claudemem — Your Persistent Memory
Memory that carries across conversations. Automatically captures important knowledge during work
and saves structured session summaries when you're done. Searches past context before new tasks.
Slash Commands
- /wrap-up — End-of-session save: extracts ALL important knowledge + saves session summary in one step. Deduplicates automatically.
- /save-session — Save only the session summary (without extracting notes)
- /recall [topic] — Search persistent memory for a topic, or show recent activity
Natural Trigger Phrases
These natural phrases also activate memory operations:
To save knowledge:
- "remember this" / "save this" / "note this down" / "keep this in mind"
To search memory:
- "what do you remember about..." / "do you recall..." / "what do we know about..."
To wrap up (save everything):
- "wrap up" / "let's wrap up" / "save everything" — triggers /wrap-up (notes + session)
- "save this session" / "summarize what we did" — triggers /save-session (session only)
To recall past work:
- "what did we do last time" / "show me recent sessions" / "what happened with [topic]"
Setup
Before first use, verify the CLI is installed. If
is not found on PATH, install it:
bash
curl -fsSL https://raw.githubusercontent.com/zelinewang/claudemem/main/skills/claudemem/scripts/install.sh | bash
Or run the bundled installer:
bash
bash "SKILL_DIR/scripts/install.sh"
After installation, verify with
.
Commands
bash
# Notes (knowledge fragments)
claudemem note add <category> --title "..." --content "..." --tags "tag1,tag2"
claudemem note search "query" [--in category] [--tag tags]
claudemem note list [category]
claudemem note get <id>
claudemem note update <id> --content "..." [--title "..."] [--tags "..."]
claudemem note append <id> "additional content"
claudemem note delete <id>
claudemem note categories
claudemem note tags
# Sessions (conversation summaries)
claudemem session save --title "..." --branch "..." --project "..." --session-id "..." --content "..."
claudemem session list [--last N] [--date today] [--date-range 7d] [--branch X]
claudemem session search "query" [--branch X]
claudemem session get <id>
# Unified search (across notes AND sessions)
claudemem search "query" [--type note|session] [--limit N]
# Statistics
claudemem stats
# Configuration
claudemem config set/get/list/delete <key> [value]
# Data portability
claudemem export [output-file] # Backup as tar.gz
claudemem import <archive-file> # Restore from backup (auto-reindexes)
# Data integrity
claudemem verify # Check DB-file consistency
claudemem repair # Fix orphaned entries
Add
to any command for structured output.
Autonomous Behavior
Recommended: Auto Wrap-Up Before Session Ends
If the user has enabled auto wrap-up in their CLAUDE.md, automatically execute /wrap-up before the conversation ends:
- Extract unsaved knowledge fragments → save as notes (with dedup)
- Generate session summary → save as session
- Show brief report of what was saved
Auto-Save Notes (Silent + Brief Indicator)
Automatically capture knowledge without asking during normal conversation. After saving,
add a brief indicator at the end of your response so the user knows what was captured:
[📝 Saved: "TikTok Rate Limits" → api-specs]
What to auto-save (proactive, no user prompt needed):
- API specs, field mappings, rate limits, endpoint details
- Technical decisions with rationale (why X over Y)
- Integration quirks, gotchas, workarounds
- Resolved bugs and their root causes
- Configuration requirements and defaults
- User preferences and project conventions
- Important URLs, endpoints, environment configs
How to auto-save gracefully:
- Identify the knowledge fragment during your normal response
- Choose an appropriate category (create new if none fits)
- Before saving, quickly search to avoid duplicates:
claudemem note search "keyword" --format json
- If related note exists:
claudemem note append <id> "new info"
- Save:
claudemem note add <category> --title "..." --content "..." --tags "..."
- Show the indicator:
[📝 Saved: "<title>" → <category>]
Do NOT auto-save:
- Temporary debugging output or transient state
- File paths or code snippets without context
- General programming knowledge available in docs
- Information the user is likely to change immediately
Auto-Search Before Tasks (Silent)
Search memory at the start of tasks that might benefit from prior context:
- Before implementing a feature in a domain previously discussed
- When working with an API or system previously documented
- Before making architectural decisions
Search silently. If relevant results found, mention them briefly:
[🔍 Found related memory: "TikTok Rate Limits" — rate limit is 100/min]
Save Sessions (On Request via /save-session or Natural Phrase)
Session summaries are saved when the user explicitly asks — via
command
or natural phrases like "save this session" or "wrap up". Do NOT auto-save sessions
without the user's request, as they may want to continue the conversation.
Workflow Rules
- Before saving: search existing content first — update or append if related note exists
- Before working: search for relevant context that may inform the current task
- Merge related information under existing categories/titles when possible
- Preserve existing content unless contradicted by new information
- Focus on evergreen knowledge, not transient conversation artifacts
Session Summary Template
When saving a session, generate content following this structure:
markdown
## Summary
One or two paragraphs describing what was accomplished.
## Key Decisions
- Decision 1 with rationale
- Decision 2 with rationale
## What Changed
- `path/to/file.py` — Description of change
## Problems & Solutions
- **Problem**: Description of issue
**Solution**: How it was resolved
## Questions Raised
- Open question needing future attention
## Next Steps
- [ ] First follow-up task
What NOT to Capture
- Temporary debugging sessions or transient state
- File paths or code snippets without context
- General programming knowledge available in docs
- Meta-commentary about the conversation itself
- Information that changes frequently without lasting value
Data Portability
All data stored at
as plain Markdown files with YAML frontmatter.
SQLite FTS5 index is a rebuildable cache — only the Markdown files matter.
Backup:
claudemem export backup.tar.gz
:
claudemem import backup.tar.gz
(auto-rebuilds search index)
Storage
— Plain text Markdown files organized by type (notes/ and sessions/).
FTS5 SQLite index for sub-10ms full-text search. File permissions: 0600/0700.