name: memory-management description: Manages long-term memory for users across conversations. Automatically queries relevant memories when starting a new topic, and saves important personal information, habits, schedules, and user-requested memories. Use this when discussing user background, preferences, or plans; starting a new task or project; users mention personal details or ask to remember something.

Memory Management Skill

This skill enables Claude to maintain persistent memory of user information across conversations through the Memory MCP Server.

Query Strategy (When & How)

When to Query: 1) New conversation/topic start - query relevant memories for context. 2) User references background ("As I mentioned...") - query related past discussions. 3) Topic resumption - verify previous context. 4) Explicit recall requests. Query once per topic, don't re-query repeatedly.

Recommended Flow: In new conversations, call list_memory_titles FIRST to see all available memories, then use read_memory with specific filenames or keywords to retrieve relevant ones. This improves recall accuracy significantly.

What to Save as Long-Term Memory

Personal Info: Name, contact, location, education, professional role, career goals, timezone preferences. Dev Habits: Languages/frameworks, preferred tools/IDEs, code style standards, testing/deployment practices, architecture patterns, learning style. Schedule: Working hours, timezone, recurring meetings, deadlines, planned leave, regular activities. Context: Current projects & status, team composition, constraints/requirements, past decisions & rationale, ongoing challenges. User-Requested: Always save when users say "remember that...", "save that I...", "note that..." - capture the intent.

Available Tools

list_memory_titles

Purpose: Discover all available memories. Call this FIRST in new conversations to see what memories exist. Input: None required Output: One memory per line in format filename|title|priority|lastAccessedAt, e.g. work-schedule.md|工作安排|P1|2026-02-10T08:00:00.000Z Usage: list_memory_titles() → Review titles and priorities → Then call read_memory with relevant keywords or filenames

read_memory

Purpose: Retrieve memories, optionally filtered by search query. Input: { "query": "optional search term" } - If omitted, returns all memories. Usage: read_memory(query="TypeScript practices") or read_memory() for all

write_memory

Purpose: Create a new memory entry with optional priority. Input: { "title": "Brief searchable title", "content": "Full memory content with details", "priority": "P0|P1|P2 (optional, default P2)" } Priority Guide: P0 = core identity, long-term preferences, safety rules (never evicted). P1 = current projects, active strategies (evicted after 90 days without access). P2 = one-off events, debug notes, temporary preferences (evicted after 30 days without access). Usage: write_memory(title="User Dev Habits", content="Prefers TypeScript...", priority="P1")

update_memory

Purpose: Update an existing memory. Critical: Preserve original content - only append or modify specific parts, NEVER summarize. Input: { "filename": "current-filename.md", "title": "Updated title", "content": "Updated content (must preserve original)", "priority": "P0|P1|P2 (optional, keeps current)" } Rules: Original 2000-word memory + 40 new words = ~2040 words result, NOT 540 words. Append new info or modify conflicting parts only.

delete_memory

Purpose: Delete a memory entry permanently (not archived). Input: { "filename": "filename-to-delete.md" }

search_archive

Purpose: Search archived (evicted) memories. Use when current memories don't have the answer — old memories may be in the archive. Input: { "query": "search term" } Usage: When read_memory returns nothing relevant, try search_archive(query="Python pipeline") to check cold storage.

evict_memories

Purpose: Manually trigger memory eviction sweep. Normally runs automatically on read (at most once per 24h). Input: { "dryRun": true|false (optional, default false) } Usage: evict_memories(dryRun=true) to preview what would be archived, then evict_memories() to execute.

Implementation Guidelines

Query Strategy: On conversation start → list_memory_titles() first, then query with specific keywords. On topic shift → query specific topic keywords. One query per topic. Respect "no memory" requests by deleting.

Save Strategy: Immediate save for explicit requests ("remember X"). Natural save points after personal details discussion, project completion, learning preferences. Consolidate by updating existing memories rather than creating duplicates. Assign appropriate priority: P0 for identity/preferences, P1 for active projects, P2 for transient info.

Format: Use searchable keyword titles. Organize with bullet points/sections. Include context about when info was learned. Update timestamps on changes. Remove outdated info.

Examples

New Project: User mentions "starting React/TypeScript project" → 1) list_memory_titles() 2) read_memory(query="React projects") 3) After discussion: write_memory(title="React Project 2025", content="...", priority="P1")

Personal Preference: User says "I prefer morning work until 2PM" → Immediately: write_memory(title="Working Hours", content="Prefers mornings until 2PM", priority="P0")

Topic Continuation: User says "Back to that Python pipeline..." → read_memory(query="Python pipeline") → If not found: search_archive(query="Python pipeline") → Continue with full context

Temporary Note: User debugs a timezone issue → write_memory(title="TZ Debug", content="Server uses UTC, local is CST+8", priority="P2")

Important Reminders

🔒 Privacy: User memories isolated by token. ⚡ Efficiency: Query once per topic, use list_memory_titles first for discovery. 📝 Clarity: Searchable titles for easy retrieval. 🤝 Respect: Ask before saving sensitive info (except explicit requests). 🔄 Maintenance: Update when info changes, delete when obsolete. 💬 Transparency: Optionally acknowledge "I remembered that you..."

Boundaries

This skill does NOT handle: Temporary conversation context (use normal history), real-time system info/API responses, private info user wants to keep private (ask first), system-level configuration.