layer 1: Automatic AI detection
Active after connecting · no configuration
How it works
After an AI client such as Claude Code or Claude Desktop connects to KnowMine MCP, it can recognize valuable content and call save_memory to save it. KnowMine uses five knowledge types:
decision"Choose pgvector instead of Pinecone because it costs less and PostgreSQL is already in use."
lesson"Do not configure a proxy in the VS Code extension because it breaks the OAuth flow."
insight"AI memory benefits from Trace, Memory, and Soul layers with different lifecycles."
preference"The user expects asynchronous work to include retries and observable status."
domain_knowledge"MCP can use Streamable HTTP transport and support stateless deployment."
Note: This layer is probabilistic. AI may not save something every time because the decision depends on the model and conversation context. Layers 2 and 3 provide explicit safeguards.
Layer 2: CLAUDE.md instructions
Check at important moments · Claude Code only
What is CLAUDE.md?
CLAUDE.md is Claude Code’s project-level instruction file. Put it in the project root and Claude Code reads it at the start of every conversation, giving AI a reusable working guide.
Setup (about two minutes)
01Open or create CLAUDE.md
Find or create CLAUDE.md in the root of your project.
02Append these instructions
The block includes automatic checks and a /distill shortcut. Copy both together:
## KnowMine automatic knowledge saving
At these moments, proactively check whether the conversation contains knowledge worth saving:
1. After completing a feature
2. After resolving a bug
3. After making a technical decision
4. After discussing a complex topic
Save one of these five types:
- **decision**: What was decided, and why was A chosen over B?
- **lesson**: What went wrong, what was the root cause, and how was it fixed?
- **insight**: What valuable insight or idea emerged?
- **preference**: What working preference or habit was discovered?
- **domain_knowledge**: What specialized knowledge was discussed?
When something is worth keeping, call the save_memory tool.
Do not save temporary debugging details, raw code snippets, or intermediate output.
## Shortcut
When the user says /distill or /沉淀, review the current conversation, extract the 1–3 most valuable pieces of knowledge, and call save_memory to store them in KnowMine.Or copy each part separately —
03Save the file
The instructions take effect in the next Claude Code conversation. No restart is required.
What changes after setup
After completing a feature — AI checks for decisions or lessons worth saving
After fixing a bug — AI captures the cause and fix so the team can avoid repeating it
After a technical choice — AI records the reasoning for future reference
Say /distill or /沉淀 — AI reviews the conversation and saves 1–3 high-value items
Layer 3: Manual trigger
Save on demand · works on every platform
How to trigger a save
In any AI conversation connected to KnowMine, use one of these prompts:
/distillEnglish shortcut
/沉淀Chinese shortcut
Save this to my knowledge baseNatural-language trigger
Save the decision we just made to my knowledge baseSave a specific part of the conversation
When to use it
• A useful idea appears and you do not want to lose it → /distill
• You finished a complex discussion and want to preserve the conclusion → /distill
• The conversation is ending and you want a final knowledge check → /distill
Other AI platforms
Not using Claude Code? Other platforms can still use Layer 1 (automatic) and Layer 3 (manual):
Claude Desktop
Layer 1 + 3
ChatGPT
Layer 1 + 3
Cursor / VS Code
Layer 1 + 3
Claude Code
Layer 1 + 2 + 3
Layer 2 (CLAUDE.md instructions) is specific to Claude Code. On other platforms, connect through MCP and use a prompt to trigger saving.
Start building reusable knowledge
After setup, each thoughtful AI conversation can become knowledge you can reuse.